Discovery of 2-Thiobenzimidazoles as Noncovalent Inhibitors of SARS-CoV-2 Main Protease

On the origins of SARS-CoV-2 main protease inhibitors

In order to address the world-wide health challenge caused by the COVID-19 pandemic, the 3CL protease/SARS-CoV-2 main protease (SARS-CoV-2-Mpro) coded by its nsp5 gene became one of the biochemical targets for the design of antiviral drugs. In less than 3 years of research, 4 inhibitors of SARS-CoV-2-Mpro have actually been authorized for COVID-19 treatment (nirmatrelvir, ensitrelvir, leritrelvir and simnotrelvir) and more such as EDP-235, FB-2001 and STI-1558/Olgotrelvir or five undisclosed compounds (CDI-988, ASC11, ALG-097558, QLS1128 and H-10517) are undergoing clinical trials. This review is an attempt to picture this quite unprecedented medicinal chemistry feat and provide insights on how these cysteine protease inhibitors were discovered. Since many series of covalent SARS-CoV-2-Mpro inhibitors owe some of their origins to previous work on other proteases, we first provided a description of various inhibitors of cysteine-bearing human caspase-1 or cathepsin K, as well as inhibitors of serine proteases such as human dipeptidyl peptidase-4 or the hepatitis C protein complex NS3/4A. This is then followed by a description of the results of the approaches adopted (repurposing, structure-based and high throughput screening) to discover coronavirus main protease inhibitors.

The prediction of main protease SARS-CoV-2 inhibition based on models of enzyme-inhibitor complexes

A set of linear regression equations predicting the IC50 values for SARS-CoV-2 main protease inhibitors was analyzed. For 180 competitive inhibitors, we have simulated the molecular dynamics of enzyme-inhibitor complexes with known structures or modeled using molecular docking. In the docking procedure, the selection of final poses was restricted by similarity to known structural analogs. The values of the energy contributions obtained by means of calculation of the free energy change of the enzyme-inhibitor complex performed by two variants of the MMPBSA (MMGBSA) method and a number of physicochemical characteristics of the inhibitors were used as independent variables. During the learning process, indicator variables were used for inhibitor subsets obtained from various literature sources to compensate the existing systematic deviations from the target value. A leave one out and leave 20% out cross validation procedures were used to evaluate the prediction quality. For the total logarithmic range width of 3.71, the mean error in predicting the lg(IC50) value was 0.45 log units. The stability of the prediction depending on the variability of the complex in molecular dynamics was investigated.

Artificial intelligence based virtual screening study for competitive and allosteric inhibitors of the SARS-CoV-2 main protease

SARS-CoV-2 is a highly contagious and dangerous coronavirus that first appeared in late 2019 causing COVID-19, a pandemic of acute respiratory illnesses that is still a threat to health and the general public safety. We performed deep docking studies of 800 M unique compounds in both the active and allosteric sites of the SARS-COV-2 Main Protease (Mpro) and the 15 M and 13 M virtual hits obtained were further taken for conventional docking and molecular dynamic (MD) studies. The best XP Glide docking scores obtained were -14.242 and -12.059 kcal/mol by CHEMBL591669 and the highest binding affinities were -10.5 kcal/mol (from 444215) and -11.2 kcal/mol (from NPC95421) for active and allosteric sites, respectively. Some hits can bind both sites making them a great area of concern. Re-docking of 8 random allosteric complexes in the active site shows a significant reduction in docking scores with a t-test P value of 2.532 × 10-11 at 95% confidence. Some specific interactions have higher elevations in docking scores. MD studies on 15 complexes show that single-ligand systems are stable as compared to double-ligand systems, and the allosteric binders identified are shown to modulate the active site binding as evidenced by the changes in the interaction patterns and stability of ligands and active site residues. When an allosteric complex was docked to the second monomer to check for homodimer formation, the validated homodimer could not be re-established, further supporting the potential of the identified allosteric binders. These findings could be important in developing novel therapeutics against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.