ArticleJournal of chemical theory and computation2022
Protein-Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Deep residual learning for molecular force fields.Nature communications · 2026Article
- Evaluation of the ABCG2 Charge Model in Protein-Ligand Binding Free-Energy Calculations.Journal of chemical information and modeling · 2025Article
- Machine Learning-Enhanced Calculation of Quantum-Classical Binding Free Energies.Journal of chemical theory and computation · 2025Article
- Quantification of the Impact of Structure Quality on Predicted Binding Free Energy Accuracy.Journal of chemical information and modeling · 2025Article
- Evaluating the Functional Importance of Conformer-Dependent Atomic Partial Charge Assignment.Journal of computational chemistry · 2025Article
- The Determination of Free Energy of Hydration of Water Ions from First Principles.Journal of chemical theory and computation · 2024Article
- Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties.Journal of chemical theory and computation · 2024Article
- Combining Force Fields and Neural Networks for an Accurate Representation of Bonded Interactions.The journal of physical chemistry. A · 2024Article
- Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.Journal of the American Chemical Society · 2023Article
- Article
- Predicting the Effect of Single Mutations on Protein Stability and Binding with Respect to Types of Mutations.International journal of molecular sciences · 2023Article
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21 authors.
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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.
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