  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.
