Application of Computer-Aided Drug Design for Lead Identification and Drug Repurposing
Posted: 10 Feb 2020
Date Written: February 7, 2020
Computer-aided drug design (CADD) methodologies are expediting the drug design process by cutting costs and time associated with drug discovery process. Structure based drug design (molecular docking) and ligand based drug design (pharmacophore, structure-activity relationship and similarity search) are two pillars of CADD. Combining the CADD techniques with plethora of freely available omics data is revolutionizing the field of drug discovery. CADD has several applications such as lead identification, lead optimization and drug repurposing etc. Present work summarizes the two application of CADD i.e. novel lead identification and drug repurposing. To show the applicability of CADD methodologies we selected two high-priority disease area (bacterial infection and neuroinflammation). Firstly, to find novel lead molecule to target Escherichia coli (E. coli), UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) is selected as target due to unavailability of its mammalian counterpart. MurA catalyses the first committed cytosolic step of bacterial cell wall biosynthesis. A combination of in silico and cell based screening techniques were utilised for screening the library of ~ 55000 compounds potential inhibitor of MurA. Secondly, approved drug library was utilised for drug repurpose drug for the treatment of Neuroinflammation. Neuroinflammation is the major cause associated with many neurodegenerative diseases such as Alzheimer's and Parkinson’s disease. Due to the lack of knowledge related to disease-specific neuroinflammatory targets, most of the clinical candidates fail in different phases of drug development. In the present study, in-silico drug design methodologies such as network biology, the Connectivity map approach and structure-based virtual screening are combined with experimental techniques to repurpose drugs against selected targets. Finally, impact of emerging technologies such as Machine learning and artificial intelligence on the area of drug discovery is presented.
Keywords: CADD, drug repurposing, Drug Design, SBDD, LBDD, Network pharmacology, Machine learning
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