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

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Author(s)

  • Fei Guo
  • Quan Zou
  • Guang Yang
  • Jijun Tang
  • Junhai Xu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number483
Journal / PublicationBMC Bioinformatics
Volume20
Issue numberSupplement 15
Online published24 Dec 2019
Publication statusPublished - 2019

Abstract

Background: Protein-protein interaction plays a key role in a multitude of biological processes, such as signal transduction, de novo drug design, immune responses, and enzymatic activities. Gaining insights of various binding abilities can deepen our understanding of the interaction. It is of great interest to understand how proteins in a complex interact with each other. Many efficient methods have been developed for identifying protein-protein interface. 
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.

Research Area(s)

  • Hexagon structure construction, Multi-scale local average block, Protein-protein interface

Citation Format(s)

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.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal