Citation: Shi-Ming Peng, Yu Zhou, Niu Huang. Improving the accuracy of pose prediction in molecular docking via structural filtering and conformational clustering[J]. Chinese Chemical Letters, ;2013, 24(11): 1001-1004. shu

Improving the accuracy of pose prediction in molecular docking via structural filtering and conformational clustering

Shi-Ming Peng ^a,c ,
Yu Zhou ^b,c ,
Niu Huang ^c,,

1.
a College of Biological Sciences, China Agricultural University, Beijing 100193, China;
2.
b College of Life Sciences, Beijing Normal University, Beijing 100875, China;
3.
c National Institute of Biological Sciences, Beijing 102206, China

Corresponding author: Niu Huang,
Received Date: 7 March 2013
Available Online: 27 May 2013

Structure-based virtual screening (molecular docking) is now one of the most pragmatic techniques to leverage target structure for ligand discovery. Accurate binding pose prediction is critical to molecular docking. Here, we describe a general strategy to improve the accuracy of docking pose prediction by implementing the structural descriptor-based filtering and KGS-penalty function-based conformational clustering in an unbiased manner. We assessed our method against 150 high-quality protein-ligand complex structures. Surprisingly, such simple components are sufficient to improve the accuracy of docking pose prediction. The success rate of predicting near-native docking pose increased from 53% of the targets to 78%. We expect that our strategymay have general usage in improving currently available molecular docking programs.
- Molecular docking,
- Pose prediction,
- Structural descriptor,
- Conformational clustering
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沈阳化工大学材料科学与工程学院沈阳 110142