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PubMed1992

Application of restrained minimization, simulated annealing and molecular dynamics simulations for the conformational analysis of oligosaccharides.

The purpose of the present study was to determine the confidence with which the small number of 1H NMR nuclear Overhauser effect (NOE) distance constraints measurable across glycosidic linkages in oligosaccharides could be used for solution conformational analysis. This was assessed by use of these constraints in restrained molecular mechanical minimization of the tetrasaccharide Gal beta 1----4(Fuc alpha 1----3)Glc-NAc beta 1----3Gal, a model compound of the Lewis-X antigenic determinant. This presents a particularly severe test case in view of extreme resonance overlap and a dearth of inter-residue distance constraints. It is concluded that these constraints, when used in conventional restrained minimization, result in the generation of 'virtual conformations' and local minima about glycosidic linkages. However, these restraints are nevertheless found to be useful in the initial stages of a conformational analysis strategy involving restrained minimization combined with dynamical simulated annealing to define more accurately the global minimum energy configuration, together with molecular dynamics simulation to explore conformational mobility about this minimum. Theoretical ROE values calculated over the time course of the MD simulation, using a formalism appropriate for the time scale of the internal motion, are compared with those obtained experimentally in the oligosaccharide.

Carbohydrate Conformation↗

PubMed2026

Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, andexperiments.

OBJECTIVE: To investigate the mechanism of action of Qinlian Jiangxia decoction (, QLJXD) in the treatment of type 2 diabetes mellitus (T2DM) complicated by hyperlipidemia using network pharmacology, molecular docking, molecular dynamics simulation and in vivo experiments. METHODS: Drug components, targets and disease targets were identified using databases such as TCM systems pharmacology database and analysis platform and GeneCards. The intersecting targets were subjected to protein-protein interaction analysis using the search tool for the retrieval of interacting genes/proteins database. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersecting targets were conducted using the Metascape platform to identify core components and targets. The results were validated using molecular docking, molecular dynamics simulations and in vivo experiments. RESULTS: QLJXD contains 76 active ingredients and 136 disease targets. The core ingredients are quercetin, β-sitosterol, wogonin and baicalein, while the core targets are fatty acid binding protein 4 (FABP4) and peroxisome proliferative activated receptor gamma (PPARG). Molecular docking and molecular dynamics simulations revealed that the core ingredients bound well to the core targets. Animal experiments demonstrated that QLJXD effectively inhibited the expression of FABP4 and increased the expression of PPARG, thereby enhancing disorders of glycolipid metabolism. CONCLUSION: The putative therapeutic efficacy of QLJXD in the management of T2DM complicated with hyperlipidemia may be ascribed to the synergistic actions of multiple components, such as quercetin, β-sitosterol, wogonin, and baicalein, which collectively modulate FABP4 and PPARG molecular targets.

Molecular Docking Simulation↗

PubMed2026

Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.

INTRODUCTION: Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. METHODS: The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. RESULTS: A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. DISCUSSION: This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. CONCLUSION: This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Molecular Docking Simulation↗

PubMed2026

Exploring the mechanism of Shengmai San in treating lung adenocarcinoma based on bioinformatics and molecular dynamics simulation.

To investigate the mechanism of Shengmai San (SMS) in the treatment of lung adenocarcinoma (LUAD) based on an integrated strategy combining "network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation," aiming to provide a precise combination therapy strategy and identify potential bioactive compounds. Differentially expressed genes in LUAD were identified from the Gene Expression Omnibus database using R (originally developed at Bell Laboratories and currently managed by Lucent Technologies). SMS components (ginseng, Ophiopogon japonicus, and Schisandra chinensis) were retrieved from encyclopaedia of traditional Chinese medicine, with Lipinski-compliant compounds selected. Compound targets were predicted via SwissTargetPrediction and Similarity Ensemble Approach. Intersecting targets between differentially expressed genes and compound targets were identified for "herbs-compounds-targets-disease" network construction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Hub targets were identified by analyzing the protein-protein interaction network. High-prognostic relevance targets were screened from The Cancer Genome Atlas. Compounds targeting these were identified through the herbs-compounds-targets-disease network, and absorption, distribution, metabolism, excretion, and toxicity-compliant compounds were selected using SwissADME (a web-based tool provided by the Molecular Modeling Group of the Swiss Institute of Bioinformatics). Core regulatory targets were identified through molecular docking, with complex stability assessed by molecular dynamics simulations. The key bioactive compounds of SMS for treating LUAD were identified as 7-hydroxy-2,5-dimethyl-4H-1-benzopyran-4-one, N-trans-feruloyltyramine, paprazine, and (E)-N-[(2S)-2-hydroxy-2-(4-hydroxyphenyl)ethyl]-3-(4-hydroxyphenyl)prop-2-enamide. Hub targets included AURKA, CCNA2, CCNB1, CDK1, CHEK1, KIF11, NEK2, PLK1, TTK, and TYMS. Among these, CDK1, CHEK1, and PLK1 demonstrated both high-prognostic relevance and strong binding affinity with SMS, emerging as core regulatory targets for SMS in LUAD treatment. Mechanistically, SMS exerts its anticancer effects primarily by modulating the tumor necrosis factor, interleukin-17, cell cycle, and Lipid and atherosclerosis signaling pathways. The active components of SMS, such as paprazine, may exert antitumor effects partly through downregulating CDK1, CHEK1, and PLK1 expression. Although the present study did not examine drug-resistance models or combination regimens, our findings raise the possibility that, in patients with high expression of these genes, combining SMS with standard chemotherapy or targeted therapy could potentially enhance chemosensitivity and mitigate the development of resistance. This hypothesis, however, requires formal testing in appropriate preclinical models and functional validation studies.

Molecular Dynamics Simulation↗

PubMed1992

3 Nsec molecular dynamics simulation of the protein ubiquitin and comparison with X-ray crystal and solution NMR structures.

Mainly due to computational limitations, past protein molecular dynamics simulations have rarely been extended to 300 psec; we are not aware of any published results beyond 350 psec. The present work compares a 3000 psec simulation of the protein ubiquitin with the available x-ray crystallographic and solution NMR structures. Aside from experimental structure availability, ubiquitin was studied because of its relatively small size (76 amino acids) and lack of disulfide bridges. An implicit solvent model was used except for explicit treatment of waters of crystallization. We found that the simulated average structure retains most of the character of the starting x-ray crystal structure. In two highly surface accessible regions, the simulation was not in agreement with the x-ray structure. In addition, there are six backbone-backbone hydrogen bonds that are in conflict between the solution NMR and x-ray crystallographic structures; two are bonds that the NMR does not locate, and four are ones that the two methods disagree upon the donor. Concerning these six backbone-backbone hydrogen bonds, the present simulation agrees with the solution NMR structure in five out-of-the six cases, in that if a hydrogen bond is present in the x-ray structure and not in the NMR structure, the bond breaks within 700 psec. Of the two hydrogen bonds that are found in the NMR structure and not in the x-ray structure, one forms at 1400 psec and the other forms rarely. The present results suggest that relatively long molecular dynamics simulations, that use protein x-ray crystal coordinates for the starting structure and a computationally efficient solvent representation, may be used to gain an understanding of conformational and dynamic differences between the solid-crystal and dilute-solution states.

Computer Simulation↗

PubMed2023

A new horizon in the phosphorylated sites of AGA: the structural impact of C163S mutation in aspartylglucosaminuria through molecular dynamics simulation.

Aspartylglucosaminuria (AGU) is a lysosomal storage disorder caused by insufficient aspartylglucosaminidase (AGA) activity leading to chronic neurodegeneration. We utilized the PhosphoSitePlus tool to identify the AGA protein's phosphorylation sites. The phosphorylation was induced on the specific residue of the three-dimensional AGA protein, and the structural changes upon phosphorylation were studied via molecular dynamics simulation. Furthermore, the structural behaviour of C163S mutation and C163S mutation with adjacent phosphorylation was investigated. We have examined the structural impact of phosphorylated forms and C163S mutation in AGA. Molecular dynamics simulations (200 ns) exposed patterns of deviation, fluctuation, and change in compactness of Y178 phosphorylated AGA protein (Y178-p), T215 phosphorylated AGA protein (T215-p), T324 phosphorylated AGA protein (T324-p), C163S mutant AGA protein (C163S), and C163S mutation with Y178 phosphorylated AGA protein (C163S-Y178-p). Y178-p, T215-p, and C163S mutation demonstrated an increase in intramolecular hydrogen bonds, leading to greater compactness of the AGA forms. Principle component analysis (PCA) and Gibbs free energy of the phosphorylated/C163S mutation structures exhibit transition in motion/orientation than Wild type (WT). T215-p may be more dominant among these than the other studied phosphorylated forms. It might contribute to hydrolyzing L-asparagine functioning as an asparaginase, thereby regulating neurotransmitter activity. This study revealed structural insights into the phosphorylation of Y178, T215, and T324 in AGA protein. Additionally, it exposed the structural changes of the C163S mutation and C163S-Y178-p of AGA protein. This research will shed light on a better understanding of AGA's phosphorylated mechanism.Communicated by Ramaswamy H. Sarma.

Molecular Dynamics Simulation↗

PubMed2026

Molecular docking, molecular dynamics simulation, and enzyme inhibitory studies of vitamin K family members on aldose reductase.

Aldose reductase (AR) is a key enzyme in the polyol pathway and plays a major role in the progression of secondary complications of diabetes. Despite extensive efforts to develop natural and synthetic aldose reductase inhibitors (ARIs), most candidates have shown limited clinical efficacy, highlighting the need for more potent and selective inhibitors. In this study, we have systematically evaluated the inhibitory potential of vitamin K family members (vitamin K1, vitamin K2, and vitamin K3) using molecular docking, protein-ligand interaction analysis, molecular dynamics simulations, and enzyme kinetics. Docking analysis predicted that vitamin K2 has the highest binding affinity for AR. Subsequent molecular dynamics simulations revealed that both vitamin K1 and vitamin K2 formed stable complexes with the protein, exhibiting comparable RMSD (∼0.5 Å difference), similar RMSF profiles, and reduced radius of gyration, indicating compact and stable binding. Interaction analysis demonstrated that ligand binding is predominantly driven by hydrophobic interactions, with vitamin K2 forming a higher number of hydrophobic contacts, while vitamin K1 exhibited slightly more hydrogen bonding. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) results further supports stronger binding of vitamin K2 (-56 kcal/mol) compared to vitaminK1 (-51 kcal/mol). Consistent with these findings, enzyme kinetics showed a slightly lower Ki value for vitamin K2 than vitamin K1. In contrast, vitamin K3 failed to maintain stable binding and moved out of the active site during simulation. Overall, the study highlights that hydrophobic interaction-driven stabilization plays a key role in ligand binding, and identifies vitamin K1 and vitamin K2 as promising inhibitors against AR, with vitamin K2 exhibiting more favourable hydrophobic interactions and binding stability.

Aldose Reductase↗

PubMed2026

Structure-based virtual screening, multi-score docking, and molecular dynamics simulation of novel small molecules targeting the epidermal growth factor receptor for potential management of oral squamous cell carcinoma.

UNLABELLED: Oral squamous cell carcinoma (OSCC) is a major global health burden, with epidermal growth factor receptor (EGFR) serving as an important therapeutic target. However, resistance to currently available EGFR inhibitors limits the efficacy of long-term treatment. In this study, a structure-based virtual screening approach was employed using the Mcule database to identify novel small molecules with potential EGFR-inhibitory activity. The top-ranked compounds were subjected to consensus docking using multiple docking platforms and compared with established EGFR inhibitors. The most promising complexes were further evaluated using 500 ns molecular dynamics simulations to investigate their structural stability, conformational flexibility, and binding persistence. ADMET and pharmacokinetic analyses were performed to assess the drug-like and safety profiles. Five lead compounds (C1-C5) demonstrated significant binding affinities toward EGFR, ranging from - 9.9 to - 9.2 kcal/mol, while satisfying the major drug-likeness criteria. Molecular dynamics simulations suggested that C1 and C4 may form relatively stable EGFR-ligand complexes, as supported by stable RMSD convergence and persistent interactions with key active-site residues throughout the simulation period. Trajectory-based interaction analyses further indicated a sustained binding behavior. ADMET profiling predicted favorable oral bioavailability and low predicted toxicity for most compounds, particularly C3 and C5, although a potential risk of cytochrome P450-mediated drug-drug interactions was observed. Overall, the shortlisted compounds exhibited docking and dynamic stability profiles comparable to those of the reference inhibitor Lapatinib. These findings suggest the potential therapeutic relevance of structurally novel EGFR-targeting scaffolds in OSCC and provide a foundation for future experimental validation through in vitro and in vivo studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s40203-026-00722-4.

ADMET↗

PubMed2025

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 kcal/mol, tighter than co-crystal ligands and existing protein-binding drugs. Molecular dynamics simulations confirmed interaction stability through low root-mean-square deviation (< 0.5 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 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↗

PubMed2026

Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties.

FcγRI is a high-affinity receptor for IgG, associated with autoimmune disease pathology and determines clinical responses to antibody-based immunotherapies. FcγRI has a complex evolutionary history that is not fully understood, and to address this we explored signatures of positive selection in the receptor's functional gene, FCGR1A, using codon-based selection tests on aligned 1-1 orthologous sequences from placental mammals (n = 32). Signatures of positive selection have occurred at several locations within the gene, with two sites (H148 (M2a ω 0.997 & M8 ω = 0.993)) and (W149 (M2a ω = 0.999 & M8 ω = 1.000)) exhibiting highest posterior probabilities, suggesting strong evidence of positive selection; these positions are known to form one of the FcγRI-IgG binding interfaces. We employed ancestral reconstruction to statistically infer prior codon sequences at these sites and identified ancestral H148P and W149R codons at different nodes in the phylogeny. Employing molecular dynamics simulations, we determined how evolutionary changes at these sites may have influenced the binding of FcγRI-IgG of modern-day Homo sapiens. Measuring RMSD, free energy, radius of gyration, hydrogen bond formation, and analyzing free energy landscapes, we demonstrate that structural instability between mutant structures vs the WT counterpart; however, overall binding potential increases at position 148, yet decreases at 149 in potential. H148P protonation at physiological pH remains similar, yet during acidotic calculations, protonation is likely reduced, with predicted reduction in affinity for IgG. While ancestral W149R substitutions demonstrate an implication for electron conjugation. Examining key sites at this binding FcγRI-IgG interface, our data demonstrate that these two codons have evolved in humans to be relatively insensitive to shifts in pH promoting a more stable interaction with the Fc portion of IgG during diseases that promote acidosis.

Receptors, IgG↗

PubMed2025

Molecular dynamics simulations reveal subtle consequences of H3K9 and H3K27 tri-methylation on chromatin constituents.

Epigenetic modifications of histone tails are key mechanisms of genome regulation. In particular, tri-methylation of lysines (K) 9 and K27 of the histone H3 tail is important for genome silencing. In this work, we explore, using all-atom molecular dynamics simulations, the effect of these two epigenetic marks on the structure and interactions of the H3 tail in several contexts: isolated tails, nucleosomes, chromatosomes, and stacked nucleosomes. Overall, we find that although the isolated tails do not show significant conformational changes upon methylation, a more flexible and extended H3 tail compared to the native tail results in the nucleosome systems, with K9 methylation effects more pronounced. This change could facilitate the interaction of the tail with protein readers like heterochromatin protein 1 or Polycomb group. We also observe that both methylations increase the interactions of the H3 tail with the linker DNA in the context of the chromatosome, producing a chromatosome with tighter linker DNA, which could favor chromatin compaction. For stacked nucleosomes mimicking i±2 zigzag interactions, methylation of either K9 or K27 reduces the interactions of one of the H3 tails with its parental nucleosome and increases its interactions with the nonparental nucleosome, which could also help compact the chromatin fiber. In the three nucleosome-containing systems, we observe an asymmetry between the two tails, especially in the chromatosome, where one tail extends to interact with the linker DNA. This asymmetry modulates the effect that methylation has on each tail. Thus, overall, methylations of K9 and K27 have a subtle but notable impact on the H3 tail structure and its interactions within the chromatin fiber. These results help explain how this epigenetic modification compacts chromatin fibers and promotes longer-range interactions; these changes also guide how to approximate these effects in coarse-grained chromatin models.

Histones↗

PubMed1992

Molecular dynamics studies of a DNA-binding protein: 2. An evaluation of implicit and explicit solvent models for the molecular dynamics simulation of the Escherichia coli trp repressor.

Although aqueous simulations with periodic boundary conditions more accurately describe protein dynamics than in vacuo simulations, these are computationally intensive for most proteins. Trp repressor dynamic simulations with a small water shell surrounding the starting model yield protein trajectories that are markedly improved over gas phase, yet computationally efficient. Explicit water in molecular dynamics simulations maintains surface exposure of protein hydrophilic atoms and burial of hydrophobic atoms by opposing the otherwise asymmetric protein-protein forces. This properly orients protein surface side chains, reduces protein fluctuations, and lowers the overall root mean square deviation from the crystal structure. For simulations with crystallographic waters only, a linear or sigmoidal distance-dependent dielectric yields a much better trajectory than does a constant dielectric model. As more water is added to the starting model, the differences between using distance-dependent and constant dielectric models becomes smaller, although the linear distance-dependent dielectric yields an average structure closer to the crystal structure than does a constant dielectric model. Multiplicative constants greater than one, for the linear distance-dependent dielectric simulations, produced trajectories that are progressively worse in describing trp repressor dynamics. Simulations of bovine pancreatic trypsin were used to ensure that the trp repressor results were not protein dependent and to explore the effect of the nonbonded cutoff on the distance-dependent and constant dielectric simulation models. The nonbonded cutoff markedly affected the constant but not distance-dependent dielectric bovine pancreatic trypsin inhibitor simulations. As with trp repressor, the distance-dependent dielectric model with a shell of water surrounding the protein produced a trajectory in better agreement with the crystal structure than a constant dielectric model, and the physical properties of the trajectory average structure, both with and without a nonbonded cutoff, were comparable.

Amino Acid Sequence↗

PubMed1992

Solution structure of the Lewis x oligosaccharide determined by NMR spectroscopy and molecular dynamics simulations.

The Lewis x (Lex) determinant is a trisaccharide fragment that has been implicated as a specific differentiation antigen, as a tumor antigen, and as a key component of the ligand for the endothelial leukocyte adhesion molecule, ELAM-1. High-resolution nuclear magnetic resonance spectroscopy shows it to have a relatively rigid structure. Only a small range of glycosidic dihedral angles in the trisaccharide produce simulated nuclear Overhauser effect spectra agreeing with data measured for the human milk pentasaccharide, lacto-N-fucopentaose-3, which contains the Lex determinant. Independently, the same average structure for the Lex determinant arises from in vacuo molecular dynamics simulations. The proposed conformation of the Lex trisaccharide is very similar to that recently determined for the closely related Lea trisaccharide. In agreement with the recent finding that both sialylated Lea and Lex react with ELAM-1, the results presented here show that the Lea and Lex determinants contain very similar carbohydrate domains.

Carbohydrate Conformation↗

PubMed1992

Molecular dynamics simulations of the resting and hydrogen peroxide-bound states of cytochrome c peroxidase.

The current hypothesis for the formation of the catalytically active compound I of peroxidases from the resting state and peroxide involves formation of a reversible "inner-sphere" complex in which the peroxide is bound to the heme iron. It is this precursor that is postulated to then form compound I. However, this crucial putative transient intermediate has not yet been definitively detected or characterized by experimental methods. We report here the use of energy minimization and molecular dynamics simulation together with the known X-ray structure of cytochrome c peroxidase to investigate the nature of this complex and comparisons of it with the resting state in which a water is bound as a ligand. Among the properties monitored in these simulations are the mode of binding of the peroxide to the heme iron, its interactions with neighboring amino acid residues, and the extent to which the binding of the peroxide perturbs both the local environment around the heme unit and more distant regions. The results of this study indicate that solvated, full protein dynamics is required to obtain reliable results for the known resting-state complex and hence for the uncharacterized peroxide complex. In this complex, the peroxide binds to the heme iron in a dynamically averaged end-on fashion, rather than a bridged structure, with approximately equal probability of each oxygen serving as the ligand to the iron. Binding of the peroxide as a ligand disrupts the H-bonded network of waters in the distal binding pocket which are present in the resting state, but there is no dramatic perturbation of the nearby amino acid residues.(ABSTRACT TRUNCATED AT 250 WORDS)

Amino Acids↗

PubMed1992

Nuclear magnetic resonance studies and molecular dynamics simulations of the solution conformation of a 'designed', alpha-helical peptide.

The complete three-dimensional structure in methanol of an amphipathic alpha-helical peptide, that has been designed by taking into account the three-dimensional structures of small haemolytic peptides, secondary structure prediction algorithms and the well documented literature on alpha-helix stabilizing factors, has been elucidated by two-dimensional NMR spectroscopy. Initially various two-dimensional spectra (COSY, TOCSY, and NOESY) allowed the complete sequence specific assignment of all signals in the 1H spectrum. Consequently trial structures were generated which were then subjected to molecular dynamics simulations using 121 NOE-derived distances and 25 vicinal coupling constant values as structural restraints to give a final set of calculated structures. These structures are in complete agreement with the results of a circular dichroism study and reveal that the peptide adopted a highly ordered alpha-helical conformation. Details of the structure which throw light on future peptide/protein design are discussed.

Amino Acid Sequence↗

PubMed2026

Investigating the mechanisms of PhIP-induced colorectal cancer through network toxicology, machine learning, and molecular dynamics simulation.

BACKGROUND: Over the past few years, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)- a compound from grilled or processed meats-has emerged as a major player in cancer development, especially colorectal cancer (CRC). This work dives into its potential links to CRC and uncovers the key genes that bridge this connection. METHODS: We tapped into various databases to pinpoint target genes tied to PhIP and CRC, then ran protein-protein interaction (PPI) analyses for visualization. Next, we explored underlying mechanisms through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. To nail down predictions, we tested 107 machine learning pipelines and picked the best one, validating its accuracy and the core genes' prognostic value across datasets. Next, molecular docking and dynamics simulations probed the interactions between these genes and PhIP. Finally, cell proliferation was assessed using Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2'-deoxyuridine (EdU) assays, and polymerase chain reaction (PCR) was performed to validate the expression levels of the hub genes. RESULTS: Our analysis identified 39 overlapping genes, from which a machine learning model (glmBoost + Enet) identified six candidate targets: CDK4, CEBPB, COMT, SOX9, TIMP1, and TOP2A. To prioritize these, a hierarchical screening framework was applied. Molecular docking and dynamics simulations identified CDK4, COMT, and TIMP1 as the most stable interactors with PhIP. Functional assays confirmed that PhIP treatment significantly enhanced the proliferation of CRC cells. Crucially, quantitative PCR (qPCR) validation in multiple CRC cell lines identified TIMP1 as the primary target, showing the most consistent and significant upregulation upon PhIP exposure. CONCLUSIONS: In essence, these genes drive PhIP is role in CRC, offering novel insights into its molecular pathways. This could reshape how we tackle food-related pollutants, paving the way for better prevention and targeted therapies.

Colorectal cancer (CRC)↗

PubMed2026

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗

PubMed2026

Leveraging bioinformatics approaches for drug repositioning in space radiation protection.

The health effects of space radiation, primarily Galactic Cosmic Rays (GCRs), on humans remain largely unknown, with potential cardiovascular consequences posing a significant threat to astronauts on long-duration spaceflight missions. Currently, there are no established pharmacological countermeasures for GCR exposure. Drug repositioning offers a promising strategy to accelerate pharmaceutical research in space medicine. This study leverages existing bioinformatics techniques to identify and prioritize potential drug candidates associated with proteomic perturbations following simulated GCR exposure using previously published murine cardiac proteomic data. A protein-protein interaction (PPI) network was constructed using the top differentially expressed proteins (DEPs) from murine heart tissue following exposure to 5-ion GCRs as seed nodes, focusing on experimentally supported interactions. Network topology, Markov clustering, and functional enrichment analyses were used to characterize biologically relevant proteins and pathways. Drug-protein interactions were predicted using Drugst.One and mapped to PPI clusters of interest to identify candidate drugs. Selected drug-macromolecule interactions were further explored using CB-Dock2 molecular docking and short-duration molecular dynamics simulations as hypothesis-generating structural assessments. Analysis of a key PPI network cluster consisting of several ATP synthase proteins identified 23 unique drug candidates. These analyses demonstrate a systematic approach for leveraging bioinformatics techniques to identify candidate molecular targets and generate pharmacological hypotheses in the context of space radiation countermeasures. Ultimately, this strategy introduces a hypothesis-generating framework for the prioritization of potential drug candidates for future computational characterization and experimental investigation against spaceflight stressors.

Animals↗