Computational Chemistry: A game-changer in the drug discovery field

Abstract

The greater development in the computational tools and the presence of a huge number of established chemical libraries emerge the inquiry about the ability to integrate the computational techniques in the drug discovery process. This review emphasizes the role of computational tools and software to accelerate the steps in the drug discovery pipeline. The data were gathered from the trendiest research articles and reviews that were indexed in the well-established scholarly search engines. Different vital techniques, such as virtual screening, pharmacophore modeling, molecular docking, molecular dynamic simulations, and quantitative structure activity relationship, are widely employed for target recognition, lead refining, and forecasting binding behavior at the atomic level. The advancement in artificial cognitive computing software significantly expanded the capabilities for rapid analysis of substantial data sets and the generation of toxicity and bioactivity predictive models of drugs. The contributions of these software tools tackled global problems, like drug repurposing during the coronavirus outbreak, and the direction toward personalized medicaments highlight their crucial role in the swift discovery of new treatments. In addition, computational tools are widely employed to enhance the drug formulations, which leads to discovering drugs with optimum pharmacokinetic and toxicity profiles. The difficulties in analyzing the multi-target binding behaviors and the limited success rates of the generated candidates in the experimental validations were the main existing limitations. However, the steep development in the field of artificial intelligence and the hybrid biochemical-computational approaches provided promising horizons to tackle these limitations. Chemical computational tools significantly affect the future of pharmaceutical research by boosting the drug discovery process toward affordable and efficient medicaments.