Name
Title | ||
|---|---|---|
Phosphate binding sites prediction in phosphorylation-dependent protein-protein interactions |
Abstract | ||
|---|---|---|
Motivation: Phosphate binding plays an important role in modulating protein-protein interactions, which are ubiquitous in various biological processes. Accurate prediction of phosphate binding sites is an important but challenging task. Small size and diversity of phosphate binding sites lead to a substantial challenge for developing accurate prediction methods. Results: Here, we present the phosphate binding site predictor (PBSP), a novel and accurate approach to identifying phosphate binding sites from protein structures. PBSP combines an energy-based ligand-binding sites identification method with reverse focused docking using a phosphate probe. We show that PBSP outperforms not only general ligand binding sites predictors but also other existing phospholigand-specific binding sites predictors. It achieves similar to 95% success rate for top 10 predicted sites with an average Matthews correlation coefficient value of 0.84 for successful predictions. PBSP can accurately predict phosphate binding modes, with average position error of 1.4 and 2.4 angstrom in bound and unbound datasets, respectively. Lastly, visual inspection of the predictions is conducted. Reasons for failed predictions are further analyzed and possible ways to improve the performance are provided. These results demonstrate a novel and accurate approach to phosphate binding sites identification in protein structures. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/bioinformatics/btab525 | BIOINFORMATICS |
DocType | Volume | Issue |
Conference | 37 | 24 |
ISSN | Citations | PageRank |
1367-4803 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zheng-Chang Lu | 1 | 0 | 0.34 |
| Fan Jiang | 2 | 0 | 0.68 |
| Yun-Dong Wu | 3 | 8 | 3.43 |