ArticleJournal of chemical theory and computation2021
Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy.
Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Adaptive Normal Mode Sampling (aMDeNM) Enhances Exploration of Protein Conformational Space and Reveals the Functional Role of Frequency Coupling.Journal of chemical theory and computation · 2026Article
- On Free Energy Calculations in Drug Discovery.Accounts of chemical research · 2025Article
- Thermodynamics of Molecular Binding and Clustering in the Atmosphere Revealed through Conventional and ML-Enhanced Umbrella Sampling.ACS omega · 2025Article
- Binding Free Energy Calculations Based on the Path Collective Variable along a String Pathway.The journal of physical chemistry. B · 2025Article
- Path-Based Nonequilibrium Binding Free Energy Estimation, from Protein-Ligand to RNA-Ligand Binding.Journal of chemical information and modeling · 2025Article
- Nonequilibrium Binding Free Energy Simulations: Minimizing Dissipation.Journal of chemical theory and computation · 2025Article
- Adaptive CVgen: Leveraging reinforcement learning for advanced sampling in protein folding and chemical reactions.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Exploring Carbamazepine Polymorph Crystal Growth in Water by Enhanced Sampling Simulations.ACS omega · 2024Article
- Computational studies on the catalytic potential of the double active site for enzyme engineering.Scientific reports · 2024Article
- Enhanced Sampling of Buried Charges in Free Energy Calculations Using Replica Exchange with Charge Tempering.Journal of chemical theory and computation · 2024Article
- Host Dynamics under General-Purpose Force Fields.Molecules (Basel, Switzerland) · 2023Article
- RosettaDDGPrediction for high-throughput mutational scans: From stability to binding.Protein science : a publication of the Protein Society · 2023Article
- Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure.Journal of computer-aided molecular design · 2022Article
- Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers.Interface focus · 2021Article
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4 authors.
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Abstract
Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including the free energy of a drug binding to a target. In contrast to calculations of relative binding free energy, which are nowadays widely exploited for drug discovery, we here push the boundary of computing the binding free energy and the potential of mean force. We introduce a novel protocol that leverages enhanced sampling, machine learning, and ad hoc algorithms to limit human intervention, computing time, and free parameters in free energy calculations. We first validate the method on a host-guest system, and then we apply the protocol to glycogen synthase kinase 3 beta, a protein kinase of pharmacological interest. Overall, we obtain a good correlation with experimental values in relative and absolute terms. While we focus on protein-ligand binding, the strategy is of broad applicability to any complex event that can be described with a path collective variable. We systematically discuss key details that influence the final result. The parameters and simulation settings are available at PLUMED-NEST to allow full reproducibility.
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