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Current Topics in Medicinal Chemistry


ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

Review Article

Bioinformatics and Drug Discovery

Author(s): Xuhua Xia*

Volume 17, Issue 15, 2017

Page: [1709 - 1726] Pages: 18

DOI: 10.2174/1568026617666161116143440

open access plus


Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.

Keywords: Drug target, Drug candidate, Drug screening, Genomics, Epigenetics, Transcriptomics, Proteomics, Structure.

Graphical Abstract

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