Prediction of Potency of Protease Inhibitors Using Free Energy Simulations with Polarizable Quantum Mechanics-Based Ligand Charges and a Hybrid Water Model
Year: 2009
Type: article
Abstract: Reliable and robust prediction of the binding affinity for drug molecules continues to be a daunting challenge. We simulated the binding interactions and free energy of binding of nine protease inhibitors (PIs) with wild-type and various mutant proteases by performing GBSA simulations in which each PI's partial charge was determined by quantum mechanics (QM) and the partial charge accounts for the polarization induced by the protease environment. We employed a hybrid solvation model that retains selected explicit water molecules in the protein with surface-generalized Born (SGB) implicit solvent. We examined the correlation of the free energy with the antiviral potency of PIs with regard to amino acid substitutions in protease. The GBSA free energy thus simulated showed strong correlations (r > 0.75) with antiviral IC(50) values of PIs when amino acid substitutions were present in the protease active site. We also simulated the binding free energy of PIs with P2-bis-tetrahydrofuranylurethane (bis-THF) or related cores, utilizing a bis-THF-containing protease crystal structure as a template. The free energy showed a strong correlation (r = 0.93) with experimentally determined anti-HIV-1 potency. The present data suggest that the presence of selected explicit water in protein and protein polarization-induced quantum charges for the inhibitor, compared to lack of explicit water and a static force-field-based charge model, can serve as an improved lead optimization tool and warrants further exploration.
DOI: 10.1021/ci900320p
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2078587289