BindFlow: A Free, User-Friendly Pipeline for Absolute Binding Free Energy Calculations Using Free Energy Perturbation...

Area of Science:

• Computational chemistry
• Molecular modeling
• Drug discovery

Background:

• Accurate prediction of binding free energies is crucial for drug discovery.
• Existing methods for absolute binding free energy (ABFE) calculations can be computationally expensive and complex.
• There is a need for accessible and efficient software tools for ABFE analysis.

Purpose of the Study:

• To introduce BindFlow, a novel Python-based software for automated ABFE calculations.
• To validate BindFlow's performance against experimental data for diverse receptor-ligand systems.
• To compare the efficiency and accuracy of different theoretical approaches within BindFlow.

Main Methods:

• BindFlow utilizes GROMACS for molecular dynamics simulations.
• Supports various force fields including GAFF, OpenFF, and Espaloma, with custom field options.
• Employs both free energy perturbation (FEP) and molecular mechanics Poisson-Boltzmann/generalized Born surface area [MM(PB/GB)SA] methods.
• Tested on 139 receptor-ligand pairs across eight different targets.

Main Results:

• BindFlow demonstrates agreement with experimental binding affinities comparable to established methods.
• MM(PB/GB)SA calculations within BindFlow showed promising correlations with experimental data, approaching FEP results at lower computational cost.
• The software proved effective across soluble proteins, membrane proteins, and host-guest systems.

Conclusions:

• BindFlow is a validated, user-friendly, and accessible tool for automated ABFE calculations.
• The software facilitates efficient and customizable binding affinity predictions.
• MM(PB/GB)SA offers a computationally cheaper alternative to FEP for certain ABFE applications using BindFlow.