Drug design principles from electric field calculations: understanding SARS-CoV-2 main protease interaction with X77 non-covalent inhibitor

TL;DR

This study introduces a method using electric field calculations in molecular dynamics to identify key residues in enzyme-inhibitor interactions, exemplified by SARS-CoV-2 main protease and the X77 inhibitor, streamlining drug discovery.

Contribution

The paper presents a novel approach to link structure and function via electric field calculations, reducing the complexity of identifying critical interaction residues in drug design.

Findings

Identified 3 key residues influencing inhibitor binding

Contrasted with 20 residues previously reported

Enabled targeted optimization of potential inhibitors

Abstract

Fast and effective drug discovery processes rely on rational drug design to circumvent the tedious and expensive trial and error approach. However, accurate predictions of new remedies, which are often enzyme inhibitors, require a clear understanding of the nature and function of the key players governing the interaction between the drug candidate and its target. Here, we propose to calculate electric fields to explicitly link structure to function in molecular dynamics simulations, a method that can easily be integrated within the rational drug discovery workflow. By projecting the electric fields onto specific bonds, we can identify the system components that are at the origin of stabilizing intermolecular interactions (covalent and non-covalent) in the active site. This helps to significantly narrow the exploration space when predicting new inhibitors. To illustrate this method, we characterize the binding of the non-covalent inhibitor X77 to the main protease of SARS-CoV-2, a particularly time-sensitive drug discovery problem. With electric field calculations, we were able to identify 3 key residues (Asn-142, Met-165 and Glu-166), that have functional consequences on X77. This contrasts with the nearly 20 residues reported in previous studies as being in close contact with inhibitors in the active site of the protease. As a result, the search for new non-covalent inhibitors can now be accelerated by techniques that look to optimize the interaction between candidate molecules and these residues.