Identifying protein-protein interface via a novel multi-scale local sequence and structural representation
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Related Research Unit(s)
|Journal / Publication||BMC Bioinformatics|
|Issue number||Supplement 15|
|Online published||24 Dec 2019|
|Publication status||Published - 2019|
Publisher's Copyright Statement
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-85077109997&origin=recordpage|
Results: In this paper, we obtain the local information on protein-protein interface, through multi-scale local average block and hexagon structure construction. Given a pair of proteins, we use a trained support vector regression (SVR) model to select best configurations. On Benchmark v4.0, our method achieves average Irmsd value of 3.28Å and overall Fnat value of 63%, which improves upon Irmsd of 3.89Å and Fnat of 49% for ZRANK, and Irmsd of 3.99Å and Fnat of 46% for ClusPro. On CAPRI targets, our method achieves average Irmsd value of 3.45Å and overall Fnat value of 46%, which improves upon Irmsd of 4.18Å and Fnat of 40% for ZRANK, and Irmsd of 5.12Å and Fnat of 32% for ClusPro. The success rates by our method, FRODOCK 2.0, InterEvDock and SnapDock on Benchmark v4.0 are 41.5%, 29.0%, 29.4% and 37.0%, respectively.
Conclusion: Experiments show that our method performs better than some state-of-the-art methods, based on the prediction quality improved in terms of CAPRI evaluation criteria. All these results demonstrate that our method is a valuable technological tool for identifying protein-protein interface.
- Hexagon structure construction, Multi-scale local average block, Protein-protein interface
Identifying protein-protein interface via a novel multi-scale local sequence and structural representation. / Guo, Fei; Zou, Quan; Yang, Guang; Wang, Dan; Tang, Jijun; Xu, Junhai.In: BMC Bioinformatics, Vol. 20, No. Supplement 15, 483, 2019.