RF-Score: A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
Please feel free to use RF-Score. It is free of charge to all users and we hope that the community enjoys using it.
We thank the Biotechnology and Biological Sciences Research Council (grant BB/G000247/1) for funding this work.
We also thank SULSA for funding.
Download a zip file containing the RF-Score scripts and programs.
To learn how to use RF-Score, please read the following instructions:
Instructions to reproduce RF-Score performance on PDBbind benchmark
Instructions to re-score other sets of complexes with RF-Score
These instructions appear as Supporting Information associated with the publication describing RF-Score, which should be cited if you use RF-Score in published work:A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking
P.J. Ballester & J.B.O. Mitchell,
Bioinformatics, 26, 1169-1175 (2010)
doi: 10.1093/bioinformatics/btq112
PMID 20236947
RF-Score by Pedro Ballester & John Mitchell is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
Based on a work at chemistry.st-andrews.ac.uk.
Permissions beyond the scope of this license may be available at http://chemistry.st-andrews.ac.uk/staff/jbom/group/RF-Score.html.