Paper Key : IRJ************929
Author: Shreyash Shankarrao Chavan,Shweta Gite
Date Published: 21 Nov 2024
Abstract
Network pharmacology is an interdisciplinary field combining systems biology, bioinformatics, and pharmacology to investigate drug-target interactions, molecular pathways, and disease networks. It represents a shift from the conventional one drug, one target approach to a holistic multi-target, multi-pathway perspective. The success of network pharmacology heavily relies on computational tools and software that facilitate data integration, network construction, and analysis.Key tools used in network pharmacology include Cytoscape , a widely used platform for constructing and visualizing biological networks, and STRING , which predicts protein-protein interactions based on experimental and computational data. Databases such as TCMSP (Traditional Chinese Medicine Systems Pharmacology) and DrugBank provide essential information on drug-related molecular properties. Tools like STITCH and TargetNet help predict drug-target interactions. For pathway enrichment and functional analysis, DAVID , Metascape , and KEGG Mapper are commonly employed.Emerging tools such as Open Targets Platform integrate multi-omics data, enhancing the identification of potential therapeutic targets. Machine learning frameworks like DeepChem are also being explored to predict complex drug interactions and polypharmacology effects.Integration of tools for molecular docking, such as AutoDock and MOE , with network pharmacology platforms facilitates detailed mechanistic insights into ligand-receptor interactions. The interoperability of these tools allows researchers to develop comprehensive networks to identify biomarkers, repurpose drugs, and explore combination therapies for complex diseases like cancer, neurodegeneration, and metabolic disorders.The evolution of software and tools in network pharmacology continues to advance drug discovery by enabling high-throughput and precise analyses, paving the way for a more personalized and systems-based approach to medicine.