Drug Design Assisted by Computers: New Tools in Bioinformatics

Abstract

The utilization of bioinformatics tools can expedite the process of identifying drug targets, examining and modifying drug candidates, and classifying potential side effects and drug resistance. Various high-throughput data, such as genomics, epigenetics, genome architecture, transcriptomics, proteomics, and ribosome profiling, have significant implications for drug repurposing and the development of mechanism-based drugs. Protein-ligand docking experiments and virtual screening are possible due to the creation of protein and RNA structure libraries, advances in structure modeling through homology, and databases of small molecules and metabolites. This article outlines the fundamental framework behind these high-throughput data, summarizes their effectiveness and potential in drug discovery, discusses their limitations, proposes new methods for refining the analysis, and highlights important software and databases commonly used in drug discovery.