In Silico Fold-Switching Protein Design Driven by Cα-Based Statistical Potential.

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Bondeepa Saikia,Anupaul Baruah
{"title":"In Silico Fold-Switching Protein Design Driven by Cα-Based Statistical Potential.","authors":"Bondeepa Saikia,Anupaul Baruah","doi":"10.1021/acs.jcim.5c01435","DOIUrl":null,"url":null,"abstract":"Structural plasticity of naturally occurring proteins allows them to change their shape in response to environmental factors such as pH, temperature, or binding partners. This ability to adopt different conformations is essential for many biological processes. While computational methods have been applied to design and redesign protein sequences that fold to a single ordered and stable state, the computational design of protein sequences with high sequence similarity that adopt well-defined but structurally divergent structures remains an outstanding challenge. Here, we designed 28 pairs of sequences using Monte Carlo simulation, denoted as (a1, b1), (a2, b2), (a3, b3), ..., (a28, b28), where ai and bi represent sequences adopting the 3-α fold and 4β + α fold, respectively. Among these, we identified three sets of fold-switching protein sequences, (a1, b1), (a2, b2), and (a3, b3): one with 89.29% sequence similarity and two others with 87.50% sequence similarity. This reflects the ability of statistical potential to finely balance competing structural constraints. The designed sequences differ by only few residues; however, they possess different tertiary structures: a 3-α helix fold and a 4β + α fold. In addition, sequence variants for a1, a2, and a3 are also designed using rational design guided by sequence analysis, and the results show striking outcomes: single point mutations, specifically D26C or A39F in a1, are sufficient to induce fold switching from the 3-α fold to the 4β + α fold while maintaining 98% sequence similarity with the parent sequence. Together, these findings suggest that the design approach is successful in designing fold-switching sequences that are compatible with their respective target structures. This work also ensures that the developed one-body and two-body statistical potentials are successful in designing protein sequences that exhibit fold conservation and the fold-switching phenomenon, as well as stability at the respective target structures.","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":"102 1","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jcim.5c01435","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

Abstract

Structural plasticity of naturally occurring proteins allows them to change their shape in response to environmental factors such as pH, temperature, or binding partners. This ability to adopt different conformations is essential for many biological processes. While computational methods have been applied to design and redesign protein sequences that fold to a single ordered and stable state, the computational design of protein sequences with high sequence similarity that adopt well-defined but structurally divergent structures remains an outstanding challenge. Here, we designed 28 pairs of sequences using Monte Carlo simulation, denoted as (a1, b1), (a2, b2), (a3, b3), ..., (a28, b28), where ai and bi represent sequences adopting the 3-α fold and 4β + α fold, respectively. Among these, we identified three sets of fold-switching protein sequences, (a1, b1), (a2, b2), and (a3, b3): one with 89.29% sequence similarity and two others with 87.50% sequence similarity. This reflects the ability of statistical potential to finely balance competing structural constraints. The designed sequences differ by only few residues; however, they possess different tertiary structures: a 3-α helix fold and a 4β + α fold. In addition, sequence variants for a1, a2, and a3 are also designed using rational design guided by sequence analysis, and the results show striking outcomes: single point mutations, specifically D26C or A39F in a1, are sufficient to induce fold switching from the 3-α fold to the 4β + α fold while maintaining 98% sequence similarity with the parent sequence. Together, these findings suggest that the design approach is successful in designing fold-switching sequences that are compatible with their respective target structures. This work also ensures that the developed one-body and two-body statistical potentials are successful in designing protein sequences that exhibit fold conservation and the fold-switching phenomenon, as well as stability at the respective target structures.
基于c α统计势的折叠开关蛋白设计
天然蛋白质的结构可塑性使它们能够根据pH值、温度或结合伙伴等环境因素改变形状。这种采用不同构象的能力对于许多生物过程是必不可少的。虽然计算方法已被应用于设计和重新设计折叠成单一有序和稳定状态的蛋白质序列,但采用定义良好但结构不同的高序列相似性蛋白质序列的计算设计仍然是一个突出的挑战。本文采用蒙特卡罗模拟方法设计了28对序列,分别为(a1, b1), (a2, b2), (a3, b3),…, (a28, b28),其中ai和bi分别表示采用3-α折叠和4β + α折叠的序列。其中,我们鉴定出(a1, b1)、(a2, b2)和(a3, b3)三组折叠开关蛋白序列,其中一组序列相似性为89.29%,另外两组序列相似性为87.50%。这反映了统计潜力能够很好地平衡相互竞争的结构性约束。所设计的序列只相差几个残基;然而,它们具有不同的三级结构:3-α螺旋折叠和4β + α折叠。此外,在序列分析的指导下,利用理性设计方法设计了a1、a2和a3的序列变异,结果显示出惊人的结果:单点突变,特别是a1中的D26C或A39F,足以诱导从3-α折叠到4β + α折叠,同时与亲本序列保持98%的序列相似性。总之,这些发现表明,设计方法在设计折叠切换序列时是成功的,这些序列与它们各自的目标结构兼容。这项工作还确保了所开发的单体和双体统计势能够成功地设计出具有折叠守恒和折叠切换现象的蛋白质序列,以及在各自目标结构上的稳定性。
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
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
×
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:604180095
Book学术官方微信