PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Molecular docking simulation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources

Molecular docking of balanol to dynamics snapshots of protein kinase A.

Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.

Azepines↗

Genomic and structural analysis of dacB variants associated with cephalosporin resistance in Pseudomonas aeruginosa.

The rise of resistance to fourth-generation cephalosporin in Pseudomonas aeruginosa (P. aeruginosa) is a global concern. The resistance is largely driven by variants of chromosomally encoded AmpC β-lactamase, known as Pseudomonas-derived cephalosporinase (PDC), which arise from the mutations in the ampC gene. In addition, alteration in dacB, which encode the penicillin-binding protein 4 (PBP4), can lead to the overexpression of ampC, thereby contributing to β-lactam resistance. Present work analyzed 208 clinical isolates of P. aeruginosa using whole-genome sequencing (WGS) and detected multiple nonsynonymous single nucleotide polymorphisms (nsSNPs), such as Y264C, G444D, and a double mutation (A394P-T428P). All nsSNPs were predicted to be deleterious by several prediction program. Molecular dynamics (MD) simulations suggested that these substitutions destabilize PBP4, increase structural flexibility, and contribute to the resistance mechanism, which favored their selection. To determine the effective therapeutics against these mutations, molecular docking was conducted with various antibiotics. Cefoperazone exhibited the highest binding affinity (-7.3 kcal/mol) among multiple PBP4 variants. The Molecular dynamics (MD) simulations and Molecular Mechanics Poisson Boltzmann Surface Area calculations (MMPBSA) further confirmed the favorable interactions between cefoperazone and PBP4 variants. In vitro MIC analyses supported these findings, indicating that cefoperazone displayed significant activity against clinical dacB mutants of P. aeruginosa. The study offers structural insight of dacB variants leading to antibiotic resistance and emphasizes the need to prioritize specific antibiotics to address the challenges arising from protein mutations.

Pseudomonas aeruginosa↗

In silico, in vitro, and in vivo characterization of thiamin-binding proteins from plant seeds.

Thiamin, an essential micronutrient, is a cofactor for enzymes involved in the central carbon metabolism and amino acid pathways. Despite efforts to enhance thiamin content in rice by incorporating thiamin biosynthetic genes, increasing thiamin content in the endosperm remains challenging, possibly due to a lack of thiamin stability and/or a local sink. The introduction of storage proteins has been successful in several biofortification strategies, and similar efforts targeting thiamin have been performed, leading to a 3-4-fold increase in white rice. However, only one thiamin-binding protein (TBP) sequence has been described in plants, more specifically from sesame seeds. Therefore, we aimed to identify and characterize TBPs, as well as to evaluate the effect of their expression on thiamin concentration, using a comprehensive approach integrating in silico, in vitro, and in vivo methods. We identified the sequences of putative TBPs from Oryza sativa (Os, rice), Fagopyrum esculentum (Fe, buckwheat), and Zea mays (Zm, maize) and pinpointed the thiamin-binding pockets through molecular docking. FeTBP and OsTBP contained one pocket with binding affinities similar to the Escherichia coli TBP, a well-characterized TBP, supporting their function as TBPs. In vivo expression studies of TBPs in tobacco leaves and rice callus resulted in increased thiamin levels, with FeTBP and OsTBP showing the most pronounced effects. Additionally, thermal shift assays confirmed the thiamin-binding capabilities of FeTBP and OsTBP, as observed by the significant increases in melting temperatures upon thiamin binding, indicating protein stabilization. These findings offer new insights into the diversity and function of plant TBPs and highlight the potential of FeTBP and OsTBP to modulate thiamin levels in crop plants.

Thiamine↗

Molecular dynamics simulations of the docking of substituted N5-deazapterins to dihydrofolate reductase.

Orientations of the deazapterin ring and the conformational preferences of groups appended to the deazapterin ring in a set of 8-substituted deazapterin cations docked into the dihydrofolate reductase (DHFR) binding site have been investigated using a methodology based on the simulated annealing technique within molecular dynamics (MD) simulations. Of five possible binding pockets for the 8-substituents, identified from a preliminary manual docking study, one has been definitively eliminated after an analysis of MD trajectories, while another remains uncertain. Using a new method based on standard thermodynamic cycles and a linear approximation of polar and non-polar free energy contributions from MD averages, binding affinities of the different ligands in each binding site have been correlated with experimental dissociation constants. The study has provided insights into structure-activity relationships for use in the design of modified inhibitors of DHFR.

Binding Sites↗

Carboxyl group number and acidity of organic acids regulate structural reorganization and low glycemic index in cassava pyrodextrins via molecular interactions.

Transforming high-glycemic cassava starch into functional dietary fiber via pyrodextrinization is a promising way to valorize tuber crops, yet the molecular mechanisms catalyzed by organic acids with different carboxyl numbers and acidity remain unclear. This study investigates how carboxyl number and acidity of acetic acid (AA), tartaric acid (TA), and citric acid (CA) affect structural reorganization and low glycemic properties of cassava pyrodextrins. Compared with AA, TA, and CA with stronger acidity and more carboxyl groups promoted more extensive hydrolysis, transglycosylation, repolymerization, and esterification. These changes increased indigestible glycosidic linkages and the branching degree, while reducing molecular weight. Molecular docking confirmed stronger hydrogen-bonding interactions between TA/CA and starch chains. Furthermore, TA- and CA-catalyzed pyrodextrins exhibited superior anti-digestive properties with resistant starch up to 54.26% and an estimated glycemic index as low as 42.46, highlighting the critical role of carboxyl numbers and acidities in modulating the functionality of pyrodextrins.

Manihot↗

Putative hAPN receptor binding sites in SARS_CoV spike protein.

AIM: To obtain the information of ligand-receptor binding between the S protein of SARS-CoV and CD13, identify the possible interacting domains or motifs related to binding sites, and provide clues for studying the functions of SARS proteins and designing anti-SARS drugs and vaccines. METHODS: On the basis of comparative genomics, the homology search, phylogenetic analyses, and multi-sequence alignment were used to predict CD13 related interacting domains and binding sites in the S protein of SARS-CoV. Molecular modeling and docking simulation methods were employed to address the interaction feature between CD13 and S protein of SARS-CoV in validating the bioinformatics predictions. RESULTS: Possible binding sites in the SARS-CoV S protein to CD13 have been mapped out by using bioinformatics analysis tools. The binding for one protein-protein interaction pair (D757-R761 motif of the SARS-CoV S protein to P585-A653 domain of CD13) has been simulated by molecular modeling and docking simulation methods. CONCLUSION: CD13 may be a possible receptor of the SARS-CoV S protein, which may be associated with the SARS infection. This study also provides a possible strategy for mapping the possible binding receptors of the proteins in a genome.

Amino Acid Sequence↗

Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.

BACKGROUND: Stenotrophomonas maltophilia is a multidrug-resistant opportunistic pathogen causing severe hospital-acquired infections, especially in immunocompromised patients. The absence of an effective vaccine and rising antibiotic resistance underscore the need for novel interventions. This study employed an integrated reverse vaccinology and computational analyses to identify new immunogenic targets, design a multi-epitope vaccine (MEV), and propose potential drug targets. METHODS: A comprehensive immunoinformatics pipeline was employed to assess antigenicity, allergenicity, human similarity, and physicochemical properties of S. maltophilia proteins. Both B- and T-cell epitopes were screened; however, only the top B-cell epitopes were selected for MEV construction, given the extracellular nature of S. maltophilia. MEV-TLR interactions were analyzed through molecular docking and dynamics simulations. In parallel, cytoplasmic proteins were screened via a subtractive genomics approach to identify essential, non-human homologous, and non-microbiome-similar proteins, which were further evaluated for druggability and interaction networks to propose novel therapeutic targets. RESULTS: From a total of 4111 proteins, seven potential immunogenic targets were identified: GspD (WP_108270537.1), FhuE (WP_049451370.1), fimbrial protein (WP_012479122.1), TonB-dependent receptor (WP_169448402.1), TolC family protein (WP_108270106.1), autotransporter beta-barrel OMP (WP_169448945.1), and a hypothetical protein (WP_005407892.1). Subsequently, an MEV was designed using five immunogenic epitopes derived from four of these targets: WP_005407892.1 (ADQDSSNM), WP_049451370.1 (SGKAEQ and GEESKTPS), WP_108270537.1 (GVTSTQSDSERT), and WP_169448945.1 (RELGGDRNE). Molecular docking and molecular dynamics simulations demonstrated strong, stable, and feasible interactions between the MEV and TLR-2 and TLR-4 receptors. Moreover, nine novel drug targets were predicted for S. maltophilia, providing new therapeutic insights. CONCLUSION: The designed MEV and identified immunogenic targets represent promising vaccine candidates against S. maltophilia. Further in vitro and in vivo studies are essential to confirm their safety, immunogenicity, and protective efficacy. Additionally, subtractive genomics analysis revealed nine novel, non-homologous drug targets, offering safer and more specific therapeutic avenues.

Drug targets↗

Computational discovery of emodin-based anthraquinones as PARP-1 inhibitors with relevance to ovarian and prostate cancer.

Cancer is a disease characterized by genomic instability and aberrant DNA repair. Poly (ADP-ribose) polymerase-1 (PARP-1) represents a well-established therapeutic target, particularly in ovarian and prostate cancer. However, the currently approved PARP inhibitors face challenges such as resistance, toxicity, and reduced efficacy. The search for alternative scaffolds has therefore become increasingly urgent. In this study, we used an integrated approach combining computer-aided methods to search for potential lead compounds among emodin-based anthraquinone derivatives as PARP-1 inhibitors. Using a PASS-based QSAR approach, drug-likeness prediction, and in silico ADMET assessment, we pre-screened a large set of anthraquinones and identified several potential hits for interaction with PARP-1. These hits were studied using molecular docking with the PARP-1 catalytic domain (PDB ID: 7KK4). The most stable and compact complexes were further explored by 500 ns molecular dynamics (MD) simulations and various dynamic properties (RMSD, RMSF, Rg, SASA, MolSA, hydrogen bonds, PCA, DCCM). The key finding of this study is that several emodin-derived anthraquinones exhibited binding behavior and ADMET profiles comparable to, or better than, the reference PARP-1 inhibitor. Among them, CID-10425624 emerged as the most promising candidate, exhibiting stable binding, reduced conformational fluctuation, compact complex formation, persistent hydrogen-bond interactions, and enhanced dynamic residue correlations within the PARP-1 catalytic domain. These findings suggest that the anthraquinone scaffold can provide a valuable starting point for developing structurally distinct PARP-1 inhibitors. In summary, this study identified several emodin-derived anthraquinones, particularly CID-10425624, as computationally prioritized lead candidates for PARP-1 inhibition, providing a novel anthraquinone-based scaffold for further experimental validation and optimization.

Anthraquinones↗

EWS-RNA Binding Protein 1: Structural Insights into Ewing Sarcoma by Conformational Dynamics Investigations.

BACKGROUND: Prior research has demonstrated that proteins play a significant role in the prognosis and treatments of various sarcomas, including Ewing sarcoma through the interplay of downstream signaling cascades. However, there is limited understanding about the strcucture conformation of EWSR1 and its structural implication in the prognosis of Ewsing Sarcoma by interaction with RNA molecules. AIMS: The primary goal of ongoing research is to determine how EWSR1 contributes to Ewing sarcoma. OBJECTIVE: The current study explores the complexity of EWSR1 structure and its conformational interactions with RNA in relation to Ewing sarcoma. METHODS: Here, we employed a comparative modeling approach to predict EWSR1 domains separately and assembled them into one structural unit using a DEMO server. Additionally, the RNA motifs interacting with EWSR1 were predicted, and the 3D model was built using RNAComposer. Protein-RNA docking and MD simulation studies were carried out to check the intermolecular interactions and stability behavior of docked EWSR1-RNA complexes. RESULTS: The overall results explore the structural insights into EWSR1 and their interactions with RNA, which may play a momentous role in co- and post-transcriptional regulation to control gene expression. CONCLUSION: Taken togather, our findings suggest that EWSR1 may be a useful therapeutic target for the diagnosis and management of Ewing sarcoma.

Sarcoma, Ewing↗

LARS promotes hepatocellular carcinoma progression via the PI3K/AKT/mTOR pathway and interaction with RPS5, and serves as a prognostic biomarker.

BACKGROUND: Hepatocellular carcinoma (HCC) caused many cancer deaths around the world. Its progression involves complex mechanisms, creating an urgent need to identify new therapeutic targets. Leucine-tRNA synthetase (LARS) is a key enzyme for protein synthesis, but its specific role and mechanism in HCC are not well understood. PURPOSE: This research aims to investigate the biological function, molecular mechanism, and clinical relevance of the LARS gene in HCC progression, to assess its potential as a treatment target. METHODS: LARS expression was assessed in HCC cell lines (PLC-PRF-5, HCC-LM3) and in mouse subcutaneous tumor models using siRNA and adeno-associated virus (AAV). Techniques including Cell Counting Kit-8(CCK-8), colony formation, EdU, Transwell, wound healing, and flow cytometry were used to measure cell proliferation, migration, invasion, and apoptosis. RNA-seq, proteomics (TMT), western blot, co-immunoprecipitation (Co-IP) with mass spectrometry, molecular docking, and molecular dynamics simulation were employed to study the affected signaling pathway (PI3K/AKT/mTOR) and interacting protein (RPS5). The TCGA (The Cancer Genome Atlas) database and UALCAN platform were used to analyze links between LARS expression and clinicopathological features or prognosis in HCC patients. RESULTS: Reducing LARS expression significantly inhibited the proliferation, colony formation, migration, and invasion of HCC cells, while promoting apoptosis. In mice, LARS knockdown markedly slowed tumor growth. Mechanistic studies showed that reducing LARS expression levels affected the PI3K/AKT/mTOR signaling pathway and led to decreased levels of the key interacting protein RPS5. Overexpressing RPS5 partly reversed the proliferation inhibition caused by LARS depletion. Molecular docking and dynamics simulations suggested that the environmental contaminant triphenyl phosphate (TPP) might bind to the LARS protein. Clinical data analysis revealed that LARS expression is higher in HCC tissues. High LARS expression was significantly associated with shorter overall survival (OS) in patients and correlated positively with various clinical features like tumor stage, grade, and TP53 mutation status. CONCLUSION: LARS helped HCC become worse by affecting the PI3K/AKT/mTOR pathway and working with RPS5. High LARS meant a worse outcome for patients. This suggested LARS could be used to predict disease or as a treatment target in HCC.

Carcinoma, Hepatocellular↗

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans↗

Exploring potential targets and molecular mechanisms of traumatic brain injury exacerbated by Benzo(a)pyrene via network toxicology and molecular dynamics simulation.

Benzo(a)pyrene (BaP) is a common environmental pollutant from combustion sources that promotes oxidative stress, neuroinflammation and disruption of blood-brain barrier (BBB). However, its contribution to worsening traumatic brain injury (TBI) remains unclear. In this study, we aimed to assess the contribution of BaP to secondary injury in TBI. By integrating data from e.g., the Comparative Toxicogenomics Database, GeneCards, and Online Mendelian Inheritance in Man, 121 overlapping core targets were identified between BaP and TBI. Enrichment analyses via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, combined with protein-protein interaction networks and topological algorithms (degree, closeness centrality, betweenness centrality, average shortest path length, topological coefficient and partner of multi-edged node pairs), highlighted five hub genes (TP53, EGFR, AKT1, ACTB, and TNF) implicated in mitogen-activated protein kinase signaling, oxidative stress, and neuroinflammation. Molecular docking showed strong binding affinities of BaP to these hub proteins, with energies from -9.3 to -12.1&#xa0;kcal/mol, tighter than co-crystal ligands and existing protein-binding drugs. Molecular dynamics simulations confirmed interaction stability through low root-mean-square deviation (<&#x2009;0.5&#xa0;nm), fluctuation, and radius of gyration values. Calculation of binding free energies using MM-PBSA validated the strong binding affinity between BaP and binding pockets of each hub genes. Toxicity prediction analysis revealed an oral LD50 of 316&#xa0;mg/kg for BaP, with high probabilities for neurotoxicity, BBB permeability, carcinogenicity, and mutagenicity, associated with aryl hydrocarbon receptor activation. These findings reveal a "neurovascular homeostasis disruption" network underlying BaP-exacerbated TBI pathology and highlight potential targets to reduce pollution-related risks in TBI management.

Benzo(a)pyrene↗

Modeling Polarization in Proteins and Protein-ligand Complexes: Methods and Preliminary Results.

This chapter discusses methods for modeling electronic polarization in proteins and protein-ligand complexes. Two different approaches are considered: explicit incorporation of polarization into a molecular mechanics force field and the use of mixed quantum mechanics/molecular mechanics methods to model polarization in a restricted region of the protein or protein-ligand complex. A brief description is provided of the computational methodology and parameterization protocols and then results from two preliminary studies are presented. The first study employs quantum mechanics/molecular mechanics (QM/MM) methods to improve the accuracy of protein-ligand docking; here, incorporation of polarization is shown to dramatically improve the robustness of the accuracy of structural prediction of the protein-ligand docking by enabling qualitative improvement in the selection of the correct hydrogen bonding patterns of the docked ligand. The second study discusses a 2-ns simulation of bovine pancreatic trypsin inhibitor (BPTI) in water using a variety of fixed charge and polarizable models for both the protein and the solvent, analyzing observed root mean square deviations (RMSD), intraprotein hydrogen bonding, and water structure and dynamics. All of these efforts are in a relatively early stage of development, the results are encouraging in that stable methods have been developed, and significant effects of polarization are seen and (in the case of the QM/MM-based docking) improvements have been validated as compared to experiment. With regard to accuracy and robustness of full simulations, a great deal more work needs to be done to quantitate and improve the present models.

Animals↗

Toward selective histone deacetylase inhibitor design: homology modeling, docking studies, and molecular dynamics simulations of human class I histone deacetylases.

Histone deacetylases (HDACs) play an important role in gene transcription. Inhibitors of HDACs induce cell differentiation and suppress cell proliferation in tumor cells. Although many HDAC inhibitors have been designed and synthesized, selective inhibition for class I HDAC isoforms is a goal that has yet to be achieved. To understand the difference between class I HDAC isoforms that could be exploited for the design of isoform-specific HDAC inhibitors, we have built three-dimensional models of four class I histone deacetylases, HDAC1, HDAC2, HDAC3, and HDAC8. Comparison of the homology model of HDAC8 with the recently published X-ray structure shows excellent agreement and validates the approach. A series of HDAC inhibitors were docked to the homology models to understand the similarities and differences between the binding modes. Molecular dynamic simulations of these HDAC-inhibitor complexes indicate that the interaction between the protein surface and inhibitor is playing an important role; also some active site residues show some flexibility, which is usually not included in routine docking protocols. The implications of these results for the design of isoform-selective HDAC inhibitors are discussed.

Amino Acid Sequence↗

Plausible interaction of an alpha-fetoprotein cyclopeptide with the G-protein-coupled receptor model GPR30: docking study by molecular dynamics simulated annealing.

In this manuscript, the procedure of molecular dynamics simulated annealing is applied to locate a probable receptor and binding site of a cyclicpeptide that inhibits estrogen-stimulated proliferation of breast cancer. The hydrophilic cyclopeptide EMTOVNOGQ (O = 4-hydroxyproline), derived from alpha-fetoprotein, is an inhibitor of estrogen-stimulated proliferation of human breast cancer. This peptide has been shown to act through a mechanism different from that of estrogen; however, its receptor is unknown. We report computer experiments that suggest that this peptide may execute its actions by interacting with GPR30, a G-protein-coupled receptor. The subject of this work is the simulation, by molecular dynamics simulated annealing, of the interaction of cyclopeptide EMTOVNOGQ with receptor GPR30 protein. A conformational analysis of the cyclopeptide was undertaken and the final structure was docked on several sites of the GPR30 3D model. Our results show that the cyclopeptide interacts on the pocket located between TM6 and TM7 transmembrane helices of the G-protein, triggering a slight conformational change in the secondary structure of the receptor in the complex. Based on differences in accessible surface areas between GPR30 and its ligand, the residues in the interaction zone were identified. The cyclopeptide is stabilized in the active site by forming a network of hydrogen bonds between Glu, Thr, (1)Pro(OH) and GLn residues of the ligand and Arg-259, Cys-271, Asn-316, Asn-320 and Tyr-324 of the G-protein. Moreover, the study of the electrostatic surface potential on the GPR30 receptor shows that the active site is more positively charged than the other sites. Our modeling indicates a plausible interaction of the cyclopeptide with the seven transmembrane GPR30 protein. This may have profound implications for the treatment of breast cancer.

Amino Acid Sequence↗

Integrated computational and experimental benchmarking of Bacillus phage endolysins reveals the relationship between peptidoglycan-fragment recognition descriptors and antibacterial performance.

Protein-based antibacterials such as bacteriophage endolysins offer a targeted therapeutic strategy against Gram-positive pathogens. However, prioritizing the most effective candidates from the large sequence diversity available remains a significant challenge. Here we present a standardized computational-experimental benchmarking framework that evaluates seven phage-derived endolysin variants (E1, E2, E3, E7, E10, E12, and E15) identified from Bacillus genomes. We combined molecular docking and residue-level interaction mapping against muramyl dipeptide (MDP), a minimal conserved peptidoglycan motif, with 1000-ns molecular dynamics simulations, MM/PBSA binding free-energy estimation, and matched functional inhibition assays against Staphylococcus aureus and Micrococcus luteus. Computational analyses revealed generally favorable MDP recognition across variants, albeit with notable differences in contact patterns and complex stability profiles. Experimental screening identified E2 as the most potent antibacterial agent against both species, while E7 and E1 performed strongly in selected computational metrics. Integrated analysis showed only modest correlations between computational descriptors of fragment recognition/stability and observed antibacterial performance. This study establishes a practical comparative benchmarking platform for endolysin candidate prioritization, nominates E2 and E7 as promising candidates for further development, and highlights E1 as a potential structural scaffold for rational engineering, while explicitly demonstrating both the utility and the current limitations of using minimal peptidoglycan fragments as proxies for full cell-wall recognition in lysin benchmarking.

Endopeptidases↗

Molecular recognition analyzed by docking simulations: the aspartate receptor and isocitrate dehydrogenase from Escherichia coli.

Protein docking protocols are used for the prediction of both small molecule binding to DNA and protein macromolecules and of complexes between macromolecules. These protocols are becoming increasingly automated and powerful tools for computer-aided drug design. We review the basic methodologies and strategies used for analyzing molecular recognition by computer docking algorithms and discuss recent experiments in which (i) substrate and substrate analogues are docked to the active site of isocitrate dehydrogenase and (ii) maltose binding protein is docked to the extracellular domain of the receptor, which signals maltose chemotaxis.

Amino Acid Sequence↗

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000&#x202f;ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2&#x202f;kcal/mol), Arjunapthanoloside (-7.7&#x202f;kcal/mol), and Beta-sitosterol (-7.4&#x202f;kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6&#x202f;kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000&#x202f;ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC&#x2085;&#x2080; of 9&#x202f;&#xb5;g/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗