ArticleJournal of computer-aided molecular design2018
Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations.
Article in Journal of computer-aided molecular design, 2018. 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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Who cites it
11 citing papers in PubMed.
- Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins.Journal of chemical theory and computation · 2024Article
- Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Comparison of Receptor-Ligand Restraint Schemes for Alchemical Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2023Article
- SARS-CoV-2 and MERS-CoV Spike Protein Binding Studies Support Stable Mimic of Bound 9-Molecules (Basel, Switzerland) · 2022Article
- An open-source molecular builder and free energy preparation workflow.Communications chemistry · 2022Article
- D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.Journal of computer-aided molecular design · 2020Article
- Best Practices for Alchemical Free Energy Calculations [Article v1.0].Living journal of computational molecular science · 2020Article
- Application of ESMACS binding free energy protocols to diverse datasets: Bromodomain-containing protein 4.Scientific reports · 2019Article
- A computationally designed binding mode flip leads to a novel class of potent tri-vector cyclophilin inhibitors.Chemical science · 2019Article
- Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors.PloS one · 2019Article
- Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge.Journal of computer-aided molecular design · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.
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