Recep Adiyaman
bioinformatics

Issue #28: Predicting the Mechanism of Action of Bawei Chufan Soup in Treating Teen Depression through Network Pharmacology, Molecular Docking and Molecular Dynamics Simulation.

January 22, 2026 Daily Intelligence
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Predicting the Mechanism of Action of Bawei Chufan Soup in Treating Teen Depression through Network Pharmacology, Molecular Docking and Molecular Dynamics Simulation.

🧬 Abstract

Introduction The Bawei Chufan Soup (BWCFS) in Traditional Chinese Medicine (TCM) offers unique advantages in treating Teen Depression (TD). This study utilizes network pharmacology, molecular docking, and molecular dynamics simulations to predict the material basis and mechanism of action of the decoction. Methods The TCMSP, SwissADME, and SwissTargetPrediction databases were utilized to obtain the active ingredients and targets of the BWCFS. The GeneCards, OMIM, and Disgenet databases were used to identify disease targets, and the intersection of these sets was determined using the VENNY tool. The intersecting targets were imported into the String database for protein- protein interaction analysis and the screening of core targets. GO and KEGG enrichment analyses of the intersecting targets were conducted using the David database, and drugcomponent- target-pathway network diagrams were constructed using Cytoscape 3.10.0 software. The molecular docking models of the core components and key targets were generated using AutoDock Vina, and kinetic simulations were conducted using GROMACS 2020.3, paired with the best docking models. Results After screening, the study identified the core components of BWCFS as Baicalein, Kaempferol, Quercetin, Cerevisterol, and Cavidine, with the key targets for TD being AKT1, IL6, TNF, ESR1, and IL1B. GO enrichment analysis revealed that BWCFS may affect signal transduction in the treatment of TD, and is associated with cellular components such as the plasma membrane and dendrites, as well as the regulation of protein binding. KEGG analysis suggested that the intersecting genes are primarily enriched in the cyclic adenosine monophosphate (cAMP) signaling pathway. Molecular docking results indicated that AKT1 shows good binding affinity with Baicalein, Cavidine, Kaempferol, and Quercetin, while Cerevisterol exhibits strong binding with TNF. The molecular dynamics simulations were stable and reliable. During the protein-ligand complex simulation, the binding between the protein and ligand was stable, with van der Waals interactions as the primary force, while hydrogen bonds were present between both the protein and ligand. Discussion Though this study has several common limitations associated with network pharmacology, and no animal experiments have been conducted for verification, the study has successfully explored and validated the mechanism of action of BWCFS in treating TD using scientific computational methods. This study provides new perspectives and methods for the development and management of pharmacological treatments for TD, offering innovative insights into TCM approaches for its treatment. Conclusion Through network pharmacology, this study preliminarily predicted the material basis and mechanism of action of BWCFS in treating TD. Furthermore, the therapeutic effects of BWCFS on TD may be associated with neuroinflammation and structural and functional changes in neuronal dendrites. The cAMP-PKA-NF-κB and cAMP-PI3K-AKT-NF-κB pathways are proposed as potential therapeutic targets.

Why it matters: Enhances small-molecule or peptide docking accuracy for targeted drug discovery.

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In Silico Investigation Reveals <i>IL-6</i> as a Key Target of Asiatic Acid in Osteoporosis: Insights from Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Background/objectives Osteoporosis is a multifactorial skeletal disorder in which chronic inflammation, dysregulated cytokine signaling, and metabolic imbalance contribute to excessive bone resorption and impaired bone formation. Asiatic acid has demonstrated bone-protective effects, but its molecular mechanisms in osteoporosis remain incompletely understood. This study aimed to investigate the anti-osteoporotic mechanisms of asiatic acid using an integrative in silico strategy. Methods Network pharmacology analysis was performed to identify osteoporosis-related molecular targets of asiatic acid. Molecular docking was used to predict the binding modes and affinities between asiatic acid and its target proteins. Molecular dynamics simulation was used to assess the structural stability and interaction persistence of the asiatic acid-protein complex. Results Network pharmacology identified 135 overlapping targets between asiatic acid and osteoporosis, with IL-6 , STAT3 , PPARG , and NFKB1 emerging as key hubs. KEGG analysis indicated the PPAR signaling pathway as a potential mechanism underlying the anti-osteoporotic effect. Molecular docking showed strong binding energies of asiatic acid with all predicted target proteins, with the highest affinity observed for IL-6 , involving key residues ASN61, LEU62, GLU172, LYS66, and ARG168. Consistently, molecular dynamics simulation confirmed stable binding of asiatic acid to IL-6 , with persistent interactions with ASN61, LYS66, LEU62, LEU64, and GLN154 mediated by hydrogen bonds, water bridges, and hydrophobic interactions. Conclusions This integrative in silico study provides mechanistic insight into the potential anti-osteoporotic actions of asiatic acid, implicating IL-6 as a plausible upstream molecular target. These results establish a robust mechanistic framework for future translational studies exploring asiatic acid as a natural therapeutic candidate for osteoporosis.

Exploring the mechanism of Kemofang in treating idiopathic membranous nephropathy based on LC-MS/MS combined with network pharmacology, molecular docking, and molecular dynamics simulation.

Idiopathic membranous nephropathy (IMN), an autoimmune glomerular disease, arises from in situ immune complex deposition in the glomerular subepithelial spaces, triggering complement activation and podocyte injury. Although the Kemo Formula shows therapeutic potential for IMN, its mechanisms remain unclear. This study employed LC-MS/MS, network pharmacology, molecular docking, and dynamic simulations to elucidate the mechanism of action. LC-MS/MS and the TCMSP database identified 83 bioactive components from 267 chemicals detected in the Kemo Formula. Using PubChem, Swiss Target Prediction, and GeneCards, 827 drug targets and 2581 IMN-related targets were screened, yielding 336 overlapping targets linked to 81 components. Network analysis prioritized 15 key components ( baicalein and quercetin) and 36 core targets (TP53, IL6, and AKT1). Functional enrichment revealed involvement in hormone response, MAPK cascade regulation, and kinase binding with pathways including lipid metabolism, PI3K/Akt, and MAPK signaling. Molecular docking indicated strong binding affinities between the active components and targets, while dynamic simulations predicted the stability of the galangin-AKT1 complex. The Kemo Formula likely mitigates IMN by multi-target modulation, ameliorating lipid dysregulation, suppressing podocyte apoptosis, and attenuating immune-inflammatory and oxidative stress via PI3K/Akt and MAPK pathways. This integrative approach highlights its multicomponent, multitarget therapeutic strategy against IMN, providing a foundation for further mechanistic and clinical exploration.

Discovery of ActRIIB antagonistic peptides from in vitro-digested chicken breast meat via an integrated Peptidomics and molecular docking approach.

Sarcopenia and obesity are major global health challenges. This study investigated peptides from chicken breast meat via in vitro digestion as potent ActRIIB antagonists to promote myogenesis. The intestinal-phase digest collected at 120 min showed the highest degree of hydrolysis (65.99 % ± 4.00 %) and enhanced C2C12 proliferation (128.15 % ± 9.90 %). Peptidomics identified peptides mainly from myofibrillar proteins and metabolic enzymes. Molecular docking revealed key hydrogen-bonding residues, including Glu 95 , Pro 117 , Glu 94 , Thr 93 , Asn 96 (Chain A), Ser 97 (Chain L), and Ser 59 (Chain H). Surface plasmon resonance showed that KEKLHVYKHIEK, EIKKEEKKEER, and DLENDKQQLDEK exhibited strong ActRIIB-binding affinity (K D : 0.514, 0.813, 1.91 μM). These peptides enhanced cell proliferation, inhibited myostatin signaling by reducing Smad2/3 phosphorylation, and upregulated MyoD expression. Molecular dynamics simulations (100 ns) indicated that DLENDKQQLDEK-ActRIIB and EIKKEEKKEER-ActRIIB complexes maintained a stable average number of 6 and 10 hydrogen bonds, respectively. Chicken breast-derived peptides thus represent promising functional food ingredients for combating muscle-wasting disorders.

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The multi-target mechanisms of β-sitosterol in Alzheimer’s disease: Integrative evidence from network pharmacology, molecular docking, and mendelian randomization.

β-Sitosterol, a widely distributed phytosterol, has shown therapeutic potential against Alzheimer’s disease (AD); however, its system-level mechanisms remain unclear. This study aimed to generate testable hypotheses regarding β-sitosterol activity in AD using an integrative computational framework. Potential targets were predicted using SwissTargetPrediction and were intersected with AD-related genes. Core targets were identified via protein-protein interaction network analysis, followed by pathway enrichment and validation using Gene Expression Omnibus transcriptomic datasets. Binding interactions were evaluated using molecular docking and 100-ns molecular dynamics (MD) simulations. Mendelian randomization (MR) was used to assess the causal association between circulating estradiol levels (proxy for aromatase activity) and AD risk. Nineteen potential targets were identified, with core genes (e.g., CYP19A1, ESR1, and NR3C1) significantly enriched in steroid hormone biosynthesis pathways. Β-Sitosterol exhibited strong binding affinities to CYP19A1 (-9.7 kcal/mol) and ESR1 (-8.2 kcal/mol), and MD simulations confirmed β-sitosterol-CYP19A1 complex stability. Differential expression analysis validated the dysregulation of key targets in AD. MR analysis further indicated that genetically predicted higher estradiol levels were significantly associated with reduced AD risk (IVW: β = -11.02, SE = 2.77, p = 6.78 × 10⁻⁵). This study provides predictive evidence that β-sitosterol may influence AD pathology by modulating steroidogenic enzymes and hormone signaling. However, as all findings were computationally derived and estradiol serves only as an indirect proxy for aromatase activity, experimental validation is required to confirm these proposed mechanisms. Our results offer a hypothesis-generating framework for further investigation of β-sitosterol as a multitarget candidate for AD.

Deciphering bisphenol A (BPA)-elicited osteoarthritis mechanisms through network toxicology and molecular docking, then de novo generation of novel therapeutic candidates.

Objective Bisphenol A (BPA), a pervasive environmental pollutant, is increasingly associated with osteoarthritis (OA) development, yet its molecular mechanisms remain unknown. Currently, there is no definitive cure for OA. Methods BPA targets were predicted using STITCH and Swiss Target Prediction, while OA-related targets were collected from GeneCards, OMIM, and the Therapeutic Target Database (TTD). Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to identify hub targets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed, and molecular docking with AutoDock evaluated BPA-core target interactions. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) platform for de novo drug prediction. Results Systematic bioinformatics analysis identified 26 candidate targets, with ESR1, PTGS2, CCL2, FLNA, and TRPV1 as key hubs. Pathway analysis revealed involvement in calcium ion transport, muscle contraction, IL-17 signaling, and estrogen signaling. Molecular docking confirmed strong BPA-target binding affinities. CANDO predicted 14 potential OA treatments, including glucosamine, ibuprofen, celecoxib, indomethacin, palmitic acid, and linoleic acid. Notably, qRT-PCR validation revealed that ESR1, PTGS2, CCL2, and TRPV1 were highly expressed, whereas FLNA was expressed at lower levels in the osteoarthritis blood samples. Conclusions This study elucidates BPA’s molecular mechanisms in OA and identifies promising therapeutic candidates. The integration of network toxicology, molecular docking, and computational drug discovery provides a robust framework for understanding environmental toxicants and advancing OA therapies.

Protein folding stability estimation with explicit consideration of unfolded states.

Folding stability is crucial for the vast majority of proteins. Computational methods suggested to date for the absolute folding stability (ΔG) prediction, including those driven from protein structure prediction AIs, show clear limitations in reproducing quantitative experimental values. Here we present IFUM, a deep neural network that jointly estimates ΔG and the equilibrium ensemble of folded and unfolded states represented by residue-pair distance probability distributions. This joint learning considerably enhances prediction accuracy compared to learning ΔG alone. Trained on a dataset including Mega-scale small proteins, disordered proteins, and wild-type natural proteins, IFUM is robust to various protein types and can accurately predict complex mutational effects like insertions or deletions. Here, we show that IFUM effectively guides real-world design challenges, exhibiting strong correlation with experimental melting temperatures in protein engineering and outperforming AlphaFold-based metrics in de novo design selection.

Assessment of antimicrobial activity by LC-HRMS profiling and Molecular Docking of Bioactive Compounds from Dytiscus marginalis, an aquatic coleopteran

Abstract Background The rapid rise in antibiotic resistance highlights the need for new antimicrobial agents. Dytiscus marginalis , an aquatic insect consumed in Northeast India, was evaluated for antimicrobial activity. Extracts from five solvents were tested against Pseudomonas aeruginosa, Proteus mirabilis, Enterobacter aerogenes, and Escherichia coli using the disc diffusion method. The methanol extract was further analysed by LC–HRMS, followed by molecular docking against LasR (PDB ID: 2UV0) and Swiss ADME screening for binding affinity, pharmacokinetics and drug-likeness. Results Acidified extracts prepared with polar solvents exhibited strong inhibitory activity against all tested bacterial strains. LC-HRMS profiling revealed 180 bioactive compounds in the methanol extract. Molecular docking demonstrated binding affinities ranging from –3.0 to –10.0 kcal/mol indicating notable interactions between the identified compounds and LasR. Swiss ADME analysis further supported the therapeutic relevance of several compounds. Conclusion The study highlights Dytiscus marginalis as a promising natural source of bioactive molecules with significant antimicrobial potential. These findings justify further investigation to isolate, purify and validate specific compounds for future drug development.

Isovanillin-derived bis-hydrazones as dual cholinesterase and carbonic anhydrase inhibitors: synthesis, enzymatic profiling, and computational insights from molecular docking and dynamics.

Aims To develop isovanillin-based bis-hydrazones as multitarget inhibitors of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and human carbonic anhydrase I/II ( h CA I/II). Materials & methods Twelve bis-hydrazones ( 4a-4l ) were synthesized in two steps and evaluated by spectrophotometric enzyme assays, Lineweaver-Burk kinetics, molecular docking, MM-GBSA, molecular dynamics simulations, and in silico ADME/Tox profiling. Results All compounds showed nanomolar inhibition. Compound 4d was the most potent AChE/BChE inhibitor ( K I = 10.46 and 3.56 nM), while 4a and 4j led the h CA I/II panel ( K I = 3.46 and 16.12 nM). Docking, MM-GBSA, and molecular dynamics supported dual-site cholinesterase engagement and non-zinc, peripherally anchored h CA inhibition. Conclusions Isovanillin-based bis-hydrazones, particularly 4d, 4a , and 4j , represent promising multitarget leads for cholinergic and h CA-linked disorders.

Targeted anticancer potential of oxazole derivative against breast cancer: Synthesis, molecular docking, dynamics simulation, and in vitro evaluation on ERBB3 receptor.

The study investigates 5- ((2-nitrobenzylidene) amino 2-phenyloxazole-4-carbonitrile (PS13), a derivative of the oxazole that was designed to block the ERBB3 receptor that plays a role in breast cancer development. The syntheses of PS13 were performed in two steps due to condensation and its structure was verified with the help of IR NMR, MS, and elemental analysis. Strong binding affinity was observed between the molecules and ERBB3 with the docking score of -9.5 kcal/mol that was reinforced by the presence of key hydrogen and hydrophobic bonds. Simulation of molecular dynamics above 500 ns showed that the formation of the ligand-receptor complex was stable, and the fluctuations of RMSD were minimal, which proves the structural compatibility of the molecules and the stability of their interaction. The ADMET profiling predicted good drug-like, gastrointestinal absorption, non-P-gp substrate, and good metabolism. The analysis of density functional theory indicated that the HOMO-LUMO energy gap is -2.27 eV, which indicated the stability of the electronics, and the ability to be reactive. The PS13-SLNs that were developed were PS13-loaded solid lipid nanoparticles that had high encapsulation efficiency (81 +/- 2.16 %), and enhanced release profiles in both the acidic and neutral pH conditions. Both in vitro MTT assays of MCF-7 cells and morphological changes depicted the dose-dependent cytotoxicity with 60.27 ± 0.04 µg/mL of IC 50 , and morphological changes that were consonant to apoptosis. Drug release kinetics indicated a first-order mechanism and Fickian diffusion, suggesting a controlled release profile. All these combined with the high ERBB3 binding affinity, good pharmacokinetics, stable SLN formulation, and in vitro anticancer efficacy of PS13, indicate that PS13 is a promising lead candidate to advance in preclinical development in the treatment of breast cancer.

Design, Synthesis, Molecular Docking, Dynamics Simulation, and Biological Evaluation of Novel Thiazolidinedione Derivatives Against Breast Cancer with Apoptosis-Inducing Activity.

Breast cancer remains one of the leading causes of cancer-related deaths among women worldwide. The chemotherapeutic drugs used in treatment often have serious side effects. In light of their anticancer potential, thiazolidinedione (TZD) derivatives are considered to be promising candidates for the development of novel antitumor agents. The objective of this study is to synthesize and produce two sets of TZD derivatives by combining the structural features of microtubule-targeting drugs used in breast cancer treatment, and to determine their molecular docking, molecular dynamics simulations, ADMET profile, antiproliferative, and apoptotic effect potential. In the present study, PZ-11 was determined by xCELLigence analysis to have the highest antiproliferative potential among all compounds tested on MCF-7 breast cancer cells. The cytotoxic activity of the synthesized compounds was evaluated against MCF-7 breast cancer cells, revealing IC 50 values of 29.44 μM for PZ-9 and 17.35 μM for PZ-11, compared to 6.45 μM for the reference drug vincristine. Analysis of the gene expression of the PZ-11 compound, which has a stronger cytotoxic effect potential, showed that PZ-11 significantly downregulates AIFM1, BAG3 , and BIRC3 , while upregulating pro-apoptotic genes such as BAD, HRK, CASP10 , and CASP14 . PZ-11’s binding affinities were screened using a molecular docking workflow via KNIME. The robust and persistent interactions between PZ-11 and AIF were substantiated by molecular dynamics simulation. It is demonstrated by ADMET predictions that PZ compounds possess suitable pharmacokinetic properties. PZ-11 is a promising TZD-based anticancer drug candidate against breast cancer cells, as determined by computational and experimental analysis. However, further validation is required through in vivo analysis to support these findings.

Two cases of TBL1XR1 heterozygous variants in children: a new splicing site variant identification and functional analysis through molecular docking and molecular dynamics simulation.

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The protein structure is the language of life; design is its poetry. — Recep Adiyaman

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