Accuracy of Molecular Simulation-Based Predictions of k_off Values: A Metadynamics Study

Abstract

The k off values of ligands unbinding to proteins are key parameters for drug discovery. Their predictions based on molecular simulation may under- or overestimate experiment in a system- and/or technique-dependent way. Here we use an established methodinfrequent metadynamics, based on the AMBER force fieldto compute the k off of the ligand iperoxo (in clinical use) targeting the muscarinic receptor M2. The ligand charges are calculated by either (i) the Amber standard procedure or (ii) B3LYP-DFT. The calculations using (i) turn out not to provide a reasonable estimation of the transition-state free energy. Those using (ii) differ from experiment by 2 orders of magnitude. On the basis of B3LYP DFT QM/MM simulations, we suggest that the observed discrepancy in (ii) arises, at least in part, from the lack of electronic polarization and/or charge transfer in biomolecular force fields. These issues might be present in other systems, such as DNA–protein complexes.

Expanding the boundaries of ligand–target modeling by exascale calculations

“…The second key issue is the quality of the interatomic potential. Standard biomolecular force‐fields, widely used in CSBDD, are parametrized to reproduce a subset of experimental data, necessarily limiting their domain of applicability 34 . They neglect polarization effects and charge transfer, which may play a role in ligand/target interactions 34 .…”

“…It can routinely run systems of 10 5 atoms for μs timescales. MD‐based ligand binding free energies 13,28–32 allow to predict potency and residence times of drugs 30,33–35 . Examples of the impact of MD in pharmacology include (but are by no means limited to) the development of the FDA‐approved HIV‐1 lifesaving drugs nelfinavir and raltegravir, 36 the ongoing SARS‐CoV‐2 research 37–40 and the development of a variety of anti‐cancer drugs 41,42 …”

“…34 They neglect polarization effects and charge transfer, which may play a role in ligand/target interactions. 34 In QM/MM simulations, DFT is a computationally efficient method to treat fairly large systems with a good accuracy but that it can be difficult to attain chemical accuracy especially for transition states and systems with pronounced multireference character. One should keep these limitations in mind when using MD to predict ligand poses and affinities.…”

“…MD-based ligand binding free energies 13,[28][29][30][31][32] allow to predict potency and residence times of drugs. 30,[33][34][35] Examples of the impact of MD in pharmacology include (but are by no means limited to) the development of the FDA-approved HIV-1 lifesaving drugs nelfinavir and raltegravir, 36 the ongoing SARS-CoV-2 research [37][38][39][40] and the development of a variety of anti-cancer drugs. 41,42 The development of supercomputers, combined with the power of parallel algorithms, can greatly boost the investigations of ligand/target complexes and CSBDD.…”

Kinetics and Mechanism of Fentanyl Dissociation from theµ-Opioid Receptor

“…In metadynamics bias potentials are deposited along chosen collective variables to overcome free energy barriers. As such metadynamics is an efficient method for exploring protein-ligand unbinding kinetics, [26][27][28][29] bridging the microsecond simulation and the second-to-minute experimental timescales. Most recently, metadynamics simulations of morphine and buprenorphine dissociation from mOR showed that the ligand transitioned to the vestibule region after the D147 3.32 salt bridge was disrupted.…”