Application of DNA-Binding Protein Prediction Based on Graph Convolutional Network and Contact Map.

Nan Zhou,Qiming Fu,Yijie Ding,Yu Zhang,Weizhong Lu,Khac-Minh Thai,Hongjie Wu,Haiou Li

doi:10.1155/2022/9044793

Abstract

DNA contains the genetic information for the synthesis of proteins and RNA, and it is an indispensable substance in living organisms. DNA-binding proteins are an enzyme, which can bind with DNA to produce complex proteins, and play an important role in the functions of a variety of biological molecules. With the continuous development of deep learning, the introduction of deep learning into DNA-binding proteins for prediction is conducive to improving the speed and accuracy of DNA-binding protein recognition. In this study, the features and structures of proteins were used to obtain their representations through graph convolutional networks. A protein prediction model based on graph convolutional network and contact map was proposed. The method had some advantages by testing various indexes of PDB14189 and PDB2272 on the benchmark dataset.

Highlights

The sequence of a protein determines its structure and different structures determine different functions
The graph convolution network (GCN) model was based on its PyG implementation [24], PDB14189 was used for testing to find the optimal super parameters, and PDB2272 was used to test model performance
SN represents the percentage of correctly predicted positive samples, SP represents the percentage of correctly predicted negative samples, ACC represents the percentage of correctly predicted samples in total samples, and Matthews correlation coefficient (MCC) represents the prediction quality of the binary classification model, with a range of 1⁄2−1, 1

Summary

Introduction

The sequence of a protein determines its structure and different structures determine different functions. There is about 18% of the weight of protein in the human body. As the carrier of life, it plays a very important role in human production and life. As a major component of life, proteins are involved in almost all activities of cells, including DNA replication and transcription, chromatin formation, cell growth, and a series of activities, all of which cannot be separated by specific proteins [1]. These proteins that bind to and interact with DNA are called DNA-binding proteins. DNAbinding proteins are called helical instability proteins, single-stranded DNA-binding proteins [2]

Methods

Results

Conclusion