ArticleThe journal of physical chemistry letters2021
DeepBAR: A Fast and Exact Method for Binding Free Energy Computation.
Article in The journal of physical chemistry letters, 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.
- LamNet: an alchemical-path-aware graph neural network to accelerate binding free energy calculations for drug discovery and beyond.National science review · 2026Article
- Accurate Lattice Free Energies of Packing Polymorphs from Probabilistic Generative Models.Journal of chemical theory and computation · 2025Article
- Assessing the Accuracy and Efficiency of Free Energy Differences Obtained fromJournal of chemical theory and computation · 2024Article
- Learned mappings for targeted free energy perturbation between peptide conformations.The Journal of chemical physics · 2023Article
- A generalized Kirkwood implicit solvent for the polarizable AMOEBA protein model.The Journal of chemical physics · 2023Article
- Design of synthetic promoters for cyanobacteria with generative deep-learning model.Nucleic acids research · 2023Article
- AI in drug discovery and its clinical relevance.Heliyon · 2023Review
- Contrastive Learning of Coarse-Grained Force Fields.Journal of chemical theory and computation · 2022Article
- Review
- Unifying coarse-grained force fields for folded and disordered proteins.Current opinion in structural biology · 2022Review
- Intersection of stem cell biology and engineering towards next generationFrontiers in bioengineering and biotechnology · 2022Review
- Machine Learning and Radiomic Features to Predict Overall Survival Time for Glioblastoma Patients.Journal of personalized medicine · 2021Article
- Autoimmune diseases - New insights into a troublesome field.Journal of translational autoimmunity · 2021Article
- Recent Developments in Free Energy Calculations for Drug Discovery.Frontiers in molecular biosciences · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The fast and accurate calculation of standard binding free energy has many important applications. Existing methodologies struggle at balancing accuracy and efficiency. We introduce a new method to compute binding free energy using deep generative models and the Bennett acceptance ratio method (DeepBAR). Compared to the rigorous potential of mean force (PMF) approach that requires sampling from intermediate states, DeepBAR is an order-of-magnitude more efficient as demonstrated in a series of host-guest systems. Notably, DeepBAR is exact and does not suffer from approximations for entropic contributions used in methods such as the molecular mechanics energy combined with the generalized Born and surface area continuum solvation (MM/GBSA). We anticipate DeepBAR to be a valuable tool for computing standard binding free energy used in drug design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.