PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions.

IF 4.5 3区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Protein Science Pub Date : 2025-01-01 DOI:10.1002/pro.70004
Jackson C Halpin, Amy E Keating
{"title":"PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions.","authors":"Jackson C Halpin, Amy E Keating","doi":"10.1002/pro.70004","DOIUrl":null,"url":null,"abstract":"<p><p>Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. To understand the features of SLiMs that are important for binding and to identify motif instances that are important for biological function, it is useful to examine the evolutionary conservation of motifs across homologous proteins. However, the intrinsically disordered regions (IDRs) in which SLiMs reside evolve rapidly. Consequently, multiple sequence alignment (MSA) of IDRs often misaligns SLiMs and underestimates their conservation. We present PairK (pairwise k-mer alignment), an MSA-free method to align and quantify the relative local conservation of subsequences within an IDR. Lacking a ground truth for conservation, we tested PairK on the task of distinguishing biologically important motif instances from background motifs, under the assumption that biologically important motifs are more conserved. The method outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that some SLiMs are more conserved than MSA-based metrics imply. PairK is available as an open-source python package at https://github.com/jacksonh1/pairk. It is designed to be easily adapted for use with other SLiM tools and for diverse applications.</p>","PeriodicalId":20761,"journal":{"name":"Protein Science","volume":"34 1","pages":"e70004"},"PeriodicalIF":4.5000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11669117/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Protein Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pro.70004","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. To understand the features of SLiMs that are important for binding and to identify motif instances that are important for biological function, it is useful to examine the evolutionary conservation of motifs across homologous proteins. However, the intrinsically disordered regions (IDRs) in which SLiMs reside evolve rapidly. Consequently, multiple sequence alignment (MSA) of IDRs often misaligns SLiMs and underestimates their conservation. We present PairK (pairwise k-mer alignment), an MSA-free method to align and quantify the relative local conservation of subsequences within an IDR. Lacking a ground truth for conservation, we tested PairK on the task of distinguishing biologically important motif instances from background motifs, under the assumption that biologically important motifs are more conserved. The method outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that some SLiMs are more conserved than MSA-based metrics imply. PairK is available as an open-source python package at https://github.com/jacksonh1/pairk. It is designed to be easily adapted for use with other SLiM tools and for diverse applications.

PairK:对k-mer比对,用于定量无序区域的蛋白基序保护。
蛋白质之间的相互作用通常是由一个模块肽识别结构域结合到另一个蛋白质的无序区域的短线性基序(SLiM)来介导的。为了了解对结合很重要的slim特征,并确定对生物功能很重要的基序实例,检查同源蛋白中基序的进化守恒是有用的。然而,slim所在的内在无序区(idr)发展迅速。因此,idr的多序列比对(MSA)往往对slm不正确,低估了它们的保守性。我们提出了PairK(成对k-mer对齐),这是一种无msa的方法,用于对齐和量化IDR内子序列的相对局部守恒。由于缺乏保护的基本真理,我们在区分生物学上重要的基序实例和背景基序的任务上测试了PairK,假设生物学上重要的基序更保守。该方法优于标准的基于msa的保护评分和现代基于llm的保护评分预测器。与msa相比,PairK可以在更宽的系统发育距离上量化保守性,这表明一些slm比基于msa的指标所暗示的更为保守。PairK是一个开源python包,可在https://github.com/jacksonh1/pairk上获得。它的设计很容易适应与其他SLiM工具和各种应用程序一起使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Protein Science
Protein Science 生物-生化与分子生物学
CiteScore
12.40
自引率
1.20%
发文量
246
审稿时长
1 months
期刊介绍: Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution. Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics. The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication. Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信