Spatom: a graph neural network for structure-based protein–protein interaction site prediction

Author:

Wu Haonan12,Han Jiyun1,Zhang Shizhuo1,Xin Gaojia1,Mou Chaozhou1,Liu Juntao1

Affiliation:

1. School of Mathematics and Statistics, Shandong University , Weihai 264209 , China

2. School of Mathematics, Shandong University , Jinan 250100 , China

Abstract

Abstract Accurate identification of protein–protein interaction (PPI) sites remains a computational challenge. We propose Spatom, a novel framework for PPI site prediction. This framework first defines a weighted digraph for a protein structure to precisely characterize the spatial contacts of residues, then performs a weighted digraph convolution to aggregate both spatial local and global information and finally adds an improved graph attention layer to drive the predicted sites to form more continuous region(s). Spatom was tested on a diverse set of challenging protein–protein complexes and demonstrated the best performance among all the compared methods. Furthermore, when tested on multiple popular proteins in a case study, Spatom clearly identifies the interaction interfaces and captures the majority of hotspots. Spatom is expected to contribute to the understanding of protein interactions and drug designs targeting protein binding.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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