期刊
STRUCTURE
卷 24, 期 10, 页码 1842-1853出版社
CELL PRESS
DOI: 10.1016/j.str.2016.07.021
关键词
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资金
- NSF CAREER Award [DBI-0953839]
- NIH [R01GM109980]
- Div Of Biological Infrastructure
- Direct For Biological Sciences [0953839] Funding Source: National Science Foundation
Protein-peptide interactions play an important role in many cellular processes. In silico prediction of protein-peptide complex structure is highly desirable for mechanistic investigation of these processes and for therapeutic design. However, predicting all-atom structures of protein-peptide complexes without any knowledge about the peptide binding site and the bound peptide conformation remains a big challenge. Here, we present a docking-based method for predicting protein-peptide complex structures, referred to as MDockPeP, which starts with the peptide sequence and globally docks the all-atom, flexible peptide onto the protein structure. MDockPeP was tested on the peptiDB bench-marking database using both bound and unbound protein structures. The results show that MDockPeP successfully generated near-native peptide binding modes in 95.0% of the bound docking cases and in 92.2% of the unbound docking cases. The performance is significantly better than other existing docking methods. MDockPeP is computationally efficient and suitable for large-scale applications.
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