Published September 28, 2022 | Version v1

A computational workflow for binding free energies in Python

Authors/Creators

  • 1. Aalborg University

Description

Dataset of distances between a host and six different ligands. The host was beta-cyclodextrin (bCD), while the ligands were phenol, benzene, aspirin, toluene, chlorobenzene and 1,3-dichlorobenzene. No bonds were frozen. 

The ligand were set to move with a step of 0.25 angstrom from -26 to 26 relative to the bCD (a total of 208 distances). At each distance, a energy biasing potential \(E_{bias}\) was applied the keep two molecules in place. 

\(E_{bias} = \frac{1}{2}\cdot K \cdot (R - R_0)^2\)

The parameters of the ligands were taken from OpenFF while GLYCAM were used for the host bCD. All of it were applied in Python and the OpenMM framework. Starting parameters, pdb-, and sdf-files can be found in the start folder.

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