Issue #115: Integrative structural and physicochemical characterization of chalcone synthase enzymes from medicinal plants using AlphaFold, molecular docking, and molecular dynamics.

Signal of the Day

Integrative structural and physicochemical characterization of chalcone synthase enzymes from medicinal plants using AlphaFold, molecular docking, and molecular dynamics.

Chalcone synthase (CHS) is the entry-point enzyme of the flavonoid biosynthetic pathway, catalyzing the first committed step toward the production of diverse bioactive metabolites with antioxidant, anti-inflammatory, and anticancer properties. Here, we conducted a comparative in silico characterization of CHS from 13 medicinal plants, with Arabidopsis thaliana included as reference species. Protein sequences retrieved from UniProtKB were aligned using ClustalW, revealing strong conservation of key motifs, particularly the catalytic triad (Cys-His-Asn), GFGPG motif, and catalytic loop. Physicochemical profiling indicated interspecies variability in predicted protein stability, hydrophobicity, and thermostability, reflecting structural adaptation rather than direct functional divergence. AlphaFold-predicted structures consistently adopted the conserved thiolase-like αβαβα-fold characteristic of type III polyketide synthases, while exhibiting species-specific variations in the substrate-binding channel architecture. These variations are interpreted as structural features that may influence substrate accommodation and selectivity. To assess functional relevance, molecular docking with p-coumaroyl-CoA further confirmed stable substrate placement within the conserved catalytic pocket across species. Furthermore, 100-ns molecular dynamics simulations of representative crystal-derived and AlphaFold-predicted CHS-ligand complexes confirmed conformational stability, which was supported by MM-PBSA calculations revealing favorable binding energetics dominated by van der Waals interactions. Collectively, this study integrates sequence, structural, and dynamic analyses to establish a computational framework for comparative CHS characterization in medicinal plants. While the findings are derived exclusively from in silico approaches, they provide structurally grounded hypotheses that may guide future experimental validation, enzyme engineering, and pathway-oriented exploration of flavonoid biosynthesis.

Why this matters: Provides actionable mutations to enhance catalytic efficiency or thermostability.

Also Worth Reading

Molecular Modeling of Protein-Peptide Complexes Mimicking Factor Xa-Prothrombin Using AlphaFold-Multimer and Molecular Dynamics Simulations for Functional Prediction.

Accurately predicting how point mutations influence protease activity is a major challenge in protein engineering and in the study of coagulation disorders. Factor Xa (FXa) catalyzes the proteolytic activation of prothrombin, a critical step in thrombin generation, yet the molecular details of direct enzyme-substrate recognition and the impact of pathogenic variants remain incompletely defined. Here, we combined AlphaFold-Multimer modeling with explicit-solvent molecular dynamics (MD) simulations to investigate simplified FXa-substrate interactions using prothrombin-derived peptides encompassing the Arg271 and Arg320 cleavage sites in the absence of the full prothrombinase complex. AlphaFold predictions identified catalytically competent peptide orientations, while subsequent MD simulations and free energy analyses identified key contributions of the P1 and P4 cleavage site residues to FXa binding. Distinct stability and affinity differences between the two cleavage sites were highlighted. Active site variants associated with factor X deficiency demonstrated variant-specific disruptions in peptide engagement, implicating key residues within the FXa active site as critical determinants of catalytic activity. Experimental validation with recombinant FXa variants was consistent with the computational predictions, indicating comparable inhibition by the prothrombin peptides. Together, these findings establish an integrative computational-experimental framework for probing local protease-substrate recognition, rationalizing the effects of disease-causing mutations, and guiding the design of therapeutic protease variants.

Exploring the mechanism of saffron in treating viral myocarditis using network pharmacology and molecular docking.

Viral myocarditis (VM) is a cardiovascular disorder that can lead to heart failure and cardiogenic shock. Saffron, a traditional Chinese medicinal herb, has shown therapeutic potential against VM in numerous studies. However, the mechanisms through which saffron exerts its effects on VM remain poorly understood. Thus, this study aimed to elucidate the active compounds, molecular targets, and signaling pathways involved in saffron’s therapeutic action against VM by employing network pharmacology and molecular docking approaches. The active compounds and corresponding targets of saffron were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. VM-associated targets were sourced from the GeneCards database. Overlapping targets between saffron and VM were then identified. Protein-protein interaction networks were established and analyzed utilizing the STRING platform and Cytoscape software to determine core targets. Furthermore, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were carried out utilizing Bioconductor in R to explore the potential biological activities and signaling pathways through which saffron may act against VM. Finally, molecular docking and model visualization were carried out using AutoDock Tools and PyMOL open-source software. From the database, we identified 4 active compounds in saffron with potential effects against VM: crocetin, isorhamnetin, kaempferol, and quercetin. A total of 60 corresponding targets were observed, with TNF, IL-6, IL-1β, CXCL8, and JUN emerging as core targets. Kyoto encyclopedia of genes and genomes enrichment analysis revealed 155 regulatory signaling pathways, among which the TNF, AGE-RAGE, and IL-17 signaling pathways, lipid metabolism, and atherosclerosis were the most prominent. Molecular docking results indicated that quercetin showed the strongest binding affinity toward IL-1β and CXCL8. The therapeutic effect of saffron against VM is not driven by a single factor, but rather involves multiple active compounds, targets, and signaling pathways.

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.

Research & AI Updates

• Gemini for Science: AI experiments and tools for a new era of discovery - blog.google — Gemini for Science: AI experiments and tools for a new era of discovery    blog.google.

From the Industry

• Layoff Tracker: AbbVie, Novartis slash US headcount - BioSpace — Layoff Tracker: AbbVie, Novartis slash US headcount    BioSpace.
• TaiMed Biologics Completes Phase 2b Enrollment for TMB-365/380 HIV Therapy - The Clinical Trial Vanguard — TaiMed Biologics Completes Phase 2b Enrollment for TMB-365/380 HIV Therapy    The Clinical Trial Vanguard.
• TaiMed Biologics Completes Phase 2b Enrollment for TMB-365/380 in HIV Maintenance Therapy Study - GlobeNewswire — TaiMed Biologics Completes Phase 2b Enrollment for TMB-365/380 in HIV Maintenance Therapy Study    GlobeNewswire.
• Experts on Treatment of Coexisting AxSpA, IBD Weigh In on NSAIDs, Biologics, Drug Combinations - Medscape — Experts on Treatment of Coexisting AxSpA, IBD Weigh In on NSAIDs, Biologics, Drug Combinations    Medscape.
• Incyte and Genesis expand molecular AI collaboration - The Pharma Letter — Incyte and Genesis expand molecular AI collaboration    The Pharma Letter.
• After raising $800M, Parabilis seeks an IPO to pursue ‘undruggable’ targets - BioPharma Dive — After raising $800M, Parabilis seeks an IPO to pursue ‘undruggable’ targets    BioPharma Dive.
• PharmAla Biotech Signs Term Sheet for $100 Million U.S. Licensing Deal for ALA-002 MDMA Therapy (MDXXF) - Yahoo Finance — PharmAla Biotech Signs Term Sheet for $100 Million U.S.

Quick Reads

Multi-omics investigation of benzo[a]pyrene in gastric cancer: comprehensive network toxicology, machine learning and molecular docking approaches.

Gastric cancer (GC) risk is shaped by environmental exposures such as benzo[a]pyrene (BaP). Read more →

In silico analysis of <i>Anacardium occidentale</i> phytochemicals: pharmacokinetics, molecular docking, and dynamics of <i>Cryptococcus neoformans</i> enzymes.

This study evaluated in silico the antifungal potential of phytochemicals from the leaves of Anacardium occidentale (cashew tree) against key enzymatic targets: farnesyltransferase (CnFTase), beta-carbonic anhydrase (β-CA), and adenylosuccinate synthetase (AdSS) from Cryptococcus neoformans . Read more →

Diethyl Phthalate (DEP) as a potential osteosarcoma risk factor: a multi-omics study integrating network Toxicology, single-cell RNA sequencing, and molecular docking.

Diethyl phthalate (DEP), a common plasticiser and endocrine disruptor, has been linked to cancer, but its role in osteosarcoma (OS) remains unclear. Read more →

Exploring the mechanism of stigmasterol against androgenetic alopecia using geometry optimization, network pharmacology, molecular docking, and molecular dynamics studies.

Androgenetic alopecia (AA) is a common condition that is characterized by androgen-induced follicular miniaturization and abnormal hair cycling, against which there are as yet no effective therapeutic interventions. Read more →

Investigating the mechanistic link between pesticide DDT and breast cancer through network toxicology, molecular docking, and molecular dynamics simulation.

To elucidate the molecular mechanisms by which the pesticide Dichlorodiphenyltrichloroethane (DDT) may contribute to breast cancer pathogenesis, focusing on its interactions with key cancer-related molecular pathways. Read more →

Computational exploration of Aegle marmelos coumarins: DFT, molecular docking, and dynamics studies for anti-hypertensive activity.

Literature reviews indicate that Aegle marmelos exhibits significant anti-hypertensive activity. Read more →

Exploring the renoprotective potential of Beta vulgaris in diabetic nephropathy: an integrated network pharmacology, molecular docking and dynamics simulation study.

Diabetic Nephropathy (DN) is a leading cause of end-stage renal failure globally. Read more →

Computational insights into pyridoxal 5-phosphate for cataract therapy: targeting TNF-α, IL-6, and IL-1β through network pharmacology, molecular docking, and dynamics approaches.

This study computationally investigated the effect of pyridoxal 5-phosphate (PLP) interacts with key inflammatory cytokines such as TNF-α, IL-6, and IL-1β implicated in cataract, using network pharmacology, molecular docking, and molecular dynamics simulation. Read more →

Pipeline Tip

Use local MSA generation (colabfold_search) to bypass speed bottlenecks.

Resources & Tools

• Dataset: AlphaFold Structure Database - 200M+ predicted structures from DeepMind/EMBL-EBI.
• Dataset: Uniprot Knowledgebase - The world’s most comprehensive resource for protein sequence and annotation.
• Tool: ChimeraX - Next-gen molecular visualization for large data sets. View all tools →
• Tool: AlphaFold2 - Deep learning system for high-accuracy protein structure prediction. View all tools →
• Event: Structural Biology Events (Open)
• Event: Protein Design Hub (LinkedIn Group) (Ongoing)
• Job: Share Advert | Research Assistant (Bioinformatics/Statistics) - Jobs.ac.uk at Jobs.ac.uk
• Job: Share Advert | Research Associate in Bioinformatics and Genetics - Jobs.ac.uk at Jobs.ac.uk

Deep learning is not a magic wand, but a powerful lens for structural biology. — Recep Adiyaman