Accurate Ensemble Molecular Dynamics Binding Free Energy Ranking of Multidrug-Resistant HIV-1 Proteases

Abstract

Accurate calculation of important thermodynamic properties, such as macromolecular binding free energies, is one of the principal goals of molecular dynamics simulations. However, single long simulation frequently produces incorrectly converged quantitative results due to inadequate sampling of conformational space in a feasible wall-clock time. Multiple short (ensemble) simulations have been shown to explore conformational space more effectively than single long simulations, but the two methods have not yet been thermodynamically compared. Here we show that, for end-state binding free energy determination methods, ensemble simulations exhibit significantly enhanced thermodynamic sampling over single long simulations and result in accurate and converged relative binding free energies that are reproducible to within 0.5 kcal/mol. Completely correct ranking is obtained for six HIV-1 protease variants bound to lopinavir with a correlation coefficient of 0.89 and a mean relative deviation from experiment of 0.9 kcal/mol. Multidrug resistance to lopinavir is enthalpically driven and increases through a decrease in the protein-ligand van der Waals interaction, principally due to the V82A/I84V mutation, and an increase in net electrostatic repulsion due to water-mediated disruption of protein-ligand interactions in the catalytic region. Furthermore, we correctly rank, to within 1 kcal/mol of experiment, the substantially increased chemical potency of lopinavir binding to the wild-type protease compared to saquinavir and show that lopinavir takes advantage of a decreased net electrostatic repulsion to confer enhanced binding. Our approach is dependent on the combined use of petascale computing resources and on an automated simulation workflow to attain the required level of sampling and turn around time to obtain the results, which can be as little as three days. This level of performance promotes integration of such methodology with clinical decision support systems for the optimization of patient-specific therapy.

Mechanism of Drug Efficacy Within the EGF Receptor Revealed by Microsecond Molecular Dynamics Simulation

“…It is interesting to note that the substate of the L858R mutation, around (coordinates À30, 37) on the first 2 principal components, is only reached at about 3.4 ms; the same conformation was observed in one of our previous four 200 ns simulations (18), after only 100 ns simulation. Although multiple short (ensemble) simulations have been shown to explore local conformational space more effectively (14,25), long timescale simulations are needed for large-scale conformational changes such as ligand binding (26) and protein folding (27).…”

The Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric Constant

“…These systems have been used in previous studies of free energy methods. 15,16,17 MD simulations. The MD simulations of the fXa and ferritin complexes were conducted by the Amber10 software 32 and they were taken from previous studies.…”

“…These systems have been used in previous studies of free energy methods. 15,16,17 Methods Preparation of proteins and ligands. In this paper, we study eight 3-amidinobenzyl-1H-indole-2-carboxamide inhibitors of fXa, 18 nine inhibitors to ferritin, as well as the two inhibitors amprenavir (APV) and darunavir (DRV) binding to either wild-type (WT) or a double mutant (V82T/I84V, MT) HIV-1 protease (HIV-PR).…”

Binding Affinities of Factor Xa Inhibitors Estimated by Thermodynamic Integration and MM/GBSA

“…The latter method is interesting because it is composed of physically well-defined terms and contains no adjustable parameters. It has been shown to be useful to estimate binding affinities, 16,17,18,19 although it sometimes fails. 20,21 A problem with this method has been the high statistical uncertainty of the estimates.…”