Post by Sahana P

Over the past few weeks, I've been exploring how computational biology can be used to investigate potential therapeutic compounds for complex diseases. As a learning project, I worked on an end-to-end Network Pharmacology and Molecular Docking study to explore the interaction of Quercetin, a naturally occurring flavonoid, with ENPP1, a protein associated with insulin resistance in Type 2 Diabetes Mellitus (T2DM). Rather than starting directly with molecular docking, I wanted to understand the complete workflow behind computational target identification. The project involved connecting information from multiple biological databases and tools to narrow down a biologically relevant target before evaluating protein–ligand interactions. What I worked on 🔹 Collected T2DM-associated genes from GeneCards 🔹 Predicted molecular targets of Quercetin using SwissTargetPrediction 🔹 Identified common targets between the disease and compound 🔹 Constructed and analysed a Protein–Protein Interaction (PPI) network using STRING and Cytoscape 🔹 Performed Gene Ontology (GO) and KEGG pathway enrichment analysis 🔹 Selected ENPP1 for molecular docking based on its biological relevance 🔹 Prepared the receptor and ligand for docking 🔹 Performed molecular docking using PyRx (AutoDock Vina) 🔹 Analysed protein–ligand interactions using BIOVIA Discovery Studio Visualizer The best docking pose showed a predicted binding affinity of −8.6 kcal/mol, and interaction analysis revealed multiple hydrogen bonds and hydrophobic interactions contributing to the predicted stability of the Quercetin–ENPP1 complex. More than the final docking score, what I enjoyed most was understanding how each step, from disease gene identification to pathway analysis and docking that fits together in a computational drug discovery workflow. This project helped me gain hands-on experience with biological databases, network analysis, molecular docking, and protein–ligand interaction analysis while reinforcing the importance of combining biological context with computational methods. The complete project, workflow, results, and supporting files are available on GitHub: 🔗 GitHub: https://lnkd.in/dKkY-87x I'm looking forward to building more projects in bioinformatics and computational biology and continuing to learn along the way. #Bioinformatics #ComputationalBiology #NetworkPharmacology #MolecularDocking #Type2Diabetes #Quercetin #Cytoscape #PyRx #DiscoveryStudio #GeneCards #STRING #Genomics