hAb-Convergent: an antibody rearrangement analysis system for therapeutic antibody engineering based on convergent evolution.

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jinfeng Wang,Xiaomeng Ge,Qinglan Sun,Minlong Chen,Shijie Qin,Dongmei Liu,Tao Deng,Juncai Ma,Songnian Hu,Ronghua Jin,Zhou Tong,Linhuan Wu
{"title":"hAb-Convergent: an antibody rearrangement analysis system for therapeutic antibody engineering based on convergent evolution.","authors":"Jinfeng Wang,Xiaomeng Ge,Qinglan Sun,Minlong Chen,Shijie Qin,Dongmei Liu,Tao Deng,Juncai Ma,Songnian Hu,Ronghua Jin,Zhou Tong,Linhuan Wu","doi":"10.1093/nar/gkaf407","DOIUrl":null,"url":null,"abstract":"In therapeutic antibody engineering, utilizing naturally occurring mutations in the human body as a reference for modification is an emerging trend. The theory of convergent evolution presents a viable solution. Nevertheless, the nonuniformity of the antibody rearrangement analysis system and the difficulty in identifying the heavy-chain D-region are significant challenges to research and application. To address these limitations, we developed hAb (human antibody)-Convergent, a novel tool designed to assist users in quickly identifying candidate mutation hotspots of input antibody sequences in real human immune responses for subsequent antibody engineering. It uses antibody rearrangement features-based (V, D, J genes and CDR-H3 length) rather than traditional sequence-based strategies while ensuring the security of the original sequence. Combining more inclusive D-region identification and analysis methods, it can recognize and analyze the convergence of antibodies across various individuals. Additionally, given the limitations of obtaining antibody nucleotide sequences from academic literature, it provides an optimized approach for direct analysis and rapid comparison using amino acid sequences. hAb-Convergent bridges gaps in antibody engineering by linking natural evolution patterns to in vitro design, with implications for universal vaccine development. The tool can be freely accessed at https://nmdc.cn/zoe/.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"4 1","pages":""},"PeriodicalIF":16.6000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleic Acids Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/nar/gkaf407","RegionNum":2,"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

In therapeutic antibody engineering, utilizing naturally occurring mutations in the human body as a reference for modification is an emerging trend. The theory of convergent evolution presents a viable solution. Nevertheless, the nonuniformity of the antibody rearrangement analysis system and the difficulty in identifying the heavy-chain D-region are significant challenges to research and application. To address these limitations, we developed hAb (human antibody)-Convergent, a novel tool designed to assist users in quickly identifying candidate mutation hotspots of input antibody sequences in real human immune responses for subsequent antibody engineering. It uses antibody rearrangement features-based (V, D, J genes and CDR-H3 length) rather than traditional sequence-based strategies while ensuring the security of the original sequence. Combining more inclusive D-region identification and analysis methods, it can recognize and analyze the convergence of antibodies across various individuals. Additionally, given the limitations of obtaining antibody nucleotide sequences from academic literature, it provides an optimized approach for direct analysis and rapid comparison using amino acid sequences. hAb-Convergent bridges gaps in antibody engineering by linking natural evolution patterns to in vitro design, with implications for universal vaccine development. The tool can be freely accessed at https://nmdc.cn/zoe/.
hAb-Convergent:基于收敛进化的治疗性抗体工程抗体重排分析系统。
在治疗性抗体工程中,利用人体内自然发生的突变作为修饰的参考是一个新兴的趋势。收敛进化理论给出了一个可行的解决方案。然而,抗体重排分析系统的不均匀性和重链d区识别的困难是研究和应用的重大挑战。为了解决这些限制,我们开发了hAb(人抗体)-Convergent,这是一种新颖的工具,旨在帮助用户快速识别真实人类免疫反应中输入抗体序列的候选突变热点,以便后续的抗体工程。它采用基于抗体重排特征(V、D、J基因和CDR-H3长度)而不是传统的基于序列的策略,同时保证了原始序列的安全性。结合更具包容性的d区识别和分析方法,可以识别和分析不同个体之间的抗体趋同。此外,考虑到从学术文献中获取抗体核苷酸序列的局限性,它为使用氨基酸序列进行直接分析和快速比较提供了一种优化的方法。hAb-Convergent通过将自然进化模式与体外设计联系起来,填补了抗体工程方面的空白,对通用疫苗开发具有重要意义。该工具可在https://nmdc.cn/zoe/免费访问。
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
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
×
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