title: Accurate Binding Free Energy Predictions in Fragment Optimization.
abstract: Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.
authors.affiliation: Schrödinger GmbH, Dynamostrasse 13, 68165 Mannheim, Baden-Württemberg, Germany.
authors.forename: Thomas B
authors.initials: TB
authors.lastname: Steinbrecher
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Markus
authors.initials: M
authors.lastname: Dahlgren
authors.affiliation: Schrödinger GmbH, Dynamostrasse 13, 68165 Mannheim, Baden-Württemberg, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Cappel
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Teng
authors.initials: T
authors.lastname: Lin
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Lingle
authors.initials: L
authors.lastname: Wang
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Goran
authors.initials: G
authors.lastname: Krilov
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Robert
authors.initials: R
authors.lastname: Abel
authors.affiliation: Department of Chemistry, Columbia University , 3000 Broadway New York, New York 10027, United States.
authors.forename: Richard
authors.initials: R
authors.lastname: Friesner
authors.affiliation: Schrödinger Inc., 120 West 45th Street, 17th Floor, New York, New York 10036, United States.
authors.forename: Woody
authors.initials: W
authors.lastname: Sherman
mesh_terms: D000818:Animals; D001426:Bacterial Proteins / Q000378:metabolism; D015195:Drug Design; D006801:Humans; D008024:Ligands; D051379:Mice; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*; D013211:Staphylococcus aureus / Q000378:metabolism; D013816:Thermodynamics
chemical_list: D001426:Bacterial Proteins; D008024:Ligands; D011506:Proteins