Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints.

ABSTRACT:

Background

In structure-based drug design, binding affinity prediction remains as a challenging goal for current scoring functions. Development of target-biased scoring functions provides a new possibility for tackling this problem, but this approach is also associated with certain technical difficulties. We previously reported the Knowledge-Guided Scoring (KGS) method as an alternative approach (BMC Bioinformatics, 2010, 11, 193-208). The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding data of an appropriate reference complex, so the error in binding affinity prediction can be reduced effectively.

Results

In this study, we have developed an upgraded version, i.e. KGS2, by employing 3D protein-ligand interaction finger

SUBMITTER: Liu J 

PROVIDER: S-EPMC5516336 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature