Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro

Abstract

The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson–Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE ≈ FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26 , His41 , Ser46 , Asn142 , Gly143 , Cys145 , His164 , Glu166 , and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches.

Evaluation of SARS-CoV-2 main protease and inhibitor interactions using dihedral angle distributions and radial distribution function

“…Due to the changing nature of dielectric constant ( ε ) with the protein residues, the MM/PBSA results may be more accurate for slightly higher ε whose default value is taken to be unity in MM electrostatic calculation [44] . Though there are some evidences of poor correlation between MM/PBSA results and experimental data for the systems like SARS-CoV-2 having shallow binding cleft [45] , [46] , our result is in a close agreement with the MM/PBSA free energy values for the non-covalent ligands reported by Muhtar et al (2021) [47] . According to Gupta et al (2020), the MM/PBSA free energy for dihydroergotamine is -17.9 kcal/mol and that for midostaurin is -16.2 kcal/mol.…”

Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations

“…In particular, the substrate binding site of the SARS-CoV-2 Mpro contains two residues, His41 and Cys145 located in the cleft formed by domains I and II [ 19 , 20 ]. Strong binding inhibitors to the protease normally adopt rigid contacts to these residues [ 21 ]. Furthermore, the residues Thr26, Ser46, Asn142, Gly143, His164, Glu166 and Gln189 were found to be crucial for the ligand-binding process [ 21 ].…”

Marine derivatives preventwMUS81in silicostudies

“…The MD parameters were referred to the prior works [ 41 , 61 ]. In particular, the non-bonded pair between surrounding atoms is calculated within a radius of 9 Å with the pair list is reorganized every 5 ps during the MD simulations.…”