ChemFlowFrom 2D Chemical Libraries to Protein–Ligand Binding Free Energies

• Published in: Journal of chemical information and modeling Vol. 63; no. 2; pp. 407 - 411
• Main Authors: Barreto Gomes, Diego E., Galentino, Katia, Sisquellas, Marion, Monari, Luca, Bouysset, Cédric, Cecchini, Marco
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 23.01.2023
• Subjects: Affinity; Application Note; Binding Sites; Entropy; Free energy; Libraries; Ligands; Molecular dynamics; Molecular Dynamics Simulation; Protein Binding; Proteins; Small Molecule Libraries - chemistry; Small Molecule Libraries - pharmacology; Thermodynamics
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/acs.jcim.2c00919

The accurate prediction of protein–ligand binding affinities is a fundamental problem for the rational design of new drug entities. Current computational approaches are either too expensive or inaccurate to be effectively used in virtual high-throughput screening campaigns. In addition, the most sophisticated methods, e.g., those based on configurational sampling by molecular dynamics, require significant pre- and postprocessing to provide a final ranking, which hinders straightforward applications by nonexpert users. We present a novel computational platform named ChemFlow to bridge the gap between 2D chemical libraries and estimated protein–ligand binding affinities. The software is designed to prepare a library of compounds provided in SMILES or SDF format, dock them into the protein binding site, and rescore the poses by simplified free energy calculations. Using a data set of 626 protein–ligand complexes and GPU computing, we demonstrate that ChemFlow provides relative binding free energies with an RMSE < 2 kcal/mol at a rate of 1000 ligands per day on a midsize computer cluster. The software is publicly available at https://github.com/IFMlab/ChemFlow.