Allostery and Missense Mutations as Intermittently Linked Promising Aspects of Modern Computational Drug Discovery

J Mol Biol. 2022 Sep 15;434(17):167610. doi: 10.1016/j.jmb.2022.167610. Epub 2022 Apr 28.

Abstract

Drug research and development is a multidisciplinary field with its own successes. Yet, given the complexity of the process, it also faces challenges over the long development stages and even includes those that develop once a drug is marketed, i.e. drug toxicity and drug resistance. Better success can be achieved via well designed criteria in the early drug development stages. Here, we introduce the concepts of allostery and missense mutations, and argue that incorporation of these two intermittently linked biological phenomena into the early computational drug discovery stages would help to reduce the attrition risk in later stages of the process. We discuss the individual or in concert mechanisms of actions of mutations in allostery. Design of allosteric drugs is challenging compared to orthosteric drugs, yet they have been gaining popularity in recent years as alternative systems for the therapeutic regulation of proteins with an action-at-a-distance mode and non-invasive mechanisms. We propose an easy-to-apply computational allosteric drug discovery protocol which considers the mutation effect, and detail it with three case studies focusing on (1) analysis of effect of an allosteric mutation related to isoniazid drug resistance in tuberculosis; (2) identification of a cryptic pocket in the presence of an allosteric mutation of falcipain-2 as a malarial drug target; and (3) deciphering the effects of SARS-CoV-2 evolutionary mutations on a potential allosteric modulator with changes to allosteric communication paths.

Keywords: allosteric communication paths; centrality; drug resistance; drug toxicity; dynamic residue network (DRN) analysis.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Allosteric Regulation / genetics
  • Allosteric Site
  • Computer Simulation
  • Drug Discovery* / methods
  • Drug Resistance, Bacterial
  • Humans
  • Mutation, Missense*
  • SARS-CoV-2 / genetics