Background:Mutations in isocitrate dehydrogenase 1 (IDH1) and 2 (IDH2) are prevalent drivers of acute myeloid leukemia (AML). While targeted therapies exist, resistance can emerge. This study explored the potential of natural products to identify novel dual IDH inhibitors.Methods:In silico screening of the COCONUT database was performed using Lipinski’s Rule of Five. Pharmacophore modeling identified crucial features for IDH binding. Docking simulations with Glide (Schrödinger) assessed binding affinity, followed by MM-GBSA calculations for free energy estimation. The most promising candidate underwent ADME/T and toxicity analysis. Finally, molecular dynamics (MD) simulations evaluated the stability of protein-ligand complexes and binding interactions, followed by trajectory analysis using dynamical cross-correlation matrix (DCCM) and principal component analysis (PCA).Results:Ternstroside D (CNP0166496) emerged as a potential dual inhibitor of IDH1 and IDH2 mutations. Docking and MM-GBSA analyses showed strong affinities with IDH1 (–14.2, –84.45 kcal/mol) and IDH2 (–16.8, –60.73 kcal/mol), exceeding those of reference inhibitors GSK321A (–9.6 kcal/mol) and Enasidenib (–8.9 kcal/mol). Key hydrogen-bond interactions with catalytic residues and stable binding during MD simulations support its dual mechanism. ADME/T predictions indicated drug-like properties and a favorable safety profile, highlighting Ternstroside D as a natural scaffold with superior binding compared with existing IDH inhibitors.Conclusion:This in silico study provides compelling evidence for Ternstroside D (CNP0166496) as a promising dual inhibitor for IDH1 and IDH2 mutations in AML. Furthermore, in vitro and in vivo studies are warranted to validate these findings.

Protein–protein interactions (PPIs) have becomeincreasinglyattractive as therapeutic targets due to their central role in regulatingcellular functions. Despite computational advancements, accuratelyestimating binding free energies for PPIs remains challenging dueto the dynamic and critically solvent-exposed nature of their interfaces.In this study, we present MnM-W-MMGBSA (i.e., MM-GBSA with Mix-and-Matchsampling and water inclusion), a method that addresses these challengesby incorporating both conformational flexibility and interfacial solvationeffects. We thoroughly demonstrated the applicability of MnM-W-MMGBSAacross a diverse set of 20 PPI systems and validated its robustnessusing two distinct and rigorous simulation schemes. We demonstratethat our protocol improves correlation with experimental binding affinitiesfrom47% to 70% with MnM sampling alone for standard MM-GBSA, and up to89% when interfacial water molecules are included. Our approach underscoresthe pivotal role of individual protein dynamics in validating theconcept of “destabilization of individual proteins in the unboundform.” Specifically, we show that in explicit solvent, suchdestabilization leads to a loss of native structure, suggesting thatexcessive conformational sampling may compromise the accuracy of bindingaffinity predictions. Furthermore, the critical role of intrinsicallydisordered regions in the interface of PPIs, as well as the impactof the MnM approach in the pairwise per-residue energy decomposition,were also investigated. Finally, our implementation overcomes thelimitations of the gmx_MMPBSA tool for incorporating explicit solventmolecules from MD simulation trajectories into the complex/receptorduring MM-GBSA calculation, providing an automated and reproducibleworkflow using GROMACS with AmberTools to enable efficient high-throughputscreening of protein–protein complexes. The protocol is robust,computationally efficient, and applicable to a broad range of PPIs.Overall, our protocol offers a practical and physically meaningfulalternative for estimating the binding affinities of PPIs and providesa valuable tool for advancing peptide-based drug discovery.

To design, synthesize, and evaluate a series of thiosemicarbazone and thiazolidin-4-one hybrids bearing arylsulfonate groups as potential androgen receptor-targeted anticancer agents. The compounds were synthesized via sequential sulfonylation, thiosemicarbazone formation, and cyclization to thiazolidin-4-ones. The structures of the compounds were characterized using NMR (1H and 13C), FTIR, and HRMS spectroscopic techniques. In vitro cytotoxicity was assessed against prostate cancer (PC3) and human umbilical vein endothelial cell lines (HUVEC) using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Molecular docking and MM-GBSA calculations were performed to predict binding affinities toward the androgen receptor. Molecular dynamics simulations (250 ns) were conducted to evaluate the stability and dynamics of the ligand - protein complexes. Thiazolidin-4-one derivatives, particularly compound 9, exhibited potent cytotoxicity (IC50 = 6.35 µM) and high selectivity (SI = 6.05) over HUVEC cells. Docking and MM-GBSA analyses revealed strong interactions with key residues His-874, Met-742, Trp-741, and Arg-752. MD simulations confirmed minimal deviation from the docking pose (0.75 Å), low RMSD/RMSF values, and persistent hydrogen-bonding networks, supporting the structural stability and binding affinity observed in vitro. Structure-activity relationship (SAR) analysis indicated that scaffold cyclization and appropriate arylsulfonate substitution enhance receptor engagement and selectivity. The combined synthetic, computational, and biological results demonstrate that thiazolidin-4-one-based hybrids, particularly compound 9, are promising selective androgen receptor-targeted anticancer agents, warranting further optimization and development.

Type 2 diabetes is a prevalent disease that continues to pose a significant health burden worldwide. Despite the availability of various drugs for its management, the number of diagnoses and mortalities is persistently on the rise. Alpha-glucosidase inhibition has emerged as a promising therapeutic strategy to prevent postprandial hyperglycaemia. One approach in drug discovery is drug repurposing, which involves investigating existing drugs for new therapeutic indications. This study used a three-stage molecular docking approaches to screen the DrugBank database for potential alpha-glucosidase inhibitors against N-terminal maltase glucoamylase (ntMGAM) target. We selected 10 compounds with top docking performance, and rescoring these compounds with MMGBSA calculations produced arbekacin, neamine, and sisomicin with a binding free energy of - 72.13, - 55.14, and - 69.07kcal/mol, respectively, as the top three compounds. These compounds were subsequently analysed and compared with the standard drug, acarbose for their protein-binding stability using molecular dynamics simulation (MDS) approach. The MDS analysis suggests that sisomicin exhibited the most stable interactions and stronger post-MDS binding free energy with alpha-glucosidase. These findings suggest that sisomicin is a potential inhibitor of alpha-glucosidase, and a novel candidate for drug repurposing in antidiabetic therapy.

This study aimed to evaluate the α-glucosidase inhibitory potential of newly synthesized aurone derivatives (1-14) using an integrated experimental and computational strategy, with emphasis on their antidiabetic potential. The compounds were evaluated through in vitro α-glucosidase inhibition and enzyme kinetic assays, along with in vivo studies to assess postprandial glucose control. Molecular docking, MM-GBSA calculations, and molecular dynamics (MD) simulations were performed to analyze interactions with diabetic targets (PDB IDs: 5NN4 and 6KK1). Furthermore, in silico ADME profiling and density functional theory (DFT) analyses were conducted to predict pharmacokinetic properties, drug-likeness, and electronic behavior. Several aurone derivatives exhibited strong α-glucosidase inhibition, surpassing standard drugs. Kinetic studies revealed a competitive inhibition mechanism, and in vivo evaluations confirmed their glucose-lowering effects - the first such report for aurones. Computational analyses indicated stable enzyme - ligand complexes with favorable binding affinities and ADME features. DFT results supported the observed structure - activity relationships and highlighted key electronic attributes influencing activity. This comprehensive study identifies aurones as potent α-glucosidase inhibitors with significant therapeutic potential, providing a strong foundation for further development of aurone-based antidiabetic agents.

FYN, a member of the Src family kinases (SFKs) and a non-receptor tyrosine kinase, plays a critical role in signal transduction within the nervous system and is instrumental in the activation and development of T lymphocytes. While the biological significance of FYN kinase in various cellular processes is well recognized, its potential as a therapeutic target remains largely unexplored. In this study, we investigated the potential of natural products (NPs) as preferential inhibitors of FYN kinase. A library of over 3500 NPs was screened for binding affinity with FYN kinase (PDB: 2DQ7) using XGlide docking simulations. The fourteen NPs with the highest docking scores were selected for further analysis. Their interactions with FYN kinase were evaluated through MM-GBSA calculations, and ADMET profiling was performed using SwissADME and pkCSM tools to assess pharmacokinetic properties. Molecular dynamics (MD) simulations using Desmond further confirmed the stability of FYN-NP complexes in solvent environments. Of the top fourteen NPs, only oroxin A demonstrated favorable drug-like properties and sustained stable binding to FYN kinase, as evidenced by MD simulations. Moreover, in vitro kinase inhibition assays revealed that oroxin A exhibited dose-dependent inhibition of FYN kinase. Additionally, C. elegans viability assays confirmed its low toxicity. Moreover, cross-docking revealed that although oroxin A binds to multiple SFKs due to conserved ATP binding pocket, it displayed stronger binding toward FYN, suggesting binding preference over FYN. This study provides a comprehensive evaluation of NPs as potential FYN kinase inhibitors and identifies oroxin A as a natural compound with preliminary evidence of FYN inhibition, warranting further validation.

Reduced binding of Tau(210-240) to BIN1: Phosphate charges prefer n-Src/distal loops over RT-Src loops.

Alzheimer's disease (AD) is characterized by progressive cognitive decline and pathological accumulation of amyloid-beta (Aβ). Cathepsin B (CatB) has been implicated in both Aβ degradation and amyloidogenic APP processing; this compartment-dependent dualism makes CatB a complex but intriguing target, where selective inhibition of pathogenic activities (rather than global inhibition) is likely required for therapeutic benefit. In this research, we used an integrated computational pipeline to discover effective CatB inhibitors from a natural product-like compound library. A tiered virtual screening methodology (HTVS, SP, XP) was complemented by MMGBSA rescoring to yield F3382-3724, F6617-5583, and F6617-3074 as strong candidates. DFT B3LYP-D3/6-31G optimization confirmed F6617-5583 to possess the most stable electronic structure, followed by F3382-3724. Molecular dynamics simulations of 500ns indicated that all complexes exhibited protein RMSD values below 2.0Å, with F6617-5583 achieving conformational stability earlier, showing ligand RMSD values between 3.0-3.5Å similar to the reference inhibitor. MMGBSA calculations identified F6617-5583 as the most potent binder (ΔG_bind = - 74.92 ± 3.10kcal/mol), primarily stabilized by van der Waals and lipophilic interactions. Consistent interactions involving catalytic residues such as Trp30 and Trp221 facilitated stable ligand retention. PCA and Free Energy Landscape analyses further supported the localization of F6617-5583 in a low-energy conformational pocket indicative of strong and specific binding. A compound-gene interaction network constructed using NetworkX and Matplotlib revealed distinct connectivity patterns, providing insights into potential polypharmacological effects. Collectively, these results establish F6617-5583 as the lead CatB inhibitor, while F3382-3724 remains a promising secondary candidate for further optimization in Alzheimer's disease therapeutics.

Checkpoint kinase 1 (CHK1) plays a critical role in DNA damage response and cell cycle regulation, making it an attractive target for cancer therapy. However, clinical translation of CHK1 inhibitors has been limited by selectivity issues, dose-limiting toxicities, and drug resistance mechanisms, necessitating the development of novel inhibitors with improved therapeutic profiles. We developed an integrated computational-experimental pipeline for CHK1 inhibitor discovery. Starting with 492,534 compounds from the Specs database, we applied PAINS filtering, molecular fingerprinting (ECFP4), and dimensionality reduction (UMAP with K-means clustering). Structure-based virtual screening included e-pharmacophore modeling, molecular docking (Schrödinger's Glide), and 200-ns molecular dynamics simulations with MM-GBSA calculations. Lead compounds were evaluated for ADME properties and synthetic accessibility. The top candidate was validated in triple-negative breast cancer cell lines MDA-MB-231 and MDA-MB-468 using MTT assays. The pipeline identified 544 diverse compounds for analysis. Five compounds showed favorable CHK1 binding profiles. AO-022/43514723 emerged as the lead with a docking score of -9.205kcal/mol, forming stable interactions with hinge region residues GLU85 and CYS87. Molecular dynamics confirmed complex stability. Scaffold analysis revealed novel chemotype diversity distinct from existing clinical inhibitors. ADME profiling showed drug-like properties with acceptable synthetic accessibility (SA score = 2.93). In vitro validation demonstrated dose-dependent cytotoxicity with IC₅₀ values of 51.53μM (MDA-MB-231) and 64.02μM (MDA-MB-468), representing micromolar potency typical of early-stage computational hits requiring further optimization. This integrated approach successfully identified AO-022/43514723 as a structurally novel preliminary hit with favorable computational binding profiles and preliminary cellular activity. While direct CHK1 target engagement remains to be confirmed and potency optimization is required, this compound serves as a promising starting point for lead development. The workflow provides a generalizable framework for oncology drug discovery where conventional approaches face clinical challenges.

Endocrine disrupting chemicals (EDCs) have been shown to mediate metabolic disruptions in human cells and have been associated with severe adverse health effects. By antagonizing the hormones that act on nuclear hormone receptors, like the estrogen receptor α (ERα) and the androgen receptor (AR), these chemicals disrupt the regulation of various biochemical processes, thereby adversely affecting metabolic homeostasis. The expression of estrogen and androgen receptors in the liver and pancreas, which play an important role in lipid and glucose homeostasis regulation, has made them prime targets affected by EDCs. The different chemical structures of EDCs impose limitations on elucidating their binding mechanisms in nuclear receptors. In this context, in silico tools are able to highlight the potential interactions between the chemicals and the receptors. The aim of this study is to apply molecular simulation and experimental techniques to identify common patterns in the binding process of selected EDCs to ERα and AR and, thus, pinpoint key elements that could be characterized as molecular initiating events (MIE). MM-GBSA and alchemical relative binding free energy (RBFE) calculations have verified the trends observed in the experimental assays regarding the binding affinity of bisphenol compounds. The findings that confirm the agreement between computational and experimental methods offer a framework for future studies on the behavior of EDCs with other metabolically relevant receptors.

Background: TRPC6 is recognized as a therapeutically relevant cation channel, whose activation is governed by specific ligand–pocket interactions. Methods: An integrated in silico workflow was employed, comprising structure-based docking, 100-nanosecond molecular dynamics (MD) simulations, and MM-GBSA calculations. Benzoic-acid–based compounds were designed and prioritized for binding to the TRPC6 pocket, using a known literature agonist as a reference for benchmarking. Results: Within the compound series, BT11 was found to exhibit a representative interaction profile, characterized by a key hydrogen bond with Trp680 (~64% occupancy), persistent salt-bridge interactions with Lys676 and Lys698, and π–π stacking with Phe675 and Phe679. A favorable docking score (−11.45 kcal/mol) was obtained for BT11, along with a lower complex RMSD during MD simulations (0.6–4.8 Å), compared with the reference compound (0.8–7.2 Å). A reduction in solvent-accessible surface area (SASA) after ~60 ns was also observed, suggesting decreased water penetration. The most favorable binding energy was predicted for BT11 by MM-GBSA (−67.72 kcal/mol), while SOH95 also ranked highly and slightly outperformed the reference. Conclusions: These convergent computational analyses support the identification of benzoic-acid–derived chemotypes as potential TRPC6 ligands. Testable hypotheses are proposed, along with structure–activity relationship (SAR) guidelines, to inform experimental validation and guide the design of next-generation analogs.

The PB2 cap-binding domain (PB2cap) of the influenza virus is considered an important target for blocking viral transcription due to its cap binding. The lack of the complex structures of PB2cap with m7GDP limits the exploration of the binding differences between the PB2cap of influenza A and B viruses (FluA and FluB, respectively) with methylated cap analogs (m7GTP and m7GDP). In this study, based on the complex structures of FluA-D and FluB-D obtained using Discovery Studio 2.5 software and the crystal structures of FluA and FluB with m7GTP (FluA-T and FluB-T), we investigated the binding of FluA and FluB with m7GTP and m7GDP by molecular dynamics simulations and MM-GBSA calculations. The results show that m7GTP binding affinity is greater than that of m7GDP for FluA and FluB, with a more pronounced affinity for FluA than that for FluB. The differences in the properties of the key residues of FluA (F323, H357 and N429) and FluB (Q325, W359 and S431) and the structures of the methylated cap analogs may explain the differences in binding abilities. Besides, the sandwich structure, π-π stacking interactions, and the electrostatic interactions between PB2cap and methylated cap analogs are the key factors in stabilizing the positioning in the binding pockets. Our work could provide some valuable theoretical clues for the development of influenza virus PB2 inhibitors.

Background/Objectives: Hypertension is a global health challenge. Zhengan Xifeng Decoction (ZXD), a classical traditional Chinese medicine, has shown clinical efficacy against hypertension. This study aimed to identify the bioactive constituents of ZXD and elucidate its antihypertensive mechanisms by integrating plasma UPLC–MS (ultra-performance liquid chromatography–mass spectrometry) analysis, network pharmacology, and molecular dynamics (MD) simulations. Methods: ZXD constituents and plasma-absorbed compounds were characterized by UPLC–MS. Putative targets (TCMSP, SwissTargetPrediction) were cross-referenced with hypertension targets (GeneCards, OMIM) and analyzed in a STRING protein–protein interaction network (Cytoscape) to define hub targets, followed by GO/KEGG enrichment. Selected protein–ligand complexes underwent docking, Prime MM-GBSA calculation, and MD validation. Results: A total of 72 absorbed components were identified, including 14 prototype compounds and 58 metabolites. Network pharmacology identified ten key bioactive compounds (e.g., liquiritigenin, isoliquiritigenin, and caffeic acid), 149 hypertension-related targets, and ten core targets such as SRC, PIK3CA, PIK3CB, EGFR, and IGF1R. Functional enrichment implicated cardiovascular, metabolic, and stress-response pathways in the antihypertensive effects of ZXD. Molecular docking demonstrated strong interactions between key compounds, including liquiritigenin, caffeic acid, and isoliquiritigenin, and core targets, supported by the MM-GBSA binding free energy estimation. Subsequent MD simulations confirmed the docking poses and validated the stability of the protein–ligand complexes over time. Conclusions: These findings provide mechanistic insights into the multi-component, multi-target, and multi-pathway therapeutic effects of ZXD, offering a scientific basis for its clinical use and potential guidance for future drug development in hypertension management.

The WHO declared monkeypox a global health emergency due to its rapid spread. In response, the FDA authorized emergency use of the Jynneos vaccine despite its adverse effects, while smallpox antivirals, repurposed for monkeypox treatment, have shown limited efficacy, highlighting the need for better therapeutics that are biocompatible, less toxic, and more accessible. Tea bioactives, known for their antiviral properties, were evaluated using an in silico approach to target viral enzymes: polymerase holoenzyme and methyltransferase. A total of 68 bioactives, mainly polyphenols from tea, were analyzed through molecular docking. Among them, digalloylprocyanidin B2, TSB, and NTF showed the lowest binding energies of -9.6441 kcal mol−1, -9.1740, kcal mol−1, and − 9.1563 kcal mol−1, respectively against the polymerase holoenzyme, while TSA, TF, and TF3 exhibited the binding energies of -10.2649 kcal mol−1, -9.5998 kcal mol−1, and − 9.0857 kcal mol−1, respectively for methyltransferase. The compounds showed stronger binding than reference drugs. MDS (100 ns) using Desmond software showed that top-ranked ligand complexes were more stable than unbound proteins and reference drug complexes. MM-GBSA calculations revealed greater stability with the polymerase holoenzyme than methyltransferase. Further in vitro and in vivo studies are needed to confirm their inhibitory effects.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-14583-y.

Multi-computational screening identifies homovanillic acid as a potential SAP5 inhibitor against Candida albicans biofilms.

Background: Human papillomavirus type 16 (HPV16) E6 oncoprotein is a key factor in the progression of cervical and other HPV-related cancers. Targeting E6 with small molecule inhibitors represents a promising strategy for the development of novel antiviral therapies.Objectives: This study aimed to discover and characterize small-molecule compounds that exhibit high affinity for HPV16 E6, possess favorable drug-like properties, and inhibit HPV16 E6, using advanced computational approaches.Materials and Methods: We integrated molecular dynamics simulations to capture the conformational flexibility of HPV16 E6 and employed structure-based virtual screening to identify potential inhibitors from a large chemical library. The binding stability and interaction patterns of selected compounds were evaluated through molecular docking, binding free energy calculations, and extended molecular dynamics simulations. In silico ADMET profiling was performed to assess the pharmacokinetic and toxicity properties of the top candidates.Results: Nine lead compounds demonstrated stable binding to a key functional residue (CYS51) of HPV16 E6, with strong theoretical binding affinities confirmed by MM-GBSA calculations and molecular dynamics analysis. ADMET predictions indicated that most candidates possessed favorable pharmacokinetic profiles, although two compounds showed potential toxicity concerns.Conclusion: Our findings provide a robust computational framework for the identification of drug-like small molecules targeting HPV16 E6, offering promising candidates for further development as antiviral agents against HPV-associated diseases. Experimental validation is warranted to confirm the inhibitory activity and therapeutic potential of these compounds.

Targeting norovirus RdRp: A computational study on the inhibitory potential of ursolic acid and apigenin-7-O-glucoside

Dengue, spread by Aedes aegypti and Aedes albopictus, causes 390 million infections, 50 million illnesses, and 24,000 fatalities, including over 4.5 million in 2023. This work finds DENV NS1 protein anti-virals beyond CYD-TDV using in silico approaches. Virtual screening and molecular docking were used to evaluate binding affinities, followed by toxicity profiling to assess pharmacokinetics and safety. Molecular dynamics simulations (200 ns) and MM-GBSA calculations measured the stability and binding strength of the protein-ligand complexes. Additionally, HOMO-LUMO analysis was performed to predict electronic properties and chemical reactivity. Based on natural availability and clinical relevance, 1,191 seaweed metabolite compounds were evaluated for therapeutic application. Due to their strong binding affinities (−5.567, −4.776, and − 4.550 kcal/mol), excellent ADME profiles, and low toxicity, CIDs 359, 8768, and 11,500,585 were screened out. Molecular docking showed hydrophobic interactions with ILE93 and ILE218, suggesting a pocket-wide active site for each ligand. After docking, MM-GBSA demonstrated negative binding free energies, HOMO-LUMO gaps, RMSD, RMSF, Rg, SASA, and hydrogen bonds were measured in MD simulations to confirm the protein-ligand complex’s stability. CID 11,500,585 excelled in cumulative protein RMSD, RMSF, and SASA. After the simulation, MM-GBSA analysis confirmed their stability, with CID 11,500,585 (3,4-dibromo-5-(2-hydroxyethyl) benzene-1,2-diol) from Rhodomela confervoides seaweed having the lowest value of -25.18 kcal/mol at 200 ns. It may suppress DENV proliferation. QSAR study suggested that this chemical is anti-viral, although in vivo and in vitro testing is needed.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-15030-8.

Pancreatic cancer (PC) remains one of the deadliest cancer types, with limited success in treatment despite advances in research. MAP4K4 is overexpressed in pancreatic tumors and linked to disease progression, making it a promising target for PC therapy. This study aimed to identify bioactive nutraceutical molecules targeting MAP4K4 using molecular docking, molecular dynamics (MD) simulations, and MM-GBSA calculations. The computational findings were validated through in vitro MTT cell viability assays and MAP4K4 enzyme ELISA tests. Queuine and Thiamine were identified as potent MAP4K4 inhibitors with comparable docking scores to the approved drug Gemcitabine. MD simulations confirmed stable binding for 100 ns (3 runs), with average binding free energy values of -50 kcal/mol for Queuine, -47 kcal/mol for Thiamine, and − 18 kcal/mol for Gemcitabine. In vitro assays showed that Thiamine was non-cytotoxic at high concentrations, while Queuine had a significantly lower IC50 (5.95 µM) compared to Gemcitabine (64.17 µM), making it nearly ten times more potent. MAP4K4 ELISA tests confirmed Queuine’s superior binding and enzyme inhibition compared to Gemcitabine. Synergy studies combining Queuine (0.25–1.25 µM) and Gemcitabine (0.05–2.5 µM) revealed strong synergistic effects, suggesting enhanced efficacy at lower doses. These findings highlight Queuine as a promising natural therapeutic agent for PC, with potential for combination therapy with Gemcitabine. Further in vivo studies are recommended to explore its therapeutic potential.

Harnessing computational tools for drug discovery: An integrated computational approach to identify potential BACE-1 inhibitors.