PSICalc: a novel approach to identifying and ranking critical non-proximal interdependencies within the overall protein structure

Author:

Townsley Thomas D12ORCID,Wilson James T2,Akers Harrison2,Bryant Timothy2,Cordova Salvador3,Wallace T L14,Durston Kirk K5,Deweese Joseph E267ORCID

Affiliation:

1. Department of Computational Sciences, College of Computing & Technology, Lipscomb University , Nashville, TN 37204, USA

2. Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Lipscomb University , Nashville, TN 37204, USA

3. FMS Foundation , Canandaigua, NY 14424, USA

4. School of Applied Computational Sciences, Department of Biomedical Data Science, Meharry Medical College , Nashville, TN 37208, USA

5. Department of Research and Publications, Digital Strategies , Langley, BC V2Y 1N5, Canada

6. Department of Biological, Physical, and Human Sciences, Freed-Hardeman University , Henderson, TN 38340, USA

7. Department of Biochemistry, Vanderbilt University School of Medicine , Nashville, TN 37232, USA

Abstract

Abstract Motivation AlphaFold has been a major advance in predicting protein structure, but still leaves the problem of determining which sub-molecular components of a protein are essential for it to carry out its function within the cell. Direct coupling analysis predicts two- and three-amino acid contacts, but there may be essential interdependencies that are not proximal within the 3D structure. The problem to be addressed is to design a computational method that locates and ranks essential non-proximal interdependencies within a protein involving five or more amino acids, using large, multiple sequence alignments (MSAs) for both globular and intrinsically unstructured proteins. Results We developed PSICalc (Protein Subdomain Interdependency Calculator), a laptop-friendly, pattern-discovery, bioinformatics software tool that analyzes large MSAs for both structured and unstructured proteins, locates both proximal and non-proximal inter-dependent sites, and clusters them into pairwise (second order), third-order and higher-order clusters using a k-modes approach, and provides ranked results within minutes. To aid in visualizing these interdependencies, we developed a graphical user interface that displays these subdomain relationships as a polytree graph. To demonstrate, we provide examples of both proximal and non-proximal interdependencies documented for eukaryotic topoisomerase II including between the unstructured C-terminal domain and the N-terminal domain. Availability and implementation https://github.com/jdeweeselab/psicalc-package Supplementary information Supplementary data are available at Bioinformatics Advances online.

Funder

Lipscomb University College of Pharmacy and Health Sciences, College of Computing and Technology

Center for Science and Culture, FMS Foundation

Freed-Hardeman University

Publisher

Oxford University Press (OUP)

Subject

Cell Biology,Developmental Biology,Embryology,Anatomy

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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