Use Chou’s 5-Step Rule to Predict DNA-Binding Proteins with Evolutionary Information

Author:

Lu Weizhong12ORCID,Song Zhengwei1,Ding Yijie12ORCID,Wu Hongjie12ORCID,Cao Yan1,Zhang Yu3,Li Haiou1

Affiliation:

1. School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China

2. Suzhou Key Laboratory of Virtual Reality Intelligent Interaction and Application Technology, Suzhou University of Science and Technology, Suzhou 215009, China

3. Suzhou Industrial Park Institute of Services Outsourcing, Suzhou 215123, China

Abstract

The knowledge of DNA-binding proteins would help to understand the functions of proteins better in cellular biological processes. Research on the prediction of DNA-binding proteins can promote the research of drug proteins and computer acidified drugs. In recent years, methods based on machine learning are usually used to predict proteins. Although great predicted performance can be achieved via current methods, researchers still need to invest more research in terms of the improvement of predicted performance. In this study, the prediction of DNA-binding proteins is studied from the perspective of evolutionary information and the support vector machine method. One machine learning model for predicting DNA-binding proteins based on evolutionary features by using Chou’s 5-step rule is put forward. The results show that great predicted performance is obtained on benchmark dataset PDB1075 and independent dataset PDB186, achieving the accuracy of 86.05% and 75.30%, respectively. Thus, the method proposed is comparable to a certain degree, and it may work even better than other methods to some extent.

Funder

Suzhou Science and Technology Project

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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