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

Abstract

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 .

Bartender: Martini 3 Bonded Terms via Quantum Mechanics-based Molecular Dynamics

“…Molecular dynamics (MD) simulations are useful tools for probing the dynamical behavior of biomolecular systems. For example, they can be integrated into larger workflows, such as drug discovery pipelines 1,2 . Within drug discovery campaigns, these methods can be used to identify druggable pockets in proteins 3,4 , to calculate the binding affinity of several ligands to a given protein 5,6 or to guide lead-optimization 7,8 efforts.…”

Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics

“…Molecular dynamics (MD) simulations are useful tools for probing the dynamical behavior of biomolecular systems. For example, they can be integrated into larger workflows, such as drug discovery pipelines. , Within drug discovery campaigns, these methods can be used to identify druggable pockets in proteins, , to calculate the binding affinity of several ligands to a given protein, , or to guide lead-optimization , efforts. Among the available simulation methods, coarse-grained (CG) approaches represent a trade-off between molecular detail and computational efficiency.…”

Bartender: Martini 3 Bonded Terms via Quantum Mechanics-based Molecular Dynamics

“…Molecular dynamics (MD) simulations are useful tools for probing the dynamical behavior of biomolecular systems. For example, they can be integrated into larger workflows, such as drug discovery pipelines [1,2] . Within drug discovery campaigns, these methods can be used to identify druggable pockets in proteins [3,4] , to calculate the binding affinity of several ligands to a given protein [5,6] or to guide lead-optimization [7,8] efforts.…”