Identification of Disordered Regions of Intrinsically Disordered Proteins by Multi-features Fusion

Author:

Canzhuang Sun1,Yonge Feng1

Affiliation:

1. College of Science, Inner Mongolia Agriculture University, Hohhot 010018, China

Abstract

Background: Intrinsically disordered proteins lack a well-defined three-dimensional structure under physiological conditions. They have performed multiple functions in life activities and are closely related to many human diseases. The identification of the disordered region of intrinsically disordered proteins is important to protein function annotation. Objective: To accurately identify the disordered regions in intrinsically disordered proteins. Methods: In this study, we constructed a multi-feature fusion model based on a support vector machine to predict disordered regions of intrinsically disordered proteins from the DisPort database. We extracted codons usage frequencies, GC content, protein secondary structure components, hydrophilic-hydrophobic amino acid components, and chemical shifts as features to predict the disordered regions of intrinsically disordered proteins. Results: The best accuracy is 82.098% by using codon frequencies in single feature prediction. In order to improve the performance, we fused these features and obtained the best result of 83.173% in combining codons frequencies with chemical shifts as the feature. Conclusion: The results show that our model has achieved a good prediction result in predicting disordered regions of intrinsically disordered proteins-moreover, the performances of our model are better than those of existing methods.

Funder

Inner Mongolia Autonomous Region Graduate Education Reform Project

Publisher

Bentham Science Publishers Ltd.

Subject

Computational Mathematics,Genetics,Molecular Biology,Biochemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3