Evaluating Nirmatrelvir Resistance in SARS-CoV-2 Main Protease: A Comparison Between MM/PBSA and Free Energy Perturbation (Communications in Computational Chemistry, 2025)
Mutations that cause structural changes in proteins can sometimes reduce drug efficacy dramatically, a phenomenonknown as mutation-induced drug resistance. For example, emerging drug-resistant mutations in the SARS-CoV-2 main protease $({\rm M}^{pro})$ threaten the long-term efficacy of nirmatrelvir, the active component of Paxlovid. Various methods have been developedto predict the impact of such mutations, with differing levels of reliability. In this study, comparative binding free energycalculations using Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) and Alchemical Transformation (alsoknown as Free Energy Perturbation, or FEP) were performed to assess five naturally occurring Mpro mutations (SER144ALA,MET165ALA, GLU166ALA, HIE172ALA, and GLN192ALA) at the nirmatrelvir binding site. The results reveal a weakcorrelation $(R_{Pearson}=0.18)$ between MM/PBSA predictions and experimental data. In contrast, FEP calculations using eitherthe Multistate Bennett Acceptance Ratio (MBAR) or Thermodynamic Integration (TI) yield stronger linear correlations $(R_{Pearson} = 0.56$ and $0.57,$ respectively). This study highlights the superior reliability of FEP in quantifying binding affinity lossesdue to drug resistance and underscores its potential for the proactive surveillance of clinical resistance mutations. Moreover,such insights are crucial for advancing antiviral drug development and guiding the design of inhibitors with a reduced risk ofresistance evolution.
Keywords: drug resistance; MM/PBSA; free energy perturbation; alchemical transformation; binding affinity