A new strategy to HER2-specific antibody discovery through artificial intelligence-powered phage display screening based on the Trastuzumab framework

IF 4.2 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochimica et biophysica acta. Molecular basis of disease Pub Date : 2025-06-01 Epub Date: 2025-03-07 DOI:10.1016/j.bbadis.2025.167772
Mancang Zhang , Qiangzhen Yang , Jiangrong Lou , Yang Hu , Yongyong Shi
{"title":"A new strategy to HER2-specific antibody discovery through artificial intelligence-powered phage display screening based on the Trastuzumab framework","authors":"Mancang Zhang ,&nbsp;Qiangzhen Yang ,&nbsp;Jiangrong Lou ,&nbsp;Yang Hu ,&nbsp;Yongyong Shi","doi":"10.1016/j.bbadis.2025.167772","DOIUrl":null,"url":null,"abstract":"<div><div>Human epidermal growth factor receptor 2 (HER2) is a recognized drug target, and it serves as a critical target for various cancer treatments, necessitating the discovery of more antibodies for therapeutic and detection purposes. Here, we have developed an innovative workflow for antibody generation through Artificial Intelligence-powered Phage Display Screening (AIPDS). This workflow integrates artificial intelligence-driven antibody CDRH3 sequence design, high-throughput DNA synthesis and phage display screening. We applied AIPDS workflow to generate promising antibodies against the human epidermal growth factor receptor 2 (HER2), offering a template for streamlined antibody generation. Seven novel antibodies stood out, demonstrating promising efficacy in various functional assays. Notably, DYHER2–02 demonstrates strong performance across all experimental tests. In summary, our study introduces a novel methodology to generate new antibody variants of an existing antibody using an AI-assisted phage display approach. These new antibody variants hold potential applications in research, diagnosis, and therapeutic applications.</div></div>","PeriodicalId":8821,"journal":{"name":"Biochimica et biophysica acta. Molecular basis of disease","volume":"1871 5","pages":"Article 167772"},"PeriodicalIF":4.2000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochimica et biophysica acta. Molecular basis of disease","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925443925001176","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/7 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Human epidermal growth factor receptor 2 (HER2) is a recognized drug target, and it serves as a critical target for various cancer treatments, necessitating the discovery of more antibodies for therapeutic and detection purposes. Here, we have developed an innovative workflow for antibody generation through Artificial Intelligence-powered Phage Display Screening (AIPDS). This workflow integrates artificial intelligence-driven antibody CDRH3 sequence design, high-throughput DNA synthesis and phage display screening. We applied AIPDS workflow to generate promising antibodies against the human epidermal growth factor receptor 2 (HER2), offering a template for streamlined antibody generation. Seven novel antibodies stood out, demonstrating promising efficacy in various functional assays. Notably, DYHER2–02 demonstrates strong performance across all experimental tests. In summary, our study introduces a novel methodology to generate new antibody variants of an existing antibody using an AI-assisted phage display approach. These new antibody variants hold potential applications in research, diagnosis, and therapeutic applications.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于曲妥珠单抗框架,通过人工智能驱动的噬菌体展示筛选发现her2特异性抗体的新策略
人表皮生长因子受体2 (HER2)是一个公认的药物靶点,是各种癌症治疗的关键靶点,需要发现更多的抗体用于治疗和检测目的。在这里,我们通过人工智能驱动的噬菌体显示筛选(AIPDS)开发了一种创新的抗体生成工作流程。该工作流程集成了人工智能驱动的抗体CDRH3序列设计、高通量DNA合成和噬菌体展示筛选。我们应用AIPDS工作流程生成了针对人表皮生长因子受体2 (HER2)的有希望的抗体,为流线型抗体生成提供了模板。7种新型抗体脱颖而出,在各种功能分析中显示出有希望的功效。值得注意的是,DYHER2-02在所有实验测试中表现出强大的性能。总之,我们的研究引入了一种新的方法,使用人工智能辅助噬菌体展示方法来产生现有抗体的新抗体变体。这些新的抗体变体在研究、诊断和治疗方面具有潜在的应用。
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 去求助
来源期刊
CiteScore
12.30
自引率
0.00%
发文量
218
审稿时长
32 days
期刊介绍: BBA Molecular Basis of Disease addresses the biochemistry and molecular genetics of disease processes and models of human disease. This journal covers aspects of aging, cancer, metabolic-, neurological-, and immunological-based disease. Manuscripts focused on using animal models to elucidate biochemical and mechanistic insight in each of these conditions, are particularly encouraged. Manuscripts should emphasize the underlying mechanisms of disease pathways and provide novel contributions to the understanding and/or treatment of these disorders. Highly descriptive and method development submissions may be declined without full review. The submission of uninvited reviews to BBA - Molecular Basis of Disease is strongly discouraged, and any such uninvited review should be accompanied by a coverletter outlining the compelling reasons why the review should be considered.
期刊最新文献
RTN4IP1 drives breast tumorigenesis: Molecular mechanisms linking elevated expression to enhanced proliferation, suppressed apoptosis, and therapeutic resistance The isoflavone metabolites, O-desmethylangolensin and (S)-equol, relax isolated arteries ex vivo and decrease arterial blood pressure in vivo PFKFB3-driven glycolysis in endothelial cells activates RhoA/ROCK1 to promote pulmonary vascular leakage in heatstroke Mitochondrial complex-derived ROS induces lysosomal dysfunction and impairs autophagic flux in human cells carrying the APOE4 allele BIRC3 and NOC2L synergistically promote P53 acetylation to accelerate necroptosis in sepsis-associated acute kidney injury
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1