The combination of wet-lab experimental data on multi-site combinatorial mutations and machine learning is an innovative method in protein engineering. In this study, we present an improved innovative sequence–activity relationship (innov'SAR) methodology based on novel descriptors and digital signal processing (DSP) to construct a predictive model. In this improved approach, 21 experimental (R)-selective amine transaminases from Aspergillus terreus (AT-ATA) were used as an input to predict higher thermostability than that predicted using the existing data. We successfully improved the determination coefficient (R2) of the model from 0.66 to 0.92. In addition, root mean square deviation (RMSD) and root mean square fluctuation (RMSF) were estimated and conformation analysis based on molecular dynamics simulations was performed to verify the enhanced thermal stability of the screened mutants. The improved innov'SAR algorithm enhanced the predictive accuracy, suggesting a method for modifying the stability of AT-ATA, which may help in directed evolutionary screening and open up new avenues for protein engineering.

The incorporation of polycarboxylate ether superplasticizer (PCE) type polymer and silica fume (SF) in high-performance concretes (HPC) leads to the achievement of remarkable rheological and mechanical improvements. In the fresh state, PCEs are adsorbed on cement particles and dispersants, in turn promoting the workability of the concrete. Silica fume enables a very well compacted concrete to be obtained, which is characterized by high mechanical parameters in its hardened state. Some PCEs are incompatible with silica fume, which can result in the loss of slump and in poor rheological behavior. The main objective of the research is the study of the influence of three types of PCEs, which all have a different molecular architecture, on the rheological and mechanical behavior of high-performance concretes containing 10% of SF as a partial replacement of cement. The results show that the carboxylic density of PCE has an influence on its compatibility with SF.

There has recently been interest in the development of small-molecule inhibitors of the oligomerization of Bacillus anthracis protective antigen for therapeutic use. Some of the proposed lead compounds have, however, unfavorable solubility in aqueous medium, which prevents their clinical use. In this computational work, we have designed several hundreds of derivatives with progressively higher hydrosolubility and tested their ability to dock the relevant binding cavity. The highest-ranking docking hits were then subjected to 125 ns-long simulations to ascertain the stability of the binding modes. Several of the potential candidates performed quite disappointingly , but two molecules showed very stable binding modes throughout the complete simulations. Besides the identification of these two promising leads, these molecular dynamics simulations allowed the discovery of several insights that shall prove useful in the further improvement of these candidate towards higher potency and stability.

Innovations in drug delivery systems are crucial for enhancing therapeutic efficiency. Our research presents a novel approach based on Electro-fluid dynamic atomization (EFDA) to fabricate core-shell monophasic particles (CSMp) from sodium alginate blends of varying molecular weights. This study explores the morphological characteristics of these particles in relation to material properties and process conditions, highlighting their potential in drug delivery applications. A key aspect of our work is the development of a mathematical model that simulates the release kinetics of small molecules, specifically sodium diclofenac. By assessing the diffusion properties of different molecules and gel formulations through transport and rheological models, we have created a predictive tool for evaluating the efficiency of these particles in drug delivery. Our findings underscore two critical independent parameters for optimizing drug release: the external shell thickness and the diffusivity ratios within the dual layers. This allows for precise control over the timing and intensity of the release profile. The study advances our understanding of EFDA in the fabrication of CSMp and offers promising avenues for enhancing drug delivery systems by tailoring release profiles through particle characteristic manipulation.

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative and antineoplastic activities. Recently, different studies have shown that flavonoid have the potential to inhibit BET bromodomains. Previous reports suggest that flavonoids are putative inhibitors of the ZA channel due to their orientation and interactions with P86, V87, L92, L94 and N140. Herein, a comprehensive characterization of the binding mode of the biflavonoid amentoflavone and fisetin is discussed. To this end, both compounds were docked with BRD4 using four docking programs. Results were post-processed with protein-ligand interaction fingerprints. To gain further insights into the binding mode of the two natural products, docking results were further analyzed with molecular dynamics. Results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as basis for scaffold optimization and further characterization of flavonoids as BET inhibitors.

Explosive boiling is a fast phase transition from an ultra-thin liquid film to vapor under an extremely high heat flux, which typically has been studied using molecular dynamics simulation (MDS) method. The present MDS study investigated the explosive boiling of a liquid argon nanofilm over different solid copper surfaces with different nanowall patterns including parallel and cross nanowalls. For each surface, atomic motion trajectories, number of liquid and vapor argon atoms, heat flux, and, mainly, onset time of explosive boiling were investigated. The simulation results indicated that explosive boiling occurs earlier on parallel and cross nanowall surfaces than on an ideally smooth surface, regardless of the topology and configuration of nanowalls. Moreover, the results revealed that by using the cross nanowall surfaces, the onset time of explosive boiling decreased by 0.7–4% compared to the parallel nanowall surfaces. In addition, it was found that the onset time of explosive boiling strongly depends on the potential energy barrier and the movement space between nanowalls for both parallel and cross nanowall surfaces. Furthermore, simulation findings showed that even though increasing the height of cross nanowalls increases heat flux and temperature of the fluid argon domain, it does not necessarily result in a shorter onset time of explosive boiling. These findings demonstrate the capability of cross nanowall surfaces for explosive boiling, thereby could be utilized in future surface design for thermal management applications.

The factors that determine the relative rates of amino acid substitution during protein evolution are complex and they are known to vary among taxa. We estimated relative exchangeabilities for pairs of amino acids from clades spread across the tree of life and assessed the historical signal in the distances among these clade-specific models. We trained these models separately on collections of arbitrarily selected protein alignments and on ribosomal protein alignments. In both cases we found a clear separation between the models trained using multiple sequence alignments from bacterial clades and the models trained on archaeal and eukaryotic data. We assessed the predictive power of our novel clade-specific models of sequence evolution by asking whether fit to the models could be used to identify the source of multiple sequence alignments. Model fit was generally able to classify protein alignments correctly at the level of domain (bacterial versus archaeal), but the accuracy of classification at finer scales was much lower. The only exceptions to this were the relatively high classification accuracy for two archaeal lineages: Halobacteriaceae and Thermoprotei. Genomic GC content had a modest impact on relative exchangeabilities despite having a large impact on amino acid frequencies. Relative exchangeabilities involving aromatic residues exhibited the largest differences among models. There were a small number of exchangeabilities that exhibited large differences in comparisons among major clades and between generalized models and ribosomal protein models. Taken as a whole, these results reveal that a small number of relative exchangeabilities are responsible for much of the structure of the “model space” for protein sequence evolution. If we look beyond the information that these clade-specific models reveal about protein evolution the models themselves are likely to be useful tools for phylogenomic inference across the tree of life.

Zinc finger proteins (ZFP) play important roles in cellular processes. The DNA binding region of ZFP consists of 3 zinc finger DNA binding domains connected by amino acid linkers, the sequence TGQKP connects ZF1 and ZF2, and TGEKP connects ZF2 with ZF3. Linkers act to tune the zinc finger protein in the right position to bind its DNA target, the type of amino acid residues and length of linkers reflect on ZF1-ZF2-ZF3 interactions and contribute to the search and recognition process of ZF protein to its DNA target. Linker mutations and the affinity of the resulting mutants to specific and nonspecific DNA targets were studied by MD simulations and MM_GB(PB)SA. The affinity of mutants to DNA varied with type and position of amino acid residue. Mutation of K in TGQKP resulted in loss in affinity due to the loss of positive K interaction with phosphates, mutation of G showed loss in affinity to DNA, WT protein and all linker mutants showed loss in affinity to a nonspecific DNA target, this finding confirms previous reports which interpreted this loss in affinity as due to ZF1 having an anchoring role, and ZF3 playing an explorer role in the binding mechanism. The change in ZFP-DNA affinity with linker mutations is discussed in view of protein structure and role of linker residues in binding.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

Background: Colorectal cancer is considered the third most fetal among all type of cancer. Spleen tyrosine kinase (SYK) is a non-receptor type tyrosine-protein that plays crucial role in signaling mediated via immune receptor. We adopted an onco-informatics analysis to evaluate the SYK expression and prognostic value of SYK in colorectal cancer, and identification of potential phytochemicals which may inhibit overexpression of SYK protein as well as minimized colorectal cancer. Materials & Methods: Differential expression of SYK gene was analyzed using the several transcriptomic databases including Oncomine, UALCAN, GENT2 and GEPIA2. The server, cBioPortal was used to analyze mutation and copy number alterations whereas GENT2, GEPIA, OncoLnc and PrognoScan were employed to examine the survival rate. A protein-protein interaction network of SYK and co-expressed genes of SYK was conducted via GeneMANIA. Considering SYK gene encoding protein as drug target, selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. YASARA molecular dynamics simulators were applied for the post validation of the molecular docking data. Results: We have observed significant overexpression of mRNA expression levels of SYK gene colorectal adenocarcinoma (COAD) samples compared with normal tissues. Significant methylation level and various genetic alterations are assembled in SYK gene which can lead to the development of colorectal cancer. As a result, lower level of SYK expression was related to the more chances of patients’ survival by which all the outcomes from the multiple bioinformatics platforms and web resources have demonstrated the significant evidences that the SYK kinsase can possess as a potential biomarker for the treatment of colorectal cancer. Here, aromatic phytochemicals namely, Kaempferol and Glabridin targeting SYK showed more stability compared to controls and may be useful for the treatment of colorectal cancer. Conclusion: Our study showed dysregulated expression of SYK in colorectal cancer and potentiality to act as a biomarker for the prognosis of CRC. Moreover, we have shown phytochemicals (Kaempferol and Glabridin) target SYK as potential treatment strategies and drug repositioning potentiality in colorectal cancer.

Dysregulation of the arsenal of cells, growth factors, cytokines, proteases, and proteins involved in wound healing (WH), could delay the healing process. Plants and plant-derived molecules (PDMs) have been used as medicines for skin wounds. This study aimed to select and evaluate the pro-healing capacity of PMDs. Thirty-three PDMs and 10 therapeutic targets (TTs) were chosen for molecular docking and PDMs: aristolochic acid (AA), α-copaene, selinenes, β-caryophyllene (BC), and BCoxide, and TTs: metalloproteinase (MMP) 3, MMP13, and tumor necrosis factor (TNF α) for molecular dynamics. The bests inhibitor was AA, but because of its toxicity, BC and BCoxide were chosen for evaluation in HaCat cells and BALB/c mice excisional model. Both compounds were not toxic, and higher percentages of lesion area closure (LAC) were induced by BC treatment (p<0.05). All mice healed; however, an initial delay of LAC was induced by 0.05, 0.1% BCoxide, 0.1% BC, and allantoin. At the end of treatment, lower numbers of mast cells, level of cellular infiltrates (except 1% BCoxide and 0.05, 0.5%BC), epidermal thickness tendency (except 0.1, 0.5% BCoxide), and higher values of SC-thickness, and collagen fibers only by 0.5% BC treatment compared with untreated control (p<0.05) were observed. Our results show that BC is a promising multitarget candidate for wound healing treatment and optimization campaigns.

In this report we have discussed the important role of molecular modeling, especially the use of the molecular dynamics method, in investigating transport processes in nanoporous materials such as membranes. With the availability of high performance computers, molecular modeling can now be used to study rather complex systems at a fraction of the cost or time requirements of experimental studies. Molecular modeling techniques have the advantage of being able to access spatial and temporal resolution which are difficult to reach in experimental studies. For example, sub-Angstrom level spatial resolution is very accessible as is sub-femtosecond temporal resolution. Due to these advantages, simulation can play two important roles: Firstly because of the increased spatial and temporal resolution, it can help understand phenomena not well understood. As an example, we discuss the study of reverse osmosis processes. Before simulations were used it was thought the separation of water from salt was purely a coulombic phenomenon. However, by applying molecular simulation techniques, it was clearly demonstrated that the solvation of ions made the separation in effect a steric separation and it was the flux which was strongly affected by the coulombic interactions between water and the membrane surface. Additionally, because of their relatively low cost and quick turnaround (by using multiple processor systems now increasingly available) simulations can be a useful screening tool to identify membranes for a potential application. To this end, we have described our studies in determining the most suitable zeolite membrane for redox flow battery applications. As computing facilities become more widely available and new computational methods are developed, we believe molecular modeling will become a key tool in the study of transport processes in nanoporous materials.

The SARS-CoV-2 have caused a devastating pandemic of all times in the recent human history. However, there is a serious paucity in high quality data on aggravating factors and mechanisms of co-infection. This study aimed to identify the trending patterns of bacterial co-infections and types and associated outcomes in three phases of the pandemic. Using quality hospital data, we have investigated the SARS-CoV-2 fatality rates, profiles, and types of bacterial co-infections before, during, and after COVID-19 vaccinations. Out of 389 isolates used in different aspects, 298 was examined before and during the pandemic (n=149 before, n=149 during), death rates were 32% during compared to only 7.4% before pandemic with significant association (P value = 0.000000075). Death rate was 34% in co-infected (n = 170) compared to non-co-infected patients (n = 128) indicating a highly significant value (P value = 0.00000000000088). However, analysis of patients without other respiratory problems (n=28) indicated that among the remaining 270 patients, death was 30% in co-infected patients (n=150) and only 0.8% in non-coinfected (n=120) with high significant P value= 0.00000000076. The trending patterns of co-infections before, during, and after vaccinations showed a significant decline in Staphylococcus aureus with concomitant peaks in Gram-negatives in totals of (n= 149 before/n= 149 during): Klebsiella pneumonia (n = 11/49 before/during; E. coli n=10/24, A. baumannii n=8/25, and Ps. Aeruginosa n= 5/16, and S. aureus 13/1. Nevertheless, in post vaccination phase, (n= 91) gender-specific co-infections were examined for potential differences in susceptibility. Methicillin resistant S. aureus (MRSA) dominated both genders followed by E. coli in males and females with the latter gender showing higher rates of isolations in both species. Klebsiella pneumoniae declined to third place mostly in male patients. The drastic decline in K. pneumoniae and Gram-negatives post-vaccination strongly imply a potential co-protection in vaccines. Future analysis would gain more insights into molecular mimicry.

Lily database online genomic resource composed of Korean Lily Germplasm Collection, Transcriptome Sequences, molecular markers, transcription factors (TF) and DEGs data. A total of ~0.23 gb of RNA-sequences data were mined for gene identification, marker development and gene expression analysis. As a result, 47,863 SSR, 20,929 SNP and 1213 COS-marker were developed. A total of 1327 TF genes were identified and characterized. This is the first unique, user-friendly, genomic resource database for Lilium species. It is a relational database based on a ‘three-tier architecture’ that catalogs all the information in MySQL table and a user-friendly query interface and data visualization page developed using JavaScript, PHP and HTML code. The search parameters are highly flexible, user can be retrieved data by using either single or multiple search parameters. Data present in this database can be used for germplasm characterization, gene discovery, population structure analysis, QTL mapping and accelerating the lily variety improvements. This database can be accessed through this link: http://www.genomicsres.org/lilidb/.

The anterior cruciate ligament (ACL) is a critical structure within the knee joint, primarily responsible for maintaining stability and enabling the knee to perform a wide range of movements essential for both everyday activities and athletic performance. It functions as a key stabilizer by preventing excessive forward movement of the tibia relative to the femur and by controlling rotational forces that occur during activities such as pivoting, cutting, and jumping. The biomechanical integrity provided by the ACL is crucial, especially during dynamic activities that place significant strain on the knee joint, making it indispensable for athletes and active individuals. However, due to its pivotal role and the considerable mechanical demands placed upon it, the ACL is particularly vulnerable to injury. ACL injuries are prevalent, especially among athletes involved in high-risk sports such as soccer, basketball, football, and skiing, where rapid changes in direction, sudden stops, and direct impacts are common. The incidence of ACL injuries is a significant concern in sports medicine, not only because of the immediate impact on an athlete's career but also due to the long-term health implications associated with such injuries. These injuries often result in complex, multifaceted complications, including persistent joint instability that can compromise the structural and functional integrity of the knee, leading to recurrent injuries and reduced performance levels. One of the more insidious consequences of ACL injuries is the loss of proprioception, the body's ability to sense the position, movement, and action of the joints. Proprioception is vital for coordinated movement and balance, and its impairment can lead to a diminished capacity to control knee movements, further increasing the risk of re-injury. Additionally, the long-term sequelae of ACL injuries often include the development of post-traumatic osteoarthritis, a degenerative condition characterized by the gradual breakdown of joint cartilage and underlying bone. This condition not only causes chronic pain and stiffness but can also significantly impair an individual's quality of life, limiting their ability to engage in physical activities and, in severe cases, leading to disability. Despite the remarkable progress made in the fields of orthopedic surgery and sports rehabilitation, the recovery process following an ACL injury remains challenging. Surgical techniques, such as ACL reconstruction, have evolved to offer more reliable outcomes, and rehabilitation protocols have been refined to promote quicker and more effective recovery. However, the reality is that many patients do not achieve the level of recovery needed to return to their pre-injury level of activity or to maintain long-term knee health. This suboptimal recovery is often attributed to the complex interplay of neurophysiological and molecular factors that are not yet fully understood. Neurophysiologically, the recovery from an ACL injury involves not only the physical repair of the ligament but also the re-establishment of neuromuscular control and the adaptation of the central nervous system (CNS) to the altered mechanics of the knee. The CNS plays a crucial role in modulating the body's response to injury, influencing the way muscles activate and coordinate to protect the injured joint. However, disruptions in neuromuscular control post-injury can lead to compensatory movement patterns that may predispose individuals to further injury or hinder their recovery. Understanding these neurophysiological changes is essential for developing rehabilitation strategies that address not just the mechanical aspects of recovery but also the re-training of the neuromuscular system. On the molecular level, the healing process of the ACL involves a cascade of cellular and biochemical events that are critical for tissue repair and regeneration. These processes include the inflammatory response, cell proliferation, and the remodeling of the extracellular matrix, all of which are regulated by various molecular signals and pathways. Advances in molecular biology have begun to unravel the complexities of these processes, offering insights into how they can be manipulated to enhance healing and reduce the risk of complications such as fibrosis or improper tissue regeneration. By integrating molecular biology with clinical practice, there is potential to develop targeted therapies that can optimize the healing environment, improve surgical outcomes, and accelerate the recovery process. This review aims to provide a comprehensive examination of the neurophysiological aspects of ACL injury and the rehabilitation process, while also exploring the potential contributions of molecular biology to improving treatment outcomes. By delving into the intricate mechanisms that underlie ACL injury and recovery, the review seeks to highlight the challenges that remain in the field and to propose new directions for research that could lead to more effective and individualized treatment approaches. The ultimate goal is to enhance our understanding of ACL injuries and to develop strategies that not only restore knee function but also preserve long-term joint health, allowing individuals to return to their desired level of activity with confidence.

Specialized classes of proteins, working together in a tightly orchestrated manner, induce and maintain highly curved cellular and organelles membrane morphology. Due to the various ex- perimental constraints, including the resolution limits of imaging techniques, it is non-trivial to accurately elucidate interactions among the various components involved in membrane deformation. The spatial and temporal scales of the systems also make it formidable to investigate them using simulations with molecular details. Interestingly, mechanics-based mesoscopic models have been used with great success in recapitulating the membrane defor- mations observed in experiments. In this review, we collate together and discuss the various mechanics based mesoscopic models for protein-mediated membrane deformation studies. In particular, we provide an elaborate description of a mesoscopic model where the membrane is modeled as a triangulated sheet and proteins are represented as either nematics or fila- ments. This representation allows us to explore the various aspects of protein-protein and protein-membrane interactions as well as examine the underlying mechanistic pathways for emergent behavior such as curvature-mediated protein localization and membrane deforma- tion. We also put forward current efforts in the field towards back-mapping these mesoscopic models to finer-grained particle based models - a framework that could be used to explore how molecular interactions propagate to physical scales and vice-versa. We end the review with an integrative-modeling based road map where experimental imaging micrograph and biochemical data are combined with mesoscopic and molecular simulations methods in a theoretically consistent manner to faithfully recapitulate the multiple length and time scales in the membrane remodeling processes.

The epidermal growth factor receptor (EGFR) plays vital roles in cellular processes including cell proliferation, survival, motility and differentiation. Dysregulated activation of the receptor is often implicated in human cancers. EGFR is synthesized as a single-pass transmembrane protein, which consists of an extracellular ligand-binding domain and an intracellular kinase domain separated by a single transmembrane domain. The receptor is activated by a variety of polypeptide ligands such as epidermal growth factor and transforming growth factor α. It has long been thought that EGFR is activated by ligand-induced dimerization of the receptor monomer, which brings intracellular kinase domains into close proximity for trans-autophosphorylation. An increasing number of diverse studies, however, demonstrate that EGFR is present as a pre-formed, yet inactive, dimer prior to ligand binding. Furthermore, recent progress in structural studies has provided insight into conformational changes during the activation of a pre-formed EGFR dimer. Upon ligand binding to the extracellular domain of EGFR, its transmembrane domains rotate or twist parallel to the plane of the cell membrane, resulting in reorientation of the intracellular kinase domain dimer from a symmetric inactive configuration to an asymmetric active form (the “rotation model”). This model is also able to explain how oncogenic mutations activate the receptor in the absence of ligand without assuming that the mutations induce receptor dimerization. In this review, we discuss mechanisms underlying ligand-induced activation of the preformed EGFR dimer, as well as how oncogenic mutations constitutively activate the receptor dimer, based on the rotation model.

Molecular dynamics simulations were carried out to investigate the atomic structure of a model Cu64Zr36 bulk metallic glass (BMG). It is found that the amount of icosahedral content of the system is significantly increased in a well relaxed structure. While we considered four connection types of vertex-, edge-, face-, and volume-sharing, the huge cluster in the relaxed samples mainly involve volume-type connection and exhibits a remarkable athermal plasticity that great stiffness and great yield strength compared to the as-quenched samples. In addition, the bond-angle distribution of annealed sample shows sharp peaks at specific bond angles which is an evidence of crystallized Laves-phase formed by icosahedral atoms, however the peaks are to be broaden after loading, which indicates decreasing amount of icosahedral content and their shape distortion. These results suggest that icosahedral content in a bulk metallic glasses plays a key role to determine the mechanical properties such as rigidity and maximum stress carrying capacity.

Periodontal disease, a multifactorial inflammatory condition affecting the supporting structures of the teeth, has been increasingly recognized for its association with various systemic diseases. Understanding the molecular comorbidities of periodontal disease is crucial for elucidating shared pathogenic mechanisms and potential therapeutic targets. In this study, we conducted comprehensive literature and biological database mining utilizing tools such as DisGeNET2R, Romin, and Rentrez R libraries to identify diseases sharing associated genes, proteins, or molecular pathways with periodontitis. Our analysis revealed significant molecular overlaps between periodontal disease and several systemic conditions, including cardiovascular diseases, diabetes mellitus, rheumatoid arthritis, and inflammatory bowel diseases. Shared molecular mechanisms implicated in the pathogenesis of these diseases and periodontitis encompassed dysregulation of inflammatory mediators, immune response pathways, oxidative stress pathways, and alterations in the extracellular matrix. Furthermore, network analysis unveiled key hub genes and proteins that play pivotal roles in the crosstalk between periodontal disease and its comorbidities, offering potential targets for therapeutic intervention. Insights gained from this integrative approach shed light on the intricate interplay between periodontal health and systemic well-being, emphasizing the importance of interdisciplinary collaboration in developing personalized treatment strategies for patients with periodontal disease and associated comorbidities.

Centromeres, the chromosomal loci where spindle fibers attach during cell division to segregate chromosomes, are typically found within satellite arrays in plants and animals. Satellite arrays have been difficult to analyze because they comprise megabases of tandem head-to-tail highly repeated DNA sequences. Much evidence suggests that centromeres are epigenetically defined by the location of nucleosomes containing the centromere-specific histone H3 variant cenH3, independently of the DNA sequences where they are located; however, the reason that cenH3 nucleosomes are generally found on rapidly evolving satellite arrays has remained unclear. Recently, long read sequencing technology has clarified the structures of satellite arrays and sparked rethinking of how they evolve, while new experiments and analyses have helped bring both understanding and further speculation about the role these highly repeated sequences play in centromere identification.

Objective: To observe the effect of the combination of fluid-increasing decoction, low molecular heparin sodium and aspirin in the treatment of oligohydramnios in pregnancy. Methods: In this study, 114 pregnant women with oligohydramnios during pregnancy admitted to our hospital between May 2019 and March 2022 were selected as objects, and the pregnant women were equally divided into the observation group and the experimental group by random number table method, with 57 cases in each group. The observation group received conventional fluid infusion, low molecular heparin sodium and aspirin, while the experimental group was treated with fluid-increasing decoction on the basis of the observation group. The treatment effect, S/D level, amniotic fluid index, maximum vertical pocket (MVP), coagulation indexes (plasma prothrombin time (PT), plasma activated partial thromboplastin time (APTT), fibrinogen (FIB)), pregnancy outcome and adverse reactions were compared between the two groups. Results: The total effective rate of treatment was obviously better in the experimental group than that in the observation group (P＜0.05); the S/D level after treatment in the experimental group was remarkably lower than that in the observation group (P＜0.05). The amniotic fluid index and MVP were remarkably higher in the experimental group than in the observation group after treatment (P < 0.05). No significant differences in PT, APTT and FIB were found between the two groups before and after treatment (P > 0.05). The rate of oligohydramnios at delivery, cesarean section rate, neonatal weight status and preterm delivery rate were dramatically better in the experimental group than in the observation group (P < 0.05). Post-partum haemorrhage rate, neonatal asphyxia rate, amniotic fluid contamination rate and incidence of adverse events were not significantly different between the two groups of pregnant women (P > 0.05). Conclusion: The combination of fluid-increasing decoction, low molecular heparin sodium and aspirin is clinically effective and safe in the treatment of pregnant women with oligohydramnios during pregnancy. The combination is effective in reducing the S/D ratio of fetal umbilical blood flow, enhancing the amniotic fluid index and MVP in pregnant women with oligohydramnios during pregnancy, whilst not adversely influencing the coagulation function of the mother, thus contributing to a reduction in the risk of adverse pregnancy outcomes.

Coronavirus disease 2019 (COVID-19) was recently appeared all over the world. The viral main protease (3-chymotrypsin-like cysteine enzyme) controls COVID-19 duplication and manages its life cycle, making it a drug discovery target. Therefore, herein, we analyzed the theoretical approaches of 10 structurally different hydrolysable tannins as natural anti-COVID-19 through binding with the main protease of 2019-nCoV using molecular docking modelling via Molecular Operating Environment (MOE v2009) software. Our results revealed that there are top three hits may serve as potential anti-COVID-19 lead molecules for further optimization and drug development to control COVID-19. Pedunculagin, tercatain, and punicalin were found to faithfully interact with the receptor binding site and catalytic dyad (Cys145 and His41) of COVID-19 main protease, showing their successfully inhibit the protease enzyme of 2019-nCoV. We anticipated that this study would pave way for tannins based novel small molecules as more efficacious and selective anti-COVID-19 therapeutic compounds.

Detecting IgE sensitizations in the serum of allergic dogs is commonly done using allergen extracts, but these are difficult to standardize. This article details the development and validation of the Pet Allergy Xplorer (PAX; Nextmune, Stockholm, Sweden), the first multiplex macroarray for the detection of IgE sensitization in dogs using allergen extracts and molecular components; the PAX is derived from the Allergy Xplorer (ALEX2; MacroArray Diagnostics, Vienna, Austria). The selection of allergens, cartridge processing, strategy for identifying and blocking IgE directed against cross-reactive carbohydrate determinants (CCD), and the method used for determining the positivity threshold are described. The validation of the PAX included evaluations of the specificity of its anti-IgE monoclonal antibody, specificity of IgE binding to target allergens, assay precision, and internal consistency. Additionally, the influence of possible confounding factors, such as sample type, the influence of hemolysis, lipemia, bilirubinemia, and elevated CCD-IgE, was tested. Finally, the sensitization rates of 23,858 European dogs to 145 environmental and Hymenoptera venom allergens were summarized. The PAX is accurate and reproducible and has a unique CCD-detection and blocking strategy; its molecular allergens offer a unique window on allergen cross-reactivity.

Drug nanosuspensions offer a promising approach to improve bioavailability for poorly soluble drug candidates. Such formulations often necessitate the inclusion of an excipient to stabilize the drug nanoparticles. However, a rationale to choose the correct excipient for a given drug candidate remains unclear. To gain molecular insight into formulation design, this work first utilizes molecular dynamics simulation to computationally investigate drug-excipient interactions for a number of combinations that have been previously studied experimentally. We find that hydrophobic interactions drive excipient adsorption to drug nanoparticles, and that the fraction of polar surface area serves as a predictor for experimental measurements of nanosuspension stability. To test these ideas prospectively, we applied our model to an uncharacterized drug compound, GDC-0810. Our simulations predicted that salt forms of GDC-0810 would lead to more stable nanosuspensions than the neutral form; therefore, we tested the stability of salt GDC-0810 nanosuspensions and found that the salt form readily formed nanosuspensions even without excipient. To avoid computationally expensive simulations in the future, we extended our model by showing that simple, two-dimensional properties of the single drug molecule can be used to rationalize nanosuspension design without simulation. In all, our work demonstrates how computational tools can provide molecular insight into drug-excipient interactions, and aid in rational formulation design.

Biological membranes are fascinating. Santiago Ramón y Cajal, who received the Nobel prize in 1906 together with Camillo Golgi for their work on the nervous system, wrote “[..]in the study of this membrane[..] I felt more profoundly than in any other subject of study the shuddering sensation of the unfathomable mystery of life”[1]. The visualization and conceptualization of these biological objects have profoundly shaped many aspects of modern biology, drawing inspiration from experiments, computer simulations, as well as from the imagination of scientists and artists. The aim of this review is to provide a fresh look on current ideas of biological membrane organization and dynamics by discussing selected examples across fields [1] The full quotation is “I must not conceal the fact that in the study of this membrane I for the first time felt my faith in Darwinism (hypothesis of natural selection) weakened, being amazed and confounded by the supreme constructive ingenuity revealed not only in the retina and in the dioptric apparatus of the vertebrates but even in the meanest insect eye. There, in fine, I felt more profoundly than in any other subject of study the shuddering sensation of the unfathomable mystery of life.” from the autobiography Recollections of My Life.

The effect of the communication channel size on the transport and subsequent detection of chemical messengers is investigated on millimetric and micrometric channels. The transport of the information carriers, being characterized by an advective and a diffusive contribution, was simulated by varying the flow velocity and the diffusion coefficient. Then, to evaluate the information quality, the Intersymbol Interference (ISI) between two consecutive signals at a specific release delay was estimated. This allowed us to verify that operating under micrometric channel conditions has a larger flow velocity range to obtain completely separated successive signals and smaller release delays can be used between signals. The theoretical results were confirmed by developing a prototype molecular communication platform operating under microfluidic conditions, which enables communication through fluorescent nanoparticles, namely Carbon Quantum Dots (CQDs).

Abrstract: Bacillus spp. it is a genus that is used to biocontrol post-harvest diseases in various vegetables and fruits during transportation and storage. It suppresses the development of pathogens such as gray mold (Botrytis cinerea) in strawberry cultivation. In this work, the molecular characterization of Bacillus spp. species was carried out. in three cities in Peru: Huaura, Chanchamayo and Cañete. The samples were collected from rhizospheric soil from crop areas, subsequently processed for microbiological isolation, molecular analysis using the 16S rRNA gene and bioinformatic analysis. In total, 14 strains were obtained where they were identified with a minimum of 92.05% and a maximum of 100% similarity: 8 strains of Bacillus subtilis, 4 strains of Bacillus licheniformis, 1 strain of Bacillus paralicheniformis and 1 strain of Bacillus cereus, all the strains were related by constructing a phylogenetic tree.

Starting from early 2020, the COVID-19 pandemic has caused a morbidity and mortality excess worldwide. Containment strategies rely firstly on rapid and sensitive laboratory diagnosis with molecular detection of the viral genome in respiratory samples being the gold standard. Reliability of diagnostic protocols could be affected by SARS-CoV-2 genetic variability. In fact, mutations occurring during SARS-CoV-2 genomic evolution can involve the regions targeted by the diagnostic probes. Following a review of the literature and an in silico analysis of the most recently described virus variants (including the UK B 1.1.7 and the South Africa 501Y.V2 variants), we conclude that the described genetic variability should have minimal or no effect on the sensitivity of existing diagnostic protocols for SARS-CoV-2 genome detection. However, given the continuous emergence of new variants, the situation should be monitored in the future, and protocols including multiple targets should be preferred.

This study investigates the impact of temperature-induced quantum proton tunneling probability on DNA amplification during polymerase chain reactions (PCR). Using a simulation model based on a Gaussian wavefunction and finite-difference time-domain method, quantum tunneling of protons across square potential barriers is examined. The results unveil consistent probability distributions for quantum tunneling across various PCR temperatures, with distinct oscillation patterns emerging post-barrier crossing. Acknowledging limitations in initial conditions due to temperature-dependent proton energy, the study highlights the need for refined models and experimental validation. These findings accentuate the potential interplay between quantum mechanics and biological systems, prompting further research to understand quantum tunnelling’s comprehensive effect on genetic variations and molecular processes.

COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, TMPRSS2, and AP2-associated protein kinase 1. In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of drug candidates to target receptors, providing insight into their potential efficacy. However, it is crucial to consider both the advantages and limitations of these studies and to complement them with experimental validation to ensure the efficacy and safety of identified drug candidates.

Malaria is rare in Europe, but it is a medical emergency and programs for its control should ensure access to early diagnosis and prompt treatment within 24-48 h of the symptom’s onset. The consistent number of imported malaria cases and the risk of reappearance of autochthonous cases stimulated laboratories in non-endemic countries to evaluate diagnostic methods/algorithms: microscopy remains the gold standard, but with limitations. RDTs have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. According to WHO global Technical Strategy for Malaria 2016-2030, the future direction for a rapid diagnosis is the development of Point-Of-Care Testing, which would be helpful for prompt/accurate treatment and for preventing the diseases spread. Despite the limitations of current diagnostic methods, they play important roles in dealing with the global malaria situation, including decreasing its incidence. Recently evidence suggested that Artificial Intelligence could be utilized for assisting pathologists in malaria diagnosis. Future studies need to be conducted to see whether this system can be used for routine malaria diagnostic procedures.

A single type I RC (Fe-S type, ferredoxin reducing) is found in several of the phyla of anoxygenic phototrophic bacteria. They include the heliobacteria (HB), the green sulfur bacteria (GSB) and the chloroacidobacteria (CAB), for which high-resolution homodimeric RC-PS structures have recently appeared [1-4]. The 2.2-Å Xray structure of the RC-PS of Heliomicrobium modesticaldum [1] revealed that the core PshA apoprotein (PshA1 and PshA2 homodimeric pair) exhibits a structurally conserved PSI arrangement comprised of five C-terminal transmembrane helices (TMHs) forming the RC domain and six N-terminal TMHs coordinating the light-harvesting (LH) pigments. The Hm. modesticaldum structure lacked quinones, indicating that electrons were transferred directly from the A0 (81-OH-chlorophyl (Chl) a) primary acceptor to the FX [4Fe4S] component, serving as the terminal RC acceptor. A pair of additional TMHs designated as Psh X were found, that function as a low-energy antennae. The 2.5Å resolution cryo-electron microscopy (cryo-EM) structure for the RC-PS of the GSB Chlorobaculum tepidum [2] included two Fenna-Matthews-Olson protein (FMO) antennae, which transfer excitations from the chlorosomes to the RC-PS (PscA1 and PscA2) core. Two cytochromes c (PscC) molecules were revealed, which act in series as electron donors to the photooxidized RC BChl a’ special pair, as well as PscB, housing the [4Fe-4S] cluster FA and FB, and the associated PscD protein [3]. Although their FMO components were missing from the 2.6-Å cyro-EM structure of the Zn-BChl a’ special pair containing RC-PS of Chloroacidobacterium thermophilum [4], a unique architecture was revealed that consisted of seven additional subunits including PscZ in place of PscD, the PscX and PscY cytochrome c serial electron donors and four low mol. wt. subunits of unknown function. Overall, these diverse structures have revealed that: (i) the HB RC-PS is the simplest light-energy transducing complex yet isolated, and represents the closest known homolog to a common homodimeric RC-PS ancestor; (ii) the symmetrically localized Ca2+binding sites found in each of the Type I homodimeric RC-PSs likely gave rise to the analogously positioned Mn4CaO5 cluster of the PSII RC and the TyrZ RC donor site; (iii) a close relationship between the GSB RC-PS and Chl protein (CP)43 and CP47 of PSII was demonstrated by the strongly conserved locations of their LH-(B)Chls; (iv) LH-BChls of the GSB-RC-PS are also localized in the conserved RC-associated positions of the PSII ChlZ-D1 and ChlZ-D2 sites; (v) glycosylated carotenoids of the GSB RC-PS are located in the homologous carotenoid-containing positions of PSII, reflecting an O2-tolerance mechanism capable of sustaining early stages in the evolution of oxygenic photosynthesis. In addition to the close relationships found between the homodimeric RC-PS and PSII, duplication of the gene encoding the ancestral Type I RC apoprotein, followed by genetic divergence my well account for the appearance of the heterodimeric Type I and Type II RC found in extant oxygenic phototrophs. Accordingly, the long-held view that PSII arose from the anoxygenic Type II RC is now supplanted by the new evidence provided by Type I RC-PS homodimer structures, indicating that the evolutionary origins of anoxygenic Type II RCs along with their distinct antenna rings are likely to have occured later than the events which gave rise to their oxygenic counterparts.

Organic-organic interactions play important roles in the secondary organic aerosol formation, but the interactions are complex and poorly understood. Here we use environmental molecular beam experiments combined with molecular dynamics simulations to investigate the interactions between methanol and nopinone, as atmospheric organic proxies. In the experiments, methanol monomers and clusters are sent to collide with three types of surfaces, i.e., graphite, thin nopinone coating on graphite and multilayer surfaces, at temperatures between 140 K and 230 K. Methanol monomers are efficiently scattered from the graphite surface, whereas the scattering is substantially suppressed from nopinone surfaces. The desorption from the three surfaces is similar, suggesting that all the surfaces have weak or similar influences on the methanol desorption. The molecular dynamics results show that upon collisions the methanol clusters shatter, and the shattered fragments quickly diffuse and recombine to clusters. The desorption involves a series of processes, including detaching from clusters and desorbing as monomers. The experimental results also show that all trapped methanol molecules completely desorb within a short experimental time scale at temperatures of 180 K and above. At lower temperatures, the desorption rate decreases, and a long experimental time scale is used to resolve the desorption, where three desorption components are identified. The fast component is beyond the experimental detection limit. The intermediate component exhibits multi-step desorption character and has an activation energy of E_a = 0.18 ± 0.03 eV, in good agreement with simulation results. The slow desorption component is related to diffusion processes due to the weak temperature dependence.

Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.

Birds are highly social and need pairing in order to increase their welfare. Most bird species are monomorphic, therefore, molecular sexing helps to provide appropriate welfare for birds. Moreover, early sex determination can be of great value for bird owners. The aim of this study was to demonstrate that sex identification in birds by molecular methods, using samples collected by minimally invasive methods is fast, efficient and accurate. A total of 100 samples (29 paired samples of feathers - oral swab and 14 tripled samples of feathers - oral swab - blood) from 43 birds were taken into study, as follows: wild birds (Falconiformes, Accipitriformes, landfowl – Galliformes, waterfowl– Anseriformes), companion birds (Passeriformes, Psittaciformes – large, medium and small size parrots). Amplification of CHD1-Z and CHD1-W genes was performed by conventional PCR. The results obtained from feathers were compared to those obtained from oral swabs and with those obtained from blood samples, where was the case. The obtained results show that all types of samples can be used for molecular sexing of all studied species of birds. According to our knowledge, the present study reports for the first time the molecular sex identification in: Red Siskin (Carduelis cucullata) and Goldfinch (Carduelis carduelis major). For higher accuracy, our recommendation is to use minimally invasive samples (swab-feathers) and to test both types of samples, for each bird, instead of blood samples.

Some α-Pyrone derivatives isolated from Alternaria phragmospora fungus showed promising anti leukemic activities, while others were inactive. CRM1/XPO1 (chromosome region maintenance 1 protein, also called exportin1 or PO1 in humans) has been chosen as a target for antileukemic molecular docking study for those compounds to understand their modes of interaction and structure activity relationships. The results showed that two (2 and 4), out of six, natural α-Pyrone derivatives exhibited well-established interactions with the amino acids of the receptor, which was in agreement with the experimental anti-leukemic results of these compounds. Moreover, twenty hypothetical chemically modified α-Pyrone derivatives (7-27) have been designed. Compounds 7, 8, 22 and 24 showed more efficient docking properties than the previously considered natural compounds.

Collisions of low energy electrons with molecules are important for understanding many aspects of the environment and technologies. Understanding the processes that occur in these types of collisions can give insights into plasma etching processes, edge effects in fusion plasmas, radiation damage to biological tissues and more. A radical update of the previous expert system for computing observables relevant to these processes, Quantemol-N, is presented. The new Quantemol Electron Collision (QEC) expert system simplifyies the user experience, improving reliability and implements new features. The QEC GUI interfaces the Molpro quantum chemistry package for molecular target setups and to the sophisticated UKRmol+ codes to generate accurate and reliable cross-sections. These include elastic cross-sections, super elastic cross-sections between excited states, electron impact dissociation, scattering reaction rates, dissociative electron attachment, differential cross-sections, momentum transfer cross-sections, ionization cross sections and high energy electron scattering cross-sections. With this new interface we will be implementing dissociative recombination estimations, vibrational excitations for neutrals and ions, and effective core potentials in the near future.

Shut-in after fracturing is generally adopted for wells in shale oil reservoirs, and imbibition occurring in matrix nanopores has been proven as an effective way to improve recovery. In this research, the molecular dynamics (MD) simulation was used to investigate the effects of wettability and pressure on nanopores imbibition during shut-in for a typical shale reservoir Jimsar. The results indicate that the microscopic advancement mechanism of the imbibition front is the competitive adsorption between “interfacial water molecules” at the imbibition front and “adsorbed oil molecules” on the pore wall. The essence of spontaneous imbibition involves the adsorption and aggregation of water molecules onto the hydroxyl groups on the pore wall. The flow characteristics of shale oil suggest that the overall push of the injected water to the oil phase is the main reason for the displacement of adsorbed oil molecules. Thus, shale oil especially the heavy hydrocarbon component in the adsorbed layer tends to slip on the walls. However, the weak slip ability of heavy components on the wall surface is an important reason that restricts the displacement efficiency of shale oil during spontaneous imbibition. The effectiveness of spontaneous imbibition is strongly dependent on the hydrophilicity of the matrix pore's wall. The better hydrophilicity of the matrix pore's wall facilitates higher levels of adsorption and accumulation of water molecules on the pore wall and requires less time for “interfacial water molecules” to compete with adsorbed oil molecules. During the forced imbibition process, the pressure difference acts on both the bulk oil and the boundary adsorption oil, but mainly on the bulk oil, which leads to the occurrence of wetting hysteresis. Meanwhile, shale oil still existing in the pore always maintains a good stratified adsorption structure. Because of the wetting hysteresis phenomenon, as the pressure difference increases, the imbibition effect gradually increases, but the actual capillary pressure gradually decreases and there is a loss in the imbibition velocity relative to the theoretical value. Simultaneously, the decline in hydrophilicity further weakens the synergistic effect of pressure difference because of the more pronounced wetting hysteresis. Thus, selecting an appropriate well pressure enables cost savings and maximizes the utilization of the formation's natural power for EOR.

Lung cancer is one of the most important health risks worldwide for human. Non-small cell lung cancer (NSCLC) is the most common cause of premature death from malignant disease. This study provides in-depth insights from systems biology analyses to identify molecular to inform systemic drug targeting in NSCLC. Gene expression profiles from non small cell lung cancer were analyzed with genome-scale biomolecular networks (I,e., protein-protein interaction, transcriptional and post transcriptional regulatory networks). The aim of the study was to determine the pathways and expression profile of the genes to discover molecular signature at RNA and protein levels which could serve as potential drug targets for therapeutics innovation and the identification of novel targets. Eight proteins, six TFs and seven miRNAs came into prominence as potential drug targets. The differential expression profiles of these reporter biomolecules were cross-validated by independent RNA-Seq and miRNA-Seq. Risk discrimination performance of the reporter biomolecules NPR3, JUN, PPARG, TP53, CKMT1A, SP3 and TFAP2A were also evaluated. Total 213 drugs and 7 proteins were found for non small cell lung cancer through dgidb. Among these identified drugs seven drugs such as- Gemcitabine, Carboplatin, paclitaxel, Docetaxel, Crizotinib, Bevacizumab and Gemcitabine is used for NSCLC which is approved by National Cancer Institute. The molecular signatures and repurposed drugs presented here permit further attention for experimental studies which are offer significant potential as biomarkers and candidate therapeutics for precision medicine approaches to clinical management of NSCLC.

We report a detailed investigation of vibrational modes, structure, and dynamics of glutathione (GSH) solutions using ultrasonic relaxation spectroscopy, FT-IR vibrational spectroscopy and electronic absorption measurements. The experimental data were analyzed in view of density functional theory (DFT) and molecular docking calculations. Three distinct Debye-type relaxation processes are resolved in the acoustic spectra, which are assigned to conformational changes between GSH conformers, self-association of GSH, and protonation processes. The standard volume changes for each process were estimated both experimentally and theoretically revealing a close resemblance among them. The higher the effect of the relaxation process in the structure, the greater the induced volume changes. From the temperature dependence of specific acoustic parameters, the thermodynamic characteristics of each process were determined. The experimental FT-IR spectra were compared with the corresponding theoretically predicted vibrational spectra revealing that the GSH dimers and extended conformers dominate the structure of GSH solutions in the high concentration region. The absorption spectra in the ultraviolet region confirmed the gradual aggregation mechanism that takes place in the aqueous GSH solutions. The results of the present study were discussed and analyzed in the framework of the current phenomenological status of the field.

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT2A and D2 subtypes of class A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

The [3+2] cycloaddition (32CA) reactions of strongly nucleophilic norbornadiene (NBD) with simplest diazoalkane (DAA) and three DAAs of increased electrophilicity have been studied within the Molecular Electron Density Theory (MEDT) at the MPWB1K/6-311G(d,p) computational level. These pmr-type 32CA reactions follow an asynchronous one-step mechanism with activation enthalpies ranging from 17.7 to 27.9 kcal·mol-1 in acetonitrile. The high exergonic character of these reactions makes them irreversible. The presence of electron-withdrawing (EW) substituents in the DAA increases the activation enthalpies, in complete agreement with the experimental slowing-down of the reactions, but contrary to the Conceptual DFT prediction. Despite the nucleophilic and electrophilic character of the reagents, the global electron density transfer at the TSs indicates rather non-polar 32CA reactions. The present MEDT study allows establishing that the depopulation of the NNC core in this series of DAAs with the increase of the EW character of the substituents present at the carbon center is responsible for the experimentally found deceleration.

A universally applicable method for the prediction of the isobaric heat capacities of the liquid and solid phase of molecules at 298.15 K is presented, derived from their “true” volume. The molecules’ “true” volume in A³ is calculated on the basis of their geometry-optimized structure and the Van-der-Waals radii of their constituting atoms by means of a fast numerical algorithm. Good linear correlations of the “true” volume of a large number of compounds encompassing all classes and sizes with their experimental liquid and solid heat capacities over a large range have been found, although noticeably distorted by intermolecular hydrogen-bond effects. To take account of these effects, the total amount of 1303 compounds with known experimental liquid heat capacities has been subdivided into three subsets consisting of 1102 hydroxy-group-free compounds, 164 monoalcohols/monoacids, and 36 polyalcohols/polyacids. The standard deviations for Cp(liq,298) were 20.7 J/mol/K for the OH-free compunds, 22.91 J/mol/K for the monoalcohols/monoacids and 16.03 J/mol/K for the polyols/polyacids. Analogously, 797 compounds with known solid heat capacities have been separated into a subset of 555 OH-free compounds, 123 monoalcohols/monoacids and 119 polyols/polyacids. The standard deviations for Cp(sol,298) were calculated to 23.14 J/mol/K for the first, 21.62 J/mol/K for the second, and 19.75 J/mol/K for the last subset. A discussion of structural and intermolecular effects influencing the heat capacities as well as of some special classes, in particular hydrocarbons, ionic liquids, siloxanes and metallocenes, has been given. In addition, the present method has successfully been extended to enable the prediction of the temperature dependence of the solid and liquid heat capacities in the range between 250 and 350 K.

Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Since the latter half of the XX century, synthetic auxins have been used as herbicides, presenting notable advantages, such as low toxicity in humans. As of today, extensive descriptions of syntetic and natural auxins have been made; yet studies centered on the molecular recognition process of auxins are scarce. Herein, we present a comprehensive in silico characterization of auxin receptor TIR1, using structure based methods to aid de novo design of putative ligands. In addition, we conducted binding site characterization using cosolvent molecular dynamics and enhanced sampling simulations with reference ligands. We also present a database of putative auxins and decoy compounds which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1.

There are currently worldwide efforts to reduce sugar intake due to the various adverse health effects linked with the overconsumption of sugars. Artificial sweeteners have been used as an alternative to nutritive sugars in numerous applications; however, their long-term effects on human health remain controversial. This led to a shift in consumer preference towards non-caloric sweeteners from natural sources. Thaumatins are a class of intensely sweet proteins found in arils of the fruits of the West-African plant Thaumatococcus danielli. Thaumatins’ current production method through aqueous extraction from this plant and uncertainty of the harvest from tropical rainforests limits its supply while the demand is increasing. Despite successful recombinant expression of the protein in several organisms, no large-scale bioproduction facilities exist. We present preliminary process design, process simulation, and economic analysis for a large-scale (50 metric tons/year) production of thaumatin II variant by several different molecular farming platforms.

Tuberculosis (TB) is a contagious disease, caused by Mycobacterium tuberculosis (MTB) that has infected and killed a lot of people in the past. At present treatments against TB are available at a very low cost. Since these chemical drugs have many adverse effects on health, more attention is now given on the plant-derived phytochemicals as potential agents to fight against TB. In this study, 5 phytochemicals, 4-hydroxybenzaldehyde, benzoic acid, bergapten, psoralen, and p-hydroxybenzoic acid, are selected to test their potentiality, safety, and efficacy against two potential targets, the MTB RNA polymerase and enoyl-acyl carrier protein (ACP) reductase, the InhA protein, using various tools of in silico biology. The molecular docking experiment, drug-likeness property test, ADME/T-test, P450 SOM prediction, pharmacophore mapping, and modeling, solubility testing, DFT calculations, and PASS prediction study had confirmed that all the molecules had the good potentiality to inhibit the two targets. However, two agents, 4-hydroxybenzaldehyde and bergapten were considered as the best agents among the five selected agents and they also showed far better results than the two currently used drugs, that function in these pathways, rifampicin (MTB RNA polymerase) and isoniazid (InhA protein). These two agents can be used effectively to treat tuberculosis.

Chicken collagen is a promising raw material source to produce gelatins and hydrolysates. Gelatins and hydrolysates can be prepared biotechnologically using proteolytic enzymes produced by submerged fermentation of genetically modified microorganisms. By choosing the appropriate process conditions, such changes can be achieved at the molecular level of collagen, making it possible to prepare products with targeted properties for advanced cosmetic, pharmaceutical, medical or food applications. The research aims to investigate: i) antioxidant activity (DPPH and ABTS) in model samples of chicken collagen products (gelatin and hydrolysates); ii) distribution of molecular weights by the GPC-RID analysis method; iii) functional groups and configuration of polypeptide chains related to molecular level properties using FTIR; iv) the microbiological properties on SDA, PCA, TSA and VRBL microbial populations using MALDI method. Antioxidant activity towards ABTS radicals of more than 80% was found for all samples. The molecular weights of all gelatin samples showed typical α- and β-chains. FTIR analysis confirmed that the samples showed all typical vibrational regions for collagen cleavage products, Amide A and B, Amide I, II, and III at characteristic values. Microbiological analysis of the prepared samples showed no undesirable bacteria that would limit advanced applications of the prepared products. Gelatins and hydrolysates from chicken stomachs represent a promising alternative to products made from standard collagen tissues of terrestrial animals.

The development of microbial products for cancer treatment has been in the spotlight in recent years. In order to accelerate the lengthy and expensive drug development process, in silico screening tools are systematically employed, especially during the initial discovery phase. Moreover, considering the steadily increasing number of molecules approved by authorities for commercial use, there is a demand for faster methods to repurpose such drugs. Here we present a review on virtual screening web tools, publicly available databases of molecular targets and libraries of ligands, with the aim to facilitate the discovery of potential anticancer drugs based on microbial products. We provide an entry-level step-by-step description of the workflow for virtual screening of microbial metabolites with known protein targets, as well as two practical examples using freely available web tools. The first case presents a virtual screening study of drugs developed from microbial products using Caver Web, a web tool that performs docking along a tunnel. The second case comprises a comparative analysis between a healthy isocitrate dehydrogenase 1, a mutant that results in cancer, using the recently developed web tool PredictSNP^Onco. In summary, this review provides the basic and essential background information necessary for virtual screening experiments, which may accelerate the discovery of novel anticancer drugs.

The study aims to evaluate the Quorum Sensing (QS) system inhibition against some Gram-positive and Gram-negative bacteria detected by molecular modeling of R. cathartica L. plant extract. R. cathartica L. methanol extract was evaluated in vitro. The research was carried out for the possible role and mechanism of R. cathartica L. The antibacterial activity of R. cathartica L. seed extract on some Gram-positive and Gram-negative strains was evaluated using culture-based and computational analysis. Gentamicin (CN; 30 µg/ml, Bioanalyse) was used as an antibacterial control of the extract on the production potential of QS-dependent virulence factors on Pseudomonas aeruginosa PAO1 was investigated. Phytochemical analysis resulted in the identification of 23 phenolic phytochemicals. R. cathartica L. extract was observed to have antimicrobial activity against Gram-positive and Gram-negative bacteria at different rates (11.3 mm-16 mm). The inhibitory effect of R. cathartica L. extract on P. aeruginosa PAO1 (elastase 61%, pyocyanin 18%, and biofilm 61%) was recorded moderately. Phytochemical analysis revealed that the main component of the extract is kaempferol. Therefore, the binding potential of kaempferol on QS system receptors was investigated via molecular docking. Computational analysis showed that kaempferol can inhibit the QS system by preventing competitive ligands from connecting to LasR. This study explored the activity and mechanism of action for a new green alternative against resistance. might provide a mechanism for R. cathartica L. seed extract components and thus provide a new avenue for using R. cathartica L. seed extract as a green antibacterial agent.

Cryonotothenioidea is the main group of fishes that thrive in the extremely cold Antarctic environment, thanks to the acquisition of peculiar morphological, physiological and molecular adaptations. We have previously disclosed that IgM, the main immunoglobulin isotype in teleosts, display typical cold-adapted features. Recently, we have analyzed the gene encoding the heavy chain constant region (CH) of the IgT isotype from the Antarctic teleost Trematomus bernacchii (family Nototheniidae), characterized by the near-complete deletion of the CH2 domain. Here, we aimed to track the loss of the CH2 domain along notothenioid phylogeny and to identify its ancestral origins. To this end, we obtained the IgT gene sequences from several species belonging to the Antarctic families Nototheniidae, Bathydraconidae and Artedidraconidae. All species display a CH2 remnant of variable size, encoded by a short Cτ2 exon, which retains functional splicing sites and therefore is included in the mature transcript. We also considered representative species from the three non-Antarctic families: Eleginopsioidea (Eleginops maclovinus), Pseudaphritioidea (Pseudaphritis urvillii) and Bovichtidae (Bovichtus diacanthus and Cottoperca gobio). Even though only E. maclovinus, the sister taxa of Cryonotothenioidea, shared the partial loss of Cτ2, the other non-Antarctic notothenioid species displayed early molecular signatures of this event. These results shed light on the evolutionary path that underlies the origins of this remarkable gene structural modification.

Lysophosphatidic acid (LPA) is a promising biomarker candidate to screen for ovarian cancer (OC) and potentially stratify and treat patients according to disease stage. LPA is known to target actin-binding protein gelsolin that is a key regulator of actin filament assembly. Previous studies have shown that the phosphate headgroup of LPA alone is inadequate to bind to the short chain of amino acids in gelsolin known as the PIP2-binding domain. Thus, the molecular-level detail of the mechanism of LPA binding is poorly understood. Here, we model LPA binding to the PIP2-binding domain of gelsolin in the gelsolin-actin complex through extensive ten microsecond atomistic molecular dynamics (MD) simulations. We predict that LPA binding causes a local conformational rearrangement due to LPA interactions with both gelsolin and actin residues. These conformational changes are a result of the amphipathic nature of LPA, where the anionic phosphate, polar glycerol and ester groups, and lipophilic aliphatic tail mediate LPA binding via charged electrostatic, hydrogen bonding, and van der Waals interactions. The negatively-charged LPA headgroup binds to the PIP2-binding domain of gelsolin-actin while its hydrophobic tail is inserted into actin, creating a strong LPA-insertion pocket that weakens the gelsolin–actin interface. The computed structure, dynamics, and energetics of the ternary gelsolin–LPA–actin complex confirms that a quantitative OC assay is possible based on LPA-triggered actin release from the gelsolin-actin complex.

As the interface between human and machine becomes blurred, hydrogel incorporated electronics and devices have emerged to be a new class of flexible/stretchable electronic and ionic devices due to their extraordinary properties, such as soft, mechanically robust and biocompatible. However, heat dissipation in these devices could be a critical issue and remains unexplored. Here, we report the experimental measurements and equilibrium molecular dynamics simulations of thermal conduction in polyacrylamide (PAAm) hydrogels. The thermal conductivity of PAAm hydrogels can be modulated by both the crosslinking density and water content in hydrogels. The crosslinking density dependent thermal conductivity in hydrogels varies from 0.33 to 0.51 Wm^-1K^-1, giving a 54% enhancement. We attribute the crosslinking effect to the competition between the increased conduction pathways and the enhanced phonon scattering effect. Moreover，water content can act as filler in polymers which lead to nearly 40% enhancement in thermal conductivity in PAAm hydrogels with water content vary from 23 to 88 wt%. Furthermore，we find the thermal conductivity of PAAm hydrogel is insensitive to temperature in the range of 25 ^oC – 40 ^oC. Our study offers fundamental understanding of thermal transport in soft materials and provides design guidance for hydrogel-based devices.

Nucleation is a fundamental and general process at the initial stage of first order phase transition. Although various models based on the classical nucleation theory (CNT) have been proposed to explain the energetics and kinetics of nucleation, detailed understanding on nanoscales are still required. Here we focus on homogeneous bubble nucleation, in which evaluation of the size dependence of bubble free energy is the key issue. We propose application of a formula in stochastic thermodynamics, the Jarzynski’s equality, for data analysis of molecular dynamics (MD) simulation to evaluate the free energy of bubble nucleation. As a test case, we performed a series of MD simulations with Lennard-Jones (LJ) fluid system. By applying an external spherical force field to equilibrated LJ liquid, we evaluated the free energy change during bubble growth as the Jarzynski’s ensemble average of required works. A fairly smooth free energy curve was obtained as a function of bubble radius in metastable liquid of mildly negative pressure conditions.

The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, water samples from two wastewater treatment plants (WWTPs) located at the south east of Spain (Region of Murcia) namely Murcia, and Cartagena, were analyzed by RT-qPCR, Phylogenetic Analysis, and Machine Learning Approach. The aim was to determine whether SARS-CoV-2 detection in the WWTPs of these two cities could serve as a proxy for the virus's spread in the population. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population and variant occurrences were in line with clinical reported data. Additionally, the phylogenetic analysis showed that samples obtained in close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical Clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing the Accumulated Natural Vector (ANV) of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.

Habenaria, a member of Orchidaceae family is the cosmopolitan distributions, which has significant medicinal and ornamental values. Regardless of morphology and molecular data that have been studied in recent times, the phylogenetic relationship is still under debate. Here, we sequenced, assembled, and annotated the whole chloroplast (cp) genome of two species (Habenaria aitchisonii Rchb.f. and Habenaria tibetica Schltr.ex Limpricht) of Habenaria grown on the Qinghai-Tibetan Plateau (QTP), and combined with seven already published cp genomes which may assist to uncover their genomic profiling. The two genomes ranged from 155259-155269 bp in length and both encoded 132 genes, including 86 protein, 38 tRNA and 8 rRNA. In the cp genomes, the tandem repeats (797), SSRs (2195) and diverse loci (3214) were identified. Comparative analyses of codon usage, amino frequency, microsatellite, oligo repeats and transition and transversion substitutions showed similarities among the species. Moreover, we identified 16 highly polymorphic regions with nucleotide diversity above 0.02, which may be suitable for robust authentic barcoding and inferring in the phylogeny of Habenaria species. Among the polymorphic regions, positive selection was significantly exerted on the several genes such as cemA, petA, and ycf1. This may suggest that the important adaptation stratagem for two Habenaria species on the QTP. The phylogenetic relationship displayed that H.aitchisonii and H. tibetica have closer relationship than others and the rest seven species clustered in the other three groups. Our findings also supported the idea that Habenaria could be divided into different sections. This study enriched the genomics resources of Habenaria, which may be helpful for the conservation efforts of these endangered species.

Precise HDV-RNA detection and quantification are pivotal for accurate diagnosis and monitoring of response to newly approved treatment. We evaluate the performance of three assays: Hepatitis Delta RT-PCR system, EurobioPlex HDV assay, and the RoboGene HDV RNA Quantification kit 2.0, testing 151 HBsAg-positive samples, 90 HDV-RNA negative and 61 HDV-RNA positive. We also evaluated serial dilutions of the WHO international standard for HDV, PEI 7657/12. Finally, all HDV-RNA positive samples were genotyped using a next-generation sequencing strategy. Qualitative results indicated a 100% concordance between tests. Quantitative results correlated well between tests, r2=0.703 (Vircell-vs-Eurobio), r2=0.833 (Vircell-vs-RoboGene), r2=0.835 (Robogene-vs-Eurobio). Bias index was 2.083 (Vircell-vs-Eurobio), -1.283 (Vircell-vs-RoboGene), and -3.36 (Robogene-vs-Eurobio). Using the WHO IS, Vircell overestimated the viral load by 0.98 log IU/mL, Eurobio by 1.46 log IU/mL, and RoboGene underestimated it by 0.98 log IU/mL. Fifty-nine samples were successfully genotyped (Genotype 1, n=52; Genotype 5, n=7; Genotype 6, n=1), with similar results in terms of correlation and bias. The three assays demonstrate promising performance. Their accuracy, reflected in concordance rates and quantitative analysis, makes them suitable for clinical practice. However, in the absence of assay harmonization, quantitative HDV RNA monitoring should be performed in the same laboratory and assay to avoid variability.

This study aims to investigate the spectroscopic and structural properties of the compound Lumefantrine which is important in pharmacology because of its anti-malarial effect. The structural and spectroscopic properties of this molecule such as bond lengths, bond angles, FT-IR and NMR spectra were handled computationally using a computational chemistry suite: Spar-tan’14. Both HF and DFT methods were used with different basis sets for the calculations. The re-sults calculated by the software were compared to experimental results from the literature. Both Computational and experimental results were exhibited as tables. Also some calculated results such as HOMO-LUMO boundary orbitals and electrostatic potential map, were given as graphics and pictures.

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is an established tool for the diagnosis of RNA pathogens. Its potential for automation has caused it to be used as a presence/absence diagnostic tool even when RNA quantification is not required. This technology has been pushed to the forefront of public awareness by the COVID-19 pandemic, as its global application has enabled rapid and analytically sensitive mass testing, with the first test targeting three viral genes published within days of the publication of the SARS-CoV-2 genomic sequence. One of those, targeting the RNA-dependent RNA polymerase gene, has been heavily criticised for supposed scientific flaws at the molecular and methodological level and this criticism has been extrapolated to doubts about the validity of RT-qPCR for COVID-19 testing in general. We have analysed this assay in detail and our findings reveal some limitations, but also highlight the robustness of the RT-qPCR methodology for SARS-CoV-2 detection. Whilst our data show that some errors can be tolerated, it is always prudent to confirm that primer and probe sequences complement their intended target, since when errors do occur, they may result in a reduction in the analytical sensitivity. However, in this case it is unlikely that a mismatch will result in poor specificity or significant number of false positive SARS-CoV-2 diagnoses, especially as this is routinely checked by diagnostic laboratories as part of their quality assurance.

Polymers' controlled pyrolysis is an economical and environmentally friendly solution to prepare activated carbon. However, due to the experimental difficulty in measuring the dependence between tissues and pyrolysis parameters at high temperatures, the unknown pyrolysis mechanism hinders access to the target products with desirable morphologies and performances. In this study, we investigate the pyrolysis process of polystyrene under different heating rates and temperatures employing reactive molecular dynamics (ReaxFF-MD) simulations. A clear profile of the generation of pyrolysis products determined by the temperature and heating rate is constructed. It is found that the heating rate affects the type and amount of pyrolysis intermediates and their timing, and low-rate heating helps yield more diverse pyrolysis intermediates. While the temperature affects the pyrolytic tissues of the final equilibrium products, either too low or too high a target temperature is detrimental to generating large areas of graphitized tissue. The established theoretical evolution process matches experiments well, thus contributing to preparing target activated carbons by referring to the regulatory mechanism of pyrolytic tissues.

Background: This study aimed to investigate the molecular profiles of stage III CRC patients from the international IDEA study. It also sought to correlate these profiles with Toll-like and vitamin D receptor polymorphisms, clinicopathological and epidemiological characteristics, and patient outcomes. Methods: Whole Exome Sequencing and PCR-RFLP on surgical specimens and blood samples, respectively, were performed to identify molecular profiling and the presence of Toll-like and vitamin D polymorphisms. Bioinformatic analysis revealed mutational status. Results: Among the enrolled patients, 63.7% were male, 66.7% had left-sided tumors, and 55.7% received CAPOX as adjuvant chemotherapy. Whole exome sequencing identified 59 mutated genes in 11 different signaling pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) CRC panel. On average, patients had 8 mutated genes (range, 2-21 genes). Mutations in ARAF and MAPK10 emerged as independent prognostic factors for reduced DFS (p=0.027 and p<0.001, respectively), while RAC3 and RHOA genes emerged as independent prognostic factors for reduced OS (p=0.029 and p=0.006, respectively). Right-sided tumors were also identified as independent prognostic factors for reduced DFS (p=0.019) and OS (p=0.043). Additionally, patients with tumors in the transverse colon had mutations in genes related to apoptosis, PIK3-Akt, Wnt, and MAPK signaling pathways. Conclusions: Molecular characterization of tumor cells can enhance our understanding of the disease course. Mutations may serve as promising prognostic biomarkers, offering improved treatment options. Confirming these findings with require larger patient cohorts and international collaborations to establish correlations between molecular profiling, clinicopathological and epidemiological characteristics and clinical outcomes.

This study presents a detailed comparative analysis of Molecular Docking data, focusing on the binding interactions of conventional ligands and natural compounds, Apigenin and Luteolin, with TP-53, pRb, and APOBEC. Utilizing advanced bioinformatics techniques, coupled with Ar-tificial Intelligence software and High-Performance Computing (HPC), we measured and con-trasted the binding energies of these interactions. Additionally, we investigated protein-protein interactions between HPV-16 oncoprotein E6 and tumor suppressors TP-53 and pRb. Our findings demonstrate that the natural compounds Apigenin and Luteolin exhibit significantly higher binding affinities to TP-53, pRb, and APOBEC compared to conventional pharmacological ligands. The binding energies for Apigenin and Luteolin were approximately -6.9 kcal/mol and -6.6 kcal/mol, respectively, indicating their strong potential as therapeutic agents in inhibiting the oncogenic functions of HPV-16. In contrast, conventional ligands showed lower binding affinities, with energies around -4.5 to -5.5 kcal/mol. The study further revealed that the protein-protein interactions between E6 and TP-53, and E6 and pRb, exhibited considerably higher binding en-ergies, approximately -976.7 kcal/mol, due to the multiple interaction sites and the complex nature of protein interfaces. A conversion formula was developed to translate these high-energy inter-actions to a comparable scale for non-protein-protein interactions, highlighting the superior binding potential of natural compounds, which, through the same conversion formula, was shown to be higher than that of interaction between E6 with TP-53 and E6 with pRb. These results underscore the therapeutic promise of Apigenin and Luteolin in preventing HPV-16-related on-cogenesis. By demonstrating their higher binding affinities to crucial tumor suppressors, this study supports the development of natural compound-based therapies. The findings also em-phasize the necessity for further experimental validation to explore these compounds' efficacy in clinical settings. This comprehensive analysis provides a robust framework for understanding the comparative binding interactions and lays the groundwork for innovative therapeutic strategies against HPV-16.

This study investigates the use of artificial intelligence (AI) and ethnobotanical knowledge to identify natural compounds with potent antiviral activity against HPV-16. Through molecular docking simulations, we evaluated the binding affinities of various essential oil components, in-cluding Apigenin, against the key antigenic determinants of HPV-16 (E6, E7 oncoproteins, and L1 major capsid protein). Apigenin exhibited strong binding affinities, particularly to E6 Oncopro-tein. To further enhance these findings, we employed an AI-driven reverse engineering approach to predict a natural compound with superior efficacy. The AI identified Luteolin, a flavonoid with additional hydroxyl groups, as a promising candidate. Comparative docking studies demon-strated that Luteolin possesses significantly stronger binding affinities to all three HPV-16 targets, surpassing the efficacy of Apigenin. This work highlights the potential of AI in accelerating the discovery and optimization of natural antiviral agents, providing a powerful tool for pharmaco-logical and ethnopharmacological screenings. Our findings suggest that AI-guided identification of natural compounds can lead to the development of more effective antiviral therapies, warranting further experimental validation and potential synthesis in laboratory settings.

Curcumin, a major constituent of turmeric, has beneficial effects against several diseases. In cystic fibrosis (CF), this compound potentiates the activity of a number of cystic fibrosis transmembrane conductance regulator (CFTR) mutants. Despite holding promise in the treatment of CF, the curcumin binding site in CFTR and the molecular mechanism of activation of this channel are still unknown. The results of the study, based on docking and molecular dynamics (MD) simulations, allow to propose that curcumin binds the closed ATP-free CFTR near the NBD1/ ICl1/ICl4 interface. The bound ligand, once approached by NBD2 during transient channel opening, lays at a multiple interdomain cross point. Thereafter, curcumin can bridge NBD1 and NBD2, and also ICL1/ICL4 and ICL2/ICL3 finally tightening the same interdomain interactions that normally uphold the active conformation in the wild type ATP-bound CFTR. The proposed binding site is compatible with biochemical observations made in previous CFTR-curcumin interaction studies. These findings provide the framework for the design of novel drugs that activate CFTR mutants characterized by defects in ATP binding and/or NBD dimerization, or even lacking NBD2.

Twelve wild North American Porcupines (Erethizon dorsatum) were diagnosed with dermatopathies while being cared for at two wildlife rehabilitation clinics. Biopsy and necropsy were performed on 7 and 5 animals respectively. Atypical dermatophytosis was diagnosed in all cases. Lesions consisted of diffuse severe epidermal hyperkeratosis and mild hyperplasia, with mild lymphoplasmacytic dermatitis, and no folliculitis. Dermatophytes were noted histologically as hyphae and spores in hair shafts, and follicular and epidermal keratin. Trichophyton sp. was grown in 5/6 animals where culture was performed, with molecular diagnosis of Arthroderma benhamiae / Trichophyton mentagrophytes in these 5 cases. Metagenomic analysis of formalin-fixed paraffin-embedded tissue samples from 3 cases identified fungi from 17 orders in phyla Basidiomycota and Ascomycota. Alteration of therapy from ketaconazole, which was unsuccessful in 4 of 5 early cases, to terbinafine or nitraconazole lead to resolution of disease and recovery to release in four subsequent animals. In all, 6 animals were euthanized or died due to dermatopathy, no cases resolved spontaneously, and 6 cases resolved with therapy. The work we present demonstrates an atypical lesion and anatomical distribution due to dermatophytosis in a series of free-ranging wild porcupines and successful development of novel techniques for extraction and sequencing nucleic acids from fungus in archival formalin-fixed paraffin-embedded animal tissue.

Single nucleotide polymorphisms (SNP) are associated with diseases and drug response variabilities in humans. Elucidating the damaging and disease-associated SNPs using wet-laboratory approaches can be challenging and resource-demanding due to the large number of SNPs in the human genome. Due to the growth in the field of computational biology and bioinformatics, algorithms have been developed to help screen and filter out the most deleterious SNPs that are worth considering for wet-laboratory studies. Here we review the existing in-silico based methods used to predict and characterize the effects of SNPs on protein structure and function. This cutting-edge approach will facilitate the search for novel therapeutics, help understand the etiology of diseases and fast-track the personalized medicine agenda.

Most malignant ovarian germ cell tumors (MOGTCs) have a very good prognosis and can be cured by chemotherapy, with yolk sac tumors (OYSTs) having the worse prognosis among MOGCTs. These tumors are rare and can benefit in the next future from specific therapeutic strategies after failure of platinum-based first-line and salvage regimens. In collaboration with EORTC SPECTA, we have developed a project to explore the molecular characteristics of OYST. The pilot part of the project was performed using retrospective samples and ten OYST patients including relapsed and disease free patients. The molecular analysis was performed using FoundationOne CDx. For each patient, the following variables are described in the molecular report provided by FMI (Fondation Medicine Incorporation): alteration type (SNV, deletion), actionable gene alteration, therapies approved in EU (patient's tumor type and other tumor types), tumor mutational burden (TMB) and microsatellite instability (MSI) status. A total of 10 patients with OYST diagnosed between 2007 and 2017 were analyzed. Four patients (40%) had a molecular alteration, according to the FMI test. A subset of three patients (33.3% of all patient) harbored targetable (KRAS, KIT, ARID1A) oncogenic mutations. Two patients at relapse harbored a targetable mutation. In this retrospective study, we were able to identify clinically relevant molecular alterations for all relapsed patients with molecular analysis. Dedicated studies are needed to demonstrate if they could benefit from specific therapeutic strategies after failure of platinum-based first-line and salvage regimens and if the presence of a molecular alteration could be linked to patients’ outcome.

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

Conclusions: Molecular classification could provide reliable supplementary information for evaluating prognostic and contribute to treatment option decision-making in EEC patients. Fertility-sparing treatment is not recommended for EEC patients with CNH and MSI-H. Furthermore, fertility-sparing treatment can be attempted in EEC patients with CHL, but regular follow-up should be carried out to early detection of EC relapse and prevention of disease progression.

The construction of molecular robotic-like objects that imitate living things is an important challenge for current chemists. Such molecular devices are expected to perform their duties robustly to carry out mechanical motion, process information, and make independent decisions. Dissipative self-organization plays an essential role in meeting these purposes. To produce a micro-robot that can perform the above tasks autonomously as a single entity, a function generator is required. Although many elegant review articles featuring chemical devices that mimic biological mechanical functions have been published recently, the dissipative structure, which is the minimum requirement, has not been sufficiently discussed. This article aims to show clearly that dissipative self-organization is a phenomenon involving autonomy, robustness, mechanical functions, and energy transformation. Moreover, the author details the recent experimental results of an autonomous light-driven molecular device that achieves all of these features. In addition, a chemical model of cell-amplification is also discussed to focus on the generation of hierarchical movement by dissipative self-organization. By reviewing this research, it may be perceived that mainstream approaches to synthetic chemistry have not always been appropriate. In summary, the author proposes that the integration of catalytic functions is a key issue for the creation of autonomous microarchitecture.

The emergence of diverse infections worldwide, which is a serious global threat to human existence, necessitate the urgent development of novel therapeutic candidates that can combat these diseases with efficacy. Isatin, a secondary metabolite from tryptophan is considered a privileged scaffold and favorable pharmacophore with a unique structural moiety and varied chemical and biological properties resulting in its widespread applications by medicinal chemists. Molecular hybridization is one of the most common and important techniques use in the synthesis of their bioactive hybrids in drug discovery. This review containing published articles from 2005 to 2022 focuses on isatin hybrids which have been synthesized and reported in the literature alongside a discussion on their biological properties. The purpose of this review is to set up the direction for the design and development of isatin-hybrids with tailored biological properties as effective therapeutic candidates inspired by nature.

Molecular motors play a vital role in the transport of material within the cell. A family of motors of growing interest are burnt bridge ratchets (BBRs). BBRs rectify spatial fluctuations into directed motion by creating and destroying motor-substrate bonds. It has been shown that the motility of a BBR can be optimized as a function of the system parameters. However, the amount of energy input required to generate such motion and the resulting efficiency has been less well characterized. Here, using a deterministic model, we calculate the efficiency of a particular type of BBR, namely a polyvalent hub interacting with a surface of substrate. We find that there is an optimal burn rate and substrate concentration that leads to optimal efficiency. Additionally, the substrate turnover rate has important implications on motor efficiency. We also consider the effects of force-dependent unbinding on the efficiency and find that under certain conditions the motor works more efficiently when bond breaking is included. Our results provide guidance for how to optimize the efficiency of BBRs.

Habituation is the most ancient and fundamental form of learning. As a firewall that protects our brain from sensory overload, it is indispensable for higher cognitive processes. Studies in humans and animal models provide a growing body of evidence that habituation is affected in autism and related monogenic neurodevelopmental disorders (NDDs). An integrated application of habituation assessment in NDDs and their animal models has currently unexploited potential for fundamental neuroscience and medical care.With the aim to gain mechanistic insights, we systematically retrieved genes that have been demonstrated in the literature to underlie habituation. We identified 258 evolutionarily conserved genes across species, describe the biological processes they converge on, and highlight regulatory pathways and drugs that may alleviate the habituation deficits associated with their dysregulation. We also summarize current habituation paradigms and extract the most decisive arguments from the literature that support the crucial role of habituation for cognition in health and disease. We conclude that habituation is a conserved, quantitative, cognition- and disease-relevant process that can connect preclinical and clinical work, and hence is a powerful tool to advance research, diagnostics,’’ and treatment of NDDs.

Trichoderma has been widely studied for its potential as a biocontrol agent against plant pathogenic organisms. Trichoderma's biological control mechanisms include competition, modification of environmental conditions, antibiosis, induction of plant defensive mechanisms, and mycoparasitism. Trichoderma species are known to produce a variety of secondary metabolites that have antifungal activity. These metabolites include peptaibols, gliotoxin, and trichokonins. Trichoderma also produces chitinases and β-1,3-glucanases that can degrade the cell walls of fungal pathogens. In addition to direct antagonism against fungal pathogens, Trichoderma can also induce systemic or localised resistance in plants, which is achieved through the production of elicitors such as chitin oligosaccharides and β-glucans that activate plant defence responses. Trichoderma can also form mutualistic associations with plants. In these associations, Trichoderma colonises the roots of plants and promotes plant growth by increasing nutrient uptake and inducing systemic resistance. Using Trichoderma as a biocontrol agent has several advantages over conventional crop protection techniques based on applying synthetic pesticides.

(1) Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medication to cure T2DM, the review of the literature found that various Pyrimidine derivative act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic beta-cells and its mechanism of action with fewer adverse effects.; (2) Methods: In the present research work, in-silico investigations were carried out to investigate the potential of Pyrimidine analogue as an agonists to the protein target GPR119 receptor. We performed exhaustive molecular modelling and protein modelling methodologies such as homology mod-elling, molecular docking along with various drug designing tools such as 3D-QSAR and pharmacophore mapping to ascertain the design of better GPR119 agonists.; (3) Results: On the basis of in-depth computa-tional studies, we designed new pyrimidine moiety and analyzed them for GPR-119 receptor agonist and fur-ther explored the ADME properties. Designed compounds found to exhibit better predicted activities as com-pared to reference compound; (4) Conclusions: The current research on pyrimidine derivatives, using molec-ular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of −11.696, -9.314 and -8.721 respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidate for the treatment of diabetes acting via GPR119 agonist mechanism.

Recent emergence of novel coronavirus (SARS-CoV-2) all over the world has resulted more than 33,106 global deaths. To date well-established therapeutics modules for infected patients are unknown. In this present initiative, molecular interactions between FDA-approved antiviral drugs against the Hepatitis-C virus (HCV) have been investigated theoretically against the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. HCV and SARS-CoV-2 are both +ssRNA viruses. At 25^o C beclabuvir, a non-nucleoside inhibitor of the RdRp_HCV can efficiently bind to RdRp _SARS-CoV-2 (ΔG_AutoDock = -9.95 kcal mol^-1) with an inhibition constant of 51.03 nM. Both the ΔG_London and ΔG_{GBVI / WSA} values were - 9.06 and - 6.67 kcal mol^-1, respectively for binding of beclabuvir to RdRp_SARS-CoV-2. In addition, beclabuvir has also shown better binding free energy with RdRp_SARS-CoV-2 (ΔG_vina = -8.0 kcal mol^-1) than that observed with the Thumb 1 domain of RdRp_HCV (ΔG_vina = -7.1 kcal mol^-1). InterProScan has suggested the RNA-directed 5'-3' polymerase activity exists within 549^th to 776^th amino acid residues of RdRp_SARS-CoV, where the major amino acid residues interacting being I591, Y621, C624, D625, A690, N693, L760, D762, D763, and E813-N817. Molecular interaction suggests occupancy of beclabuvir inside the active site environment of the RdRp_SARS-CoV-2, the enzyme essential for viral RNA synthesis. In conclusion, results suggest beclabuvir may serve as an anti-SARS-CoV-2 drug.

Background: Currently, limited number of therapeutic options are available to treat Diabetes mellitus, and to find a potential candidate, laboratory work takes time and also needs animal studies. So, the aim of this study was to determine the efficacy of some natural phytocompounds with the aid of molecular docking, bioinformatics and in silico drug design approaches. Method: Two proteins (Human CYP3A4 linked to metformin and Human dipeptidyl peptidase-IV) were selected and molecular docking studies were conducted using Pymol, AutoDock Vina, PyRx, and Discovery Studio. Different important pharmacokinetic parameters like ADME and toxicity data were obtained from online databases SwissADME and pkCSM program. Results: It was found that human dipeptidyl peptidase-IV (PDB ID: 4A5S) has exhibited a maximal affinity of -9.7 Kcal/mol for bryonolic acid and hesperidin, but only -6.7 kcal/mol for metformin hydrochloride. Similarly, the highest affinity of hesperidin for human CYP3A4 bound to metformin (PDB ID: 5G5J) is -10.7 Kcal/mol compared to metformin hydrochlor (-6.3 Kcal/mol). Besides, all the compounds have been documented outstanding ADMET profile, and accepted by drug-likeness or Lipinski rule. Conclusions: The present study suggested that these compounds can be further investigated in vitro and in vivo to establish them as lead compounds against Diabetes mellitus..

Rice, a globally important food crop, faces significant challenges due to salt and drought stress. These abiotic stresses severely impact rice growth and yield, manifesting as reduced plant height, decreased tillering, reduced biomass, and poor leaf development. Recent advances in molecular biology and genomics have uncovered key physiological and molecular mechanisms that rice employs to cope with these stresses, including osmotic regulation, ion balance, antioxidant re-sponses, signal transduction, and gene expression regulation. Transcription factors such as DREB, NAC, and bZIP, as well as plant hormones like ABA and GA, have been identified as crucial reg-ulators. Utilizing CRISPR/Cas9 technology for gene editing holds promise for significantly en-hancing rice stress tolerance. Future research should integrate multi-omics approaches and smart agriculture technologies to develop rice varieties with enhanced stress resistance, ensuring food security and sustainable agriculture in the face of global environmental changes.

Knee joint injuries, including those affecting the anterior cruciate ligament (ACL), meniscus, and cartilage, present significant challenges in sports medicine and orthopedics. Understanding the cellular and molecular mechanisms underlying these injuries is essential for developing effective therapeutic strategies. This systematic review explores the cell biology of knee joint injuries, focusing on the effects of early mechanical loading. We examine the types of knee injuries, cellular responses to mechanical loading, signaling pathways involved, and implications for treatment and rehabilitation. This comprehensive synthesis aims to provide insights into optimizing rehabilitation protocols and developing novel therapeutic approaches.

Alzheimer's disease (AD), which is characterized by the development of β-amyloid plaques and neurofibrillary tangles in the brain parenchyma, can result in synaptic and neuronal loss. Clinical signs, including deteriorating memory deficiency, may lead to catastrophic effects for the elderly. Research on brain imaging and its application in the study of AD has advanced extraordinarily over the past 30 years. However, widely used imaging methods are only capable of identifying structural or metabolic alterations at the anatomical level in the brain and can only be utilized for drawing inferential distinctions. As a disease with a complex pathophysiological mechanism, AD has many different molecular pathological features and molecular biomarkers. Therefore, molecular imaging for AD pathology indicators provides a practical method for the early diagnosis and impartial assessment of AD. The present review discusses the pathogenesis of AD, as well as the detection methods and principles of molecular imaging, such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) techniques. Meanwhile, various tracers and probes applied in molecular imaging that detect Aβ deposits, tau protein accumulation, and neurotransmitters are also reviewed. Molecular pathological tracers provide the possibility to accurately quantify brain changes through molecular imaging.

The purpose of this article is to highlight the new advancements in molecular and diagnostic genetic testing as well as properly classify all ovarian cancers. In this article we address statistics, histopathological classification, molecular pathways implicated in ovarian cancer, genetic screening panels and details about the genes, and also candidate genes. We hope to bring new information in the medical field as to better prevent and diagnose ovarian cancer.

Natural products from plants such as, chemopreventive agents attract huge attention because of their low toxicity and high specificity. The rational drug design in combination with structure based modeling and rapid screening methods offer significant potential for identifying and developing lead anticancer molecules. Thus, the molecular docking method plays an important role in screening a large set of molecules based on their free binding energies and proposes structural hypotheses of how the molecules can inhibit the target. Several peptide based therapeutics have been developed to combat several health disorders including cancers, metabolic disorders, heart-related, and infectious diseases. Despite the discovery of hundreds of such therapeutic peptides however, only few peptide-based drugs have made it to the market. Moreover, until date the activities of cyclic peptides towards molecular targets such as protein kinases, proteases, and apoptosis related proteins have never been explored. In this study we explore the in silico kinase and protease inhibitor potentials of cyclosaplin as well as study the interactions of cyclosaplin with other cancer-related proteins. Previously, the structure of cyclosaplin was elucidated by molecular modeling associated with dynamics that was used in the current study. Docking studies showed strong affinity of cyclosaplin towards cancer-related proteins. The binding affinity closer to 10 indicated efficient binding. Cyclosaplin showed strong binding affinities towards protein kinases such as EGFR, VEGFR2, PKB and p38 indicating its potential role in protein kinase inhibition. Moreover, it displayed strong binding affinity to apoptosis related proteins and revealed the possible role of cyclosaplin in apoptotic cell death. The protein-ligand interactions using LigPlot displayed some similar interactions between cyclosaplin and peptide-based ligands especially in case of protein kinases and a few apoptosis related proteins. Thus, the in silico analyses gave an insight of cyclosaplin as a potential apoptosis inducer and protein kinase inhibitor.

To improve the wear resistance of polyimide (PI), surface modification was developed. In this study, the tribological properties of graphene (GN), graphene oxide (GO), and KH550-grafted graphene oxide (K5-GO) modified PI were evaluated by molecular dynamics (MD) at the atomic level. The findings indicated that the addition of nanomaterials can significantly enhance the friction performance of PI. The friction coefficient of PI composites decreased from 0.253 to 0.232, 0.136, and 0.079 after coating GN, GO and K5-GO, respectively. Among them, the K5-GO/PI exhibited the best surface wear resistance. Importantly, the mechanism behind the modification of PI was thoroughly revealed by observing the wear state, analyzing the changes of interfacial interactions, interfacial temperature, and relative concentration.

The commercial cultivation of microalgae began in the 1960s and Chlorella was one of the first target organisms. The species has long been considered a potential source of renewable energy, an alternative for phytoremediation, and more recently, as a growth and immune stimulant. However, Chlorella vulgaris, which is one of the most studied microalga, has never been comprehensively profiled chemically. In the present study, comprehensive profiling of the Chlorella vulgaris metabolome grown under normal culture conditions was carried out, employing tandem LC-MS/MS to profile the ethanolic extract and GC-MS for fatty acid analysis. The fatty acid profile of C. vulgaris was shown to be rich in omega-6, -7, -9, and -13 fatty acids, with omega-6 being the highest, representing more than sixty percent (>60%) of the total fatty acids. This is a clear indication that this species of Chlorella could serve as a good source of nutrition when incorporated in diets. The profile also showed that the main fatty acid composition was that of C₁₆-C₁₈ (>92%), suggesting that it might be a potential candidate for biodiesel production. LC-MS/MS analysis revealed carotenoid constituents comprising violaxanthin, neoxanthin, lutein, β-carotene, vulgaxanthin I, astaxanthin, and antheraxanthin, along with other pigments such as the chlorophylls. In addition to these, amino acids, vitamins, and simple sugars were also profiled, and through mass spectrometry-based molecular networking, 48 phospholipids were putatively identified.

Eurycomanone and eurycomalactone are known quassinoids present in the roots and stems of Eurycoma longifolia. These compounds had been reported to have cytotoxic effects, however, their mechanism of action in a few cancer cell lines have yet to be elucidated. This study was aimed to investigate the anti-cancer effects and mechanisms of action of eurycomanone and eurycomalactone in cervical (HeLa), colorectal (HT29) and ovarian (A2780) cancer cell lines via Sulforhodamine B assay. Their mechanism of cell death was evaluated based on Hoechst 33342 assay and in silico molecular docking toward DHFR and TNF-α as putative protein targets. Eurycomanone and eurycomalactone exhibited in vitro anti-cancer effects manifesting IC50 values of 4.58 ± 0.090 µM and 1.60 ± 0.12 µM (HeLa), 1.22 ± 0.11 µM and 2.21 ± 0.049 µM (HT-29), and 1.37 ± 0.13 µM and 2.46 ± 0.081 µM (A2780) respectively. They induced apoptotic cancer cell death in dose- and time-dependent manners. Both eurycomanone and eurycomalactone were also predicted to have good inhibitory potential as demonstrated by the docking into TNF-α with binding affinity of -8.83 and -7.51 kcal/mol, respectively, as well as into DHFR with binding affinity results of -8.05 and -8.87 kcal/mol, respectively. These results support the evidence of eurycomanone and eurycomalactone as anti-cancer agents via apoptotic cell death mechanism that could be associated with TNF-α and DHFR inhibition as among possible protein targets.

The new coronavirus SARS-CoV-2 is the cause of the COVID-19 pandemic, which has created an incomparable global health problem. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. The review begins by elucidating the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Employing homology modeling, a tertiary structure model of PLpro is constructed, laying the groundwork for subsequent investigations. To expedite the search for potential therapeutic candidates, the study harnesses computational methodologies. Molecular docking techniques are employed to explore binding sites for antiviral drugs within the catalytic region of PLpro. This computational approach not only aids in drug development but also provides crucial preliminary data before experimental research commences. The stability of drug-PLpro complexes is assessed through comprehensive all-atom molecular dynamics (MD) simulations, affording dynamic insights into drug-PLpro interactions. By evaluating binding energy estimates from MD simulations, stable drug-PLpro complexes with potential antiviral properties are identified. However, it is emphasized that experimental validation is imperative to confirm these computational findings, necessitating in vitro and in vivo tests to assess safety and efficacy. This pivotal stage bridges the computational realm with real-world clinical applications. The review emphasizes the imperative need for enhancements in the existing PLpro-targeting drugs currently on the market. Their actions are insufficient for clinical use and necessitate thorough characterization and improvement. The Supervised Molecular Dynamics (SuMD) simulation technique reveals critical information about drug unbinding pathways, shedding light on opportunities for refinement. In addition to optimizing existing drugs, the investigation of sub-structurally similar molecules emerges as a promising avenue for drug development. In conclusion, the review underscores the pivotal role of targeting SARS-CoV-2 PLpro in the ongoing battle against COVID-19. By integrating molecular dynamics simulations, structural modeling, and computational insights, a robust foundation is established for identifying promising antiviral drug candidates. The continual need for improvement in existing drugs and the exploration of novel compounds remain paramount in the global effort to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, illustrating the interdisciplinary synergy crucial to this endeavor.

The aim of this study was to investigate the relationship between postprandial glycemic levels based on flash-monitoring and the production of intestinal hydrogen (H2) and methane (CH4) gases based on measurement of the amount of these gases in exhaled air. We studied 14 subjects with type 2 diabetes mellitus (T2DM) and 10 individuals without diabetes (control) with 3 food-load tests with simultaneous determination of gases in exhaled air and assessment of glucose levels. In 15.4% of patients with T2DM, there was a non-significant increase in exhaled H2. How-ever, all subjects in the control group had significant increase in exhaled H2. Moreover, the level of H2 in exhaled breathafter food load in patients with T2DM was lower than in normoglycemic subjects. Also, in normoglycemic subjects there was an inverse correlation between maximum glucose rise and maximum H2 in exhaled air after food load. At the same time in patients with T2DM the level of CH4 in exhaled air directly correlated with the parameters of postprandial glycemia in the test with lactulose. Confirmation of a causal relationship between decreased H2 production, increased intestinal CH4 production, and more severe postprandial glycemia may identify new therapeutic targets in the correction of postprandial glycemia in patients with T2DM.

Electrostatic interactions have a determining role in conformational and dynamic behavior of polyelectrolyte molecules [1]. In this study, anionic polyelectrolyte molecules, poly(glutamic acid) (PGA) and poly(aspartic acid) (PASA), in water solution with the most commonly used K+ or Na+ counterions were investigated using atomistic molecular dynamics (MD) simulations. Seven common force fields, AMBER99SB-ILDN, AMBER14SB, AMBER-FB15, CHARMM22*, CHARMM27, CHARMM36m and OPLS-AA/L, both with their native parameters and with the non-bonded fix (NBFIX) and electronic continuum corrections (ECC) to were studied. These corrections have bene introduced to correct for the problem of overbinding of ions to the charged groups of polyelectrolytes. Physical properties, such as molecular sizes, local structure and dynamics, were studied using two types of common counterions, potassium and sodium. The results show that in some cases, the macroion size and dynamics depend strongly on the models (parameters) for the counterions due to strong overbinding of ions and charged side chain groups. The local structures and dynamics are more sensitive on dihedral angle parameterization resulting in a preference for defined monomer conformations amd the type of correction used.

Andalusia is a Spanish region that is home to numerous minority varieties due to its diversity and territorial extension, offering the local viticulture the possibility of diversifying its wine production. The molecular identification of 98 specimens from six areas with a winemaking tradition in Andalusia was carried out between the years 2020 and 2022. Thirteen microsatellite markers were used in this study, including the nine recommended by the OIV. 31 different genotypes were obtained, 20 of which corresponded to profiles of already described varieties (11 of them are of minority cultivation in Andalusia: 'Rojal Tinto', 'Beba', 'Zurieles', 'Rome', 'Hebén', 'Mollar Cano', 'Listán Prieto', 'Listán del Condado', 'Jarrosuelto', 'Negra Dorada' and 'Mantúo de Pilas'), while the other 11 profiles did not match with previously identified varieties. This profiles were integrated into the database of the IFAPA “Rancho de la Merced” Germplasm Bank. The eco-geographical groups of the new identified genotypes were determined through analysis of genetic diversity. The presence of the Grapevine Fanleaf Virus, the Grapevine Fleck Virus and the Grapevine Leafroll associated Viruses was also analyzed using an ELISA test due to the necessity of having certifiable clones of the new varieties for their potential interest in being authorized for its cultivation in Spain.

Levan is a fructan-type exopolysaccharide, which is produced by many microbes from sucrose via extracellular levansucrases. The hydrocolloid properties of levan depend on its molecular weight, while it is unknown why and to which extent levan is functionally diverse in dependence of its size. The aim of our study was to get deeper insights into the size-dependent, functional variability of levan. For this purpose, levans of different sizes were produced using the water kefir isolate Gluconobacter albidus TMW 2.1191 and subsequently rheologically characterized. Three levan types could be identified, which are similarly branched, but significantly differ in their molecular size and rheological properties among each other. The smallest levan (< 107 Da) produced without adjustment of the pH exhibited Newton-like flow behavior up to a specific concentration of 25% (w/v). On the contrary, larger levans (> 108 Da) produced at pH ≥ 4.5 were shear-thinning and showed a gel like behavior at ≥ 5% (w/v). A third (intermediate) levan variant was obtained via production in buffers at pH 4.0 and exhibited the properties of a viscoelastic fluid at ≥ 5% (w/v). Our study reveals that the variable size and composition of levan are controllable and more decisive for its functionality than the amount of exerted levan.

: Early and accurate detection of infectious diseases is a key step for surveillance, epidemiology, and control, notably timely disease diagnosis, patient management and follow-up. In this study, we aimed to develop hand-held ultra-fast duplex PCR assays coupled to amplicon detection by lateral flow (LF) immunoassay to deliver a rapid, and simple molecular diagnostic test for con-comitant detection and identification of the main Leishmania parasites encountered in Tunisia and the Old World. We selected two DNA targets to amplify L. major/L. tropica and L. infantum/L. tropica group of species DNAs, respectively. We optimized the experimental conditions of a du-plex ultra-fast PCR. The amplification is performed by a portable Palm convection PCR machine within 18 min and the products are detected by a LF cassette within 10 minutes. The test allows the identification of the infecting species according to the position and number of test lines re-vealed. Tested on a selection of DNAs of representative Leishmania strains of the three studied species (N=37), the ultra-fast duplex PCR-LF showed consistent, stable, and reproducible results. The analytical limit of detection of the test was 0.4pg for L. major, 4pg for L. infantum and 40pg for L. tropica.

Background: Diabetic patients are more likely to experience morbidity and mortality as a result of microvascular complications such as retinopathy, neuropathy, nephropathy, and stroke. There are many synthetic anti-diabetic agents available which are expensive and have undesirable pathological effects. Thus, it is essential to look for cost-effective, natural, and safe antidiabetic agents. The aim of this study was to screen phytoconstituent and evaluate the in-vitro and in-silico α-amylase inhibitory activity of ethanolic extract of Adhatoda vasica leaves. Method: The extraction of Adhatoda vasica leaves was performed with ethanol through Soxhlet extraction process. Different concentrations (0.1 mg/ml to 1 mg/ml) of ethanolic extract, Acarbose, and Sitagliptin, were prepared and all concentrations were evaluated for α-amylase inhibitory activity through the spectrophotometric method. Molecular docking (AutodockVina 1.2.0) and toxicity profiling (SToPToX web server) studies were performed. Results: The plant extract showed highest inhibition of α-amylase (56.763±0.0035) at a concentration of 1 mg/ml. This inhibitory activity was supported by the in-silico study. Vasicoline (C5) and quercetin (C9), active constitute of plant Adhatoda vasica, showed the best binding energy of 8.3 and 8.0 Kcal/mol respectively with α-amylase enzyme (PDBID: 4W93). Toxicity study revealed the safety profile of plant extract. Conclusion: It was concluded that Adhatoda vasica leaves possess some bioactive compounds which are responsible for controlling blood glucose levels and its identification, purification, and isolation may lead to the development of newer therapeutic agent with lesser side effects.

ShK domain-containing proteins are peptides found in different parasitic and venomous organisms. From a previous transcriptomic dataset from Bursaphelenchus xylophilus, a plant-endoparasitic nematode that infects forest tree species, we identified 96 transcripts potentially as ShK domain-containing proteins with unknown function in the nematode genome. This study aimed to characterize and explore the functional role of genes encoding ShK domain-containing proteins in B. xylophilus biology. We selected and functionally analyzed nine candidate genes specific from B. xylophilus. In situ hybridization revealed expression of one B. xylophilus ShK in the pharyngeal gland cells, suggesting their delivery into host cells. Most of the transcripts are highly expressed during infection and showed a significant upregulation in response to peroxide products compared to the nematode catalase enzymes. We reported for the first time, the potential involvement of ShK domain genes in oxidative stress, suggesting that these proteins may have an important role protecting or modulating the reactive oxygen species (ROS) activity of the host plant during parasitism.

In bilaterians organism, the signaling of pyramidal neurons (PyrNs) is linked to the relative (prevalent) molecular chirality and physiological, perceptual, cognitive, and psychological functions and dysfunctions, providing the coupling of the central nervous system downstream and upstream evolutionary and developmental processes. The most apparent and discriminating morphological specificity of PyrNs is the geometry of the cell body. However, the question "why/how PyrNs soma gains the shape of quasi-tetrahedral symmetry" has never been explicitly articulated. If the basic function of PyrNs is sensory space perception, supporting the orientation, and movement coordination, then the pyramidal shape of soma is the best evolutionary-selected geometry to perform sensory-motor coupling. In biology, the impact of chiral symmetry (handedness) is evident at all levels of biological organization, from the prevalent symmetry of biological molecules to the morphology and function of bilateral organisms. How the tetrahedral symmetry of biomolecules is linked to the morphology and functions of bilateral organisms remains a challenging question. Cell chirality represents an intermediate point connecting two poles of biochirality. In this holistic perspective, examining the PyrNs' morphology-circuitry-function link is crucial to understanding the complex interaction between genetic, epigenetic, and environmental factors in the evolution of the CNS. The predictive power of our hypothesis can be partially expressed by the statement that the most integral and reliable biomarker of the neurodegenerative (including aging) and mental (including all variants of psychiatric illness) disorders would be the detection of the hemispheric asymmetry of D-amino acids (D-AAs) level in pyramidal neurons (PyrNs).

When liquids are confined into nanometer-scale slit, the induced layering-like film structure allows the liquid to sustain non-isotropic stresses and thus being load-bearing. Such anisotropic characteristics of liquid under confinement arise naturally from the liquids’ wave number dependent compressibility that does not need solidification to take place as a prerequisite. In other words, liquids under confinement can still remain fluidity with molecules being (sub-)diffusive. However, the extensively prolonged structural relaxation time can cause hysteresis of stress relaxation of confined molecules in response to the motions of confining walls and thereby yield the quasi-static stress tensor history-dependent. In this work, by means of molecule dynamics, the discrepancy of stress tensor of a highly confined key base-oil component, i.e. 1-decene trimer, is captured after its relaxation from being compressed and decompressed. The results indicate that among the effects (e.g. confinement, molecular structure, and film density) that can potentially affect confined stress tensor, the ordering status of the confined molecules plays a predominant role.

Molecular engineering research is the fundamental way and the only way for the development of biomaterials. Based on molecular engineering, the biocompatibility of natural conformation and polymer biomaterials was studied. In this paper, we discuss that natural conformation is the basis of protein biological function, and that the synergistic action of peptide chain and side group is the motive force for protein to construct natural conformation and complete biological function. On the basis of the influence of the adsorption of polymer biomaterials on the natural conformation of proteins, the relationship between biocompatibility of biomaterials and protein conformation is further explained. Studies have shown that bismuth molecular materials can only be applied in the market and have their functionality if they have good biocompatibility. Therefore, the biocompatibility evaluation of new materials has important practical significance.

Background: The aim was to diagnose Candida in the oral cavity of subjects with type 2 diabetes mellitus (T2DM) using a genotyping technique and to compare the results with those from con-ventional diagnosis by Papanicolau (Pap) staining. Methods: Palatal mucosa smears were per-formed in 18 dental care patients diagnosed with T2DM and grade I, II, and III prosthetic stomatitis who met the inclusion criteria; 18 healthy control subjects were also included in the study. He-moglobin A1c (HbA1c) levels were determined from total blood. Using exfoliative cytology, the Pap staining technique was used to diagnose candidiasis. Exfoliative cytology was also used for molecular diagnosis; DNA was obtained for Candida genotyping and RNA was used for gene ex-pression studies. Results: Clinical patterns indicated that all subjects were positive for Candida; however, Pap analysis revealed only three positive subjects, whereas end-point polymerase chain reaction (PCR) analysis revealed fifteen subjects with some type of Candida. The most common Candida species found were Candida guilliermondii (38.8%), Candida krusei (33.3%), Candida tropicalis, and Candida lusitaniae (22.2%). Interestingly, the coexpression of different species of Candida was found in various patients. In all patients, HbA1c levels were increased. Gene expression analysis showed a significant decrease (p ≤ 0.05) in TLR2 expression in positive subjects, whereas TLR4 expression did not differ significantly among patients. Conclusions: The end-point PCR technique showed better sensitivity for diagnosis of Candida when compared with diagnosis by Pap staining. T2DM subjects showed an increased presence of C. guilliermondii that was correlated with decreased TLR2 expression

Several therapeutic monoclonal antibodies are approved by FDA against the PD-1/PD-L1 (programmed death-1/programmed death ligand-1) immune checkpoint, which has been a great success in cancer treatment. However, existing therapeutics, including small molecules inhibitors against PD-L1 checkpoint have certain drawbacks such as high cost and drug resistance that challenge the current available anti-PD-L1 therapy. Thereof, this study presents the screening of 32552 compounds from Natural Product Atlas database against PD-L1, including three steps of structure-based virtual screening and binding free energy refinement for the selection of potent PD-L1 inhibitors. Subsequently, five natural compounds, i.e., Neoenactin B1, Actinofuranone I, Cosmosporin, Ganocapenoid A, and 3-[3-hydroxy-4-(3-methylbut-2-enyl)phenyl]-5-(4-hydroxybenzyl)-4-methyldihydrofuran-2(3H)-one, were collected based on the ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling and binding free energy (>-70 kcal/mol) for further computational investigation by comparison to co-crystallised ligand, i.e. JQT inhibitor. Based on interaction mapping, explicit 100 ns molecular dynamics simulation, and post binding free energy calculations, all the compounds exhibited intermolecular interactions (hydrogen and hydrophobic) with essential residues and substantial complex stability by comparison to the JQT inhibitor. Collectively, the calculated results advocate the selected natural compounds as the putative potent inhibitors of PD-L1 and, therefore, can be considered for further development of PD-L1 immune checkpoint inhibitor in cancer immunotherapy.

B-cell lymphoid malignancies is a heterogeneous group of hematologic cancers, where Bruton's tyrosine kinase (BTK) inhibitors have received FDA approval for several subtypes. The first-in-class covalent BTK inhibitor, ibrutinib, binds to the C481 amino acid residue to block the BTK enzyme and prevent the downstream signaling. Resistance to covalent BTK inhibitors can occur through mutations at the BTK binding site (C481S) but also other BTK sites and the phospholipase C gamma 2 (PLCγ2) resulting in downstream signaling. To bypass the C481S mutation, non-covalent BTK inhibitors, such as pirtobrutinib, were developed and are active against both wild-type and the C481S mutation. In this review, we discuss the molecular and genetic mechanisms which contribute to acquisition of resistance to covalent and non-covalent BTK inhibitors. In addition, we discuss the new emerging class of BTK degraders, which utilize the evolution of proteolysis-targeting chimeras (PROTACs) to degrade the BTK protein and constitute an important avenue of overcoming resistance. The moving landscape of resistance to BTK inhibitors and the development of new therapeutic strategies highlight the ongoing advances, that are being made towards the pursue of cure of B-cell lymphoid malignancies.

Abies beshanzuensis, an extremely endangered species, attracts serious concerns on genetic diversity recovery and population protection. However, little genetic information was known about it till now. In this study, intra-/intergenomic ITS variation, secondary structure, and molecular phylogeny of A.beshanzuensis were determined by nrDNA-ITS marker, and results indicated that, ITS region featured rich polymorphism in ITS1 and highly conservative in 5.8S/ITS2 among intra-/inter-genome, implying rich genetic diversities and the occurrence of non-concerted evolution in ITS region. Predicated 5.8S structure possessed Helices-Loops with 3 motifs (M1/M2/M3) and 5 helices B4-B8, and ITS2 could form conservative Clover-like structure with 5 ribotypes, manifesting genetically structural generalities and individualities. Thirteen ITS pseudogenes were also identified from 76 samples (or clones). Molecular phylogeny revealed that, A.beshanzuensis shared genetically closer relationships with A.fanjingshanensis, A.chensiensis, A.yuanbaoshanensis among genus Abies. The available original data provided rich genetic information on ITS sequence, structure and molecular phylogeny of A.beshanzuensis, which not only updated the databases of ITS sequences as well as secondary structures essential for phylogenetic reference and DNA barcoding analyses, but also contributed to deep exploration of population diversities, origin and evolution as well theoretical direction for population recovery and protection of A.beshanzuensis.