Network Pharmacology and Molecular Docking Internship

To investigate the multi-component and multi-target mechanisms of drugs, natural products, medicinal plants, or bioactive compounds using network pharmacology, protein-interaction analysis, pathway enrichment, and molecular docking.

• Medicinal plant pharmacology
• Natural-product drug discovery
• Cancer therapeutics
• Anti-inflammatory compounds
• Neuroprotective compounds
• Antidiabetic compounds

• Select a medicinal plant, natural compound, formulation, or approved drug.
• Collect active compounds and standardize compound structures.
• Apply drug-likeness and ADME screening filters.
• Predict compound targets and collect disease-associated genes.
• Identify common compound-disease targets.
• Construct compound-target and protein-interaction networks.
• Identify hub targets and functional modules.
• Perform Gene Ontology, KEGG, and Reactome enrichment analysis.

PubChem ChEMBL-Compatible Resources SwissTargetPrediction-Compatible Resources BindingDB-Compatible Resources GeneCards-Compatible Resources DisGeNET-Compatible Resources STRING Cytoscape cytoHubba MCODE ClueGO AutoDock Vina PyRx Open Babel RDKit

• Active-compound database
• Drug-likeness and ADME report
• Compound-target table
• Disease-gene table
• Common-target analysis
• STRING protein-interaction network
• Cytoscape network and session file
• Hub-target ranking

Network Pharmacology of Curcumin in Breast Cancer

Multi-Target Mechanism of Withania somnifera in Neurodegenerative Disease

Network Pharmacology and Docking Analysis of Natural Compounds Against Diabetes

Systems Pharmacology of Plant-Derived Anti-Inflammatory Compounds

Network-Based Drug Repurposing for Viral Infection

Network Pharmacology of Bioactive Compounds in Cardiovascular Disease

• Natural-product and medicinal-plant mechanism discovery
• Multi-target drug discovery and drug repurposing
• Identification of disease-relevant hub targets and pathways
• Validation of traditional medicine through computational evidence
• Docking-based screening of bioactive compounds against disease targets
• Mechanistic interpretation of compound-target-pathway-disease relationships

• Biotechnology, bioinformatics, pharmacy, and life-science students
• Pharmaceutical science and drug-discovery learners
• Researchers working on medicinal plants and natural products
• PhD scholars interested in systems pharmacology and docking
• Faculty members and early-career researchers in computational biology
• Learners interested in multi-target therapeutics and traditional medicine validation

Prerequisites: Basic knowledge of biology, pharmacology, molecular targets, and bioinformatics is recommended. Familiarity with Cytoscape, molecular docking, or Google Colab will be helpful but is not mandatory.

• Compound database preparation and chemical-structure standardization
• Drug-likeness, ADME, and target-screening interpretation
• Disease-gene collection and common-target identification
• Protein-interaction network construction and Cytoscape analysis
• Hub-target detection, module analysis, and pathway enrichment
• Molecular docking, binding-interaction analysis, and mechanism modeling