Computational Approaches for Identifying Therapeutic Potential of Phytocompounds

Abstract

AbstractDrug discovery is a process that aims at identifying a compound with therapeutic potential in curing and treating disease. Developing methods for diagnosing and treating disease has been a big challenge for pharmaceutical researchers and clinicians. The era of Computer Aided Drug Discovery (CADD) has bought down the time and efforts to a large extent. CADD has contributed largely to different stages of the drug discovery pipeline, mainly in the identification and optimization of lead compounds, leading them to the advanced stages in drug discovery. CADD gives valuable information about the molecular properties, pharmacodynamics, and toxicity, thus helping in the lead optimization phase and improving the efficacy and potency of the drug candidate. This chapter highlights basic steps in the CADD pipeline, two important categories of CADD, i.e., ligand-based and structure-based drug discovery (SBDD and LBDD). Various techniques used in SBDD and LBDD, including molecular docking, molecular dynamic simulation, Quantitative structure-activity relationship (QSAR), pharmacophore modeling, etc., have been briefly discussed. Also, available webservers and tools, significance, applications, and limitations of CADD are also briefly mentioned.KeywordsCADDQSARMolecular dockingSBDDLBDDPharmacophore