ArticleJournal of chemical information and modeling2019
Using AMBER18 for Relative Free Energy Calculations.
Article in Journal of chemical information and modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.
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Who cites it
109 citing papers in PubMed.
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- Article
- Comparative Analysis of Quantum-Mechanical and Standard Single-Structure Protein-Ligand Scoring Functions with MD-Based Free Energy Calculations.Journal of chemical information and modeling · 2025Article
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- The crystal structure of GH57 family amylopullulanase reveals its dual binding pockets sharing the same catalytic dyad.Communications biology · 2025Article
- Identification of naturally occurring drug-resistant mutations of SARS-CoV-2 papain-like protease.Nature communications · 2025Article
49 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
With renewed interest in free energy methods in contemporary structure-based drug design, there is a pressing need to validate against multiple targets and force fields to assess the overall ability of these methods to accurately predict relative binding free energies. We computed relative binding free energies using graphics processing unit accelerated thermodynamic integration (GPU-TI) on a data set originally assembled by Schrödinger, Inc. Using their GPU free energy code (FEP+) and the OPLS2.1 force field combined with the REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol. In our study using GPU-TI from AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 perturbations contained in this data set. A more detailed analysis of our results suggested that the observed differences between the two studies arise from differences in sampling protocols along with differences in the force fields employed. Future work should address the problem of establishing benchmark quality results with robust statistical error bars obtained through multiple independent runs and enhanced sampling, which is possible with the GPU-accelerated features in AMBER.
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