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通过对天然配对的人类抗体序列和结构数据的大规模分析揭示的保守重链/轻链接触和种系偏好。

Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.

作者信息

Dudzic Pawel, Chomicz Dawid, Bielska Weronika, Jaszczyszyn Igor, Zieliński Michał, Janusz Bartosz, Wróbel Sonia, Le Pannérer Marguerite-Marie, Philips Andrew, Ponraj Prabakaran, Kumar Sandeep, Krawczyk Konrad

机构信息

NaturalAntibody, Szczecin, Poland.

Sanofi, Babraham Research Campus, Cambridge, UK.

出版信息

Commun Biol. 2025 Jul 26;8(1):1110. doi: 10.1038/s42003-025-08388-y.

DOI:10.1038/s42003-025-08388-y
PMID:40715549
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12297541/
Abstract

Understanding the pairing preferences and structural interactions between antibody heavy and light chains can enhance our ability to design more effective and specific therapeutic antibodies. Insights from natural antibody repertoires and conserved contact sites help reduce autoreactivity and improve drug safety and efficacy. Current databases represent only a limited portion of the estimated diversity of unique paired antibody molecules. To address this, we introduce PairedAbNGS, a novel database with paired heavy/light antibody chains. To our knowledge, this is the largest resource for paired natural antibody sequences with 58 bioprojects and over 14 million assembled productive sequences. Using this dataset, we investigated heavy and light chain variable (V) gene pairing preferences and found significant biases beyond gene usage frequencies, possibly due to receptor editing favoring less autoreactive combinations. Analyzing the available antibody structures from the Protein Data Bank, we studied conserved contact residues between heavy and light chains, particularly interactions between the CDR3 region of one chain and the FWR2 region of the opposite chain. Examination of amino acid pairs at key contact sites revealed significant deviations of amino acids distributions compared to random pairings, in the heavy chain's CDR3 region contacting the opposite chain, indicating specific interactions might be crucial for proper chain pairing. This observation is further reinforced by preferential IGHV-IGLJ and IGLV-IGHJ pairing preferences. We hope that both our resources and the findings would contribute to improving the engineering of biological drugs. We make the database accessible at https://naturalantibody.com/paired-ab-ngs as a valuable tool for biological and machine-learning applications.

摘要

了解抗体重链和轻链之间的配对偏好和结构相互作用,能够增强我们设计更有效、更具特异性治疗性抗体的能力。天然抗体库和保守接触位点的相关见解有助于降低自身反应性,提高药物安全性和疗效。目前的数据库仅涵盖了估计的独特配对抗体分子多样性的有限部分。为了解决这一问题,我们引入了PairedAbNGS,这是一个包含配对重/轻抗体链的新型数据库。据我们所知,这是最大的配对天然抗体序列资源库,包含58个生物项目和超过1400万个组装好的有效序列。利用这个数据集,我们研究了重链和轻链可变(V)基因的配对偏好,发现除了基因使用频率之外,还存在显著偏差,这可能是由于受体编辑倾向于较少的自身反应性组合。通过分析蛋白质数据库中现有的抗体结构,我们研究了重链和轻链之间保守的接触残基,特别是一条链的互补决定区3(CDR3)区域与另一条链的框架区2(FWR2)区域之间的相互作用。对关键接触位点的氨基酸对进行检查发现,与随机配对相比,在与相对链接触的重链CDR3区域中,氨基酸分布存在显著偏差,这表明特定的相互作用可能对正确的链配对至关重要。IGHV-IGLJ和IGLV-IGHJ的优先配对偏好进一步强化了这一观察结果。我们希望我们的资源和研究结果都能有助于改进生物药物的工程设计。我们将数据库发布在https://naturalantibody.com/paired-ab-ngs上,作为生物学和机器学习应用的宝贵工具。

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