Protein–Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field

Abstract

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

“…In two of the systems (MCL1 and Thrombin), ARROW performed well, and in a third (CDK2) serious force field deficiencies were uncovered in describing strong interactions involving the charged ASP87. Here we have described the ligand−protein, ligand−water, and protein−protein (within 6A of the binding pocket) interactions by ARROW-NN and repeated the benchmark 48 calculations. The multiple details of alchemical transformations and other protocols are discussed at length in ref 48.…”

“…Molecular simulations were performed with in-house MD software (Arbalest) as has been described in previous publications ,, as well as in Section SI 5. We have previously highlighted the necessity of including nuclear quantum effects for precise predictions, and all computations below are done at the PIMD8 level of NQE.…”

“…As we have shown in previous work 14 and in Figure 3b(right) and Section SI 4, for ARROW, this is indeed so: the inductive nonadditive components are accurate to less than 1% of the total energy. The required degree of accuracy of the 2-body energies (V 2 ), touched on above and illustrated in Figure 1, was unexpected, 48 and improving them is the main point of this manuscript.…”

“…7,42−45 Within the polarizable subcategory, most models are (partially) parametrized by fitting to experimental data, 13,36,46 and some, e.g., ARROW FF, are based purely on ab initio QM calculations. 11,14,47 Although the ARROW FF has successfully predicted solvation and hydration energies of neutral molecules to within chemical accuracy, 14 this group's application of the ARROW force field to protein− ligand complexes 48 has uncovered major deficiencies in describing strong interactions in these systems. As we have previously noted, "The ARROW FF is likely at the limit of complexity feasible for a wide-coverage analytical force field," 14 and a fresh approach is needed.…”

Selectivity Mechanism of Pyrrolopyridone Analogues Targeting Bromodomain 2 of Bromodomain-Containing Protein 4 from Molecular Dynamics Simulations

“…A reliable inhibitor–protein complex structure plays a vital role in drug development. − Computational methods, such as homology modeling, − molecular docking, − molecular dynamics (MD) simulation, − binding free energy calculation, − and others − are widely employed. These methods were used to elucidate the binding models and mechanisms of inhibitor/BET systems. − Thus, MD simulations and binding free energy calculations were employed in the present study to elucidate the selective-BD2 mechanism for the pyrrolopyridone core compounds.…”