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Relative BAT: An Automated Tool for Relative Binding Free Energy Calculations by the Separated Topologies Approach.

Germano Heinzelmann1, David J Huggins2,3, Michael K Gilson4

  • 1Departamento de Fisica, Universidade Federal de Santa Catarina, Florianopolis 88040-900, Brasil.

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|December 1, 2025
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Summary
This summary is machine-generated.

The Binding Affinity Tool (BAT.py) software now offers relative binding free energy (RBFE) calculations using separated topologies (SepTop). This method enhances drug discovery by accurately predicting binding affinities for diverse ligands with reduced computational cost.

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Molecular modeling

Background:

  • Absolute (ABFE) and relative binding free energy (RBFE) calculations using molecular dynamics (MD) are crucial for cost-effective early-stage drug discovery.
  • Existing methods face challenges with ligand similarity, occluded binding sites, and receptor conformational changes.

Purpose of the Study:

  • Introduce a new implementation of the Binding Affinity Tool (BAT.py) software.
  • Incorporate RBFE calculations utilizing separated topologies (SepTop) into an automated workflow.
  • Address limitations of traditional ABFE and RBFE methods.

Main Methods:

  • Implemented three distinct thermodynamic paths for RBFE calculations within BAT.py.
  • Utilized AMBER and OpenMM simulation engines for molecular dynamics simulations.
  • Tested the new SepTop approach on the BRD4(2) benchmark system.

Main Results:

  • Evaluated the correlation between SepTop RBFE, ABFE, standard RBFE, and experimental data.
  • Assessed the computational cost associated with the implemented thermodynamic paths.
  • Demonstrated the applicability of SepTop to ligands with low or no structural similarity.

Conclusions:

  • The BAT.py software with SepTop offers a robust and versatile approach for binding free energy calculations.
  • SepTop RBFE calculations provide a valuable alternative, overcoming common challenges in drug discovery simulations.
  • This advancement has the potential to accelerate the identification of novel drug candidates.