Name
Title | ||
|---|---|---|
Correcting the impact of docking pose generation error on binding affinity prediction. |
Abstract | ||
|---|---|---|
Binding affinity prediction is often carried out on the docked pose of a known binder rather than its co-crystallised pose. Our results suggest than pose generation error is in general far less damaging for binding affinity prediction than it is currently believed. Another contribution of our study is the proposal of a procedure that largely corrects for this error. The resulting machine-learning scoring function is freely available at http://istar.cse.cuhk.edu.hk/rf-score-4.tgz and http://ballester.marseille.inserm.fr/rf-score-4.tgz . |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1169-4 | BMC Bioinformatics |
Keywords | Field | DocType |
Binding affinity,Drug discovery,Machine learning,Molecular docking | Docking (molecular),Lead Finder,Drug discovery,Ligand (biochemistry),Docking (dog),Computer science,Bioinformatics | Journal |
Volume | Issue | ISSN |
17 | S-11 | 1471-2105 |
Citations | PageRank | References |
2 | 0.36 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongjian Li | 1 | 64 | 6.26 |
| Kwong-Sak Leung | 2 | 1887 | 205.58 |
| Man Hon Wong | 3 | 814 | 233.13 |
| Pedro J. Ballester | 4 | 281 | 18.60 |