COMPUTATIONAL MODELING AND PHYSICS IN DRUG DISCOVERY

Abstract

Computational modeling and physics will play an important role in drug discovery, because it allows researchers to hypothesize the efficacy and safety of potential drugs without investing international regulatory approval time and large amounts of money. Computational modeling and physics-based approaches are changing the drug discovery space and have provided some powerful possible methods for reducing time and accelerating (failed) drug discovery. More than just reflecting on discovery methods, this review describes and situates the science of computer modelling and physics and the pharmaceutical sciences, collectively emphasizing the roles of each science relative to creating new drugs. This article provides a review of contemporary results regarding the ability to develop new pharmaceuticals using computer modelling, and physics that executed, taken literally, includes molecular docking, molecular dynamics simulation, quantitative structure-activity relationship (QSAR) modelling, virtual screening and machine learning. Within this review, I explore the challenges and limitations of undertaking computer modelling and physics-based approaches, as well as the applications the pharmaceutical industry may improve upon. A systematic search was performed for the review using the following electronic databases: PubMed, Scopus, Science Direct, Springer, Cureus, Elsevier, and Web of Science. The searches produced publications published within the past 10 years related to the topic of interest. At first, 40 articles were located but only 25 articles were selected for the review, because their content was relevant. Finally, computational modelling and physics are indispensable in drug discovery by providing valuable information on how molecules interact with each other, and they also aid in the design, development, and optimization of new therapeutic candidates.