伦敦大学学院Joseph C. F. Ng小组近日取得一项新成果。经过不懈努力，他们揭示了ImmunoMatch学习并预测重、轻免疫球蛋白链的同源配对。2025年11月18日，国际知名学术期刊《自然—方法学》发表了这一成果。

该课题组人员提出了ImmunoMatch，这是一个机器学习框架，对来自人类B细胞的配对H和L序列进行训练，以识别链相容性的分子特征。ImmunoMatch区分同源和随机H-L对，并捕获与κ和λ轻链相关的差异，反映骨髓中B细胞的选择机制。研究人员利用ImmunoMatch从空间VDJ测序数据中重构成对抗体，并研究健康和疾病B细胞成熟阶段H-L配对的细化。该研究组进一步发现ImmunoMatch对H-L界面的序列差异敏感。这些见解为控制抗体组装和稳定性的更广泛的生物学原理提供了计算视角。

据悉，由兼容的重(H)和轻(L)链对形成的稳定抗体的发展对于抗体产生细胞的体内成熟和治疗性抗体的体外设计都是至关重要的。

附：英文原文

Title: ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains

Author: Guo, Dongjun, Dunn-Walters, Deborah K., Fraternali, Franca, Ng, Joseph C. F.

Issue&Volume: 2025-11-18

Abstract: The development of stable antibodies formed by compatible heavy (H) and light (L) chain pairs is crucial in both in vivo maturation of antibody-producing cells and ex vivo designs of therapeutic antibodies. We present ImmunoMatch, a machine-learning framework trained on paired H and L sequences from human B cells to identify molecular features underlying chain compatibility. ImmunoMatch distinguishes cognate from random H–L pairs and captures differences associated with κ and λ light chains, reflecting B cell selection mechanisms in the bone marrow. We apply ImmunoMatch to reconstruct paired antibodies from spatial VDJ sequencing data and study the refinement of H–L pairing across B cell maturation stages in health and disease. We find further that ImmunoMatch is sensitive to sequence differences at the H–L interface. These insights provide a computational lens into the broader biological principles governing antibody assembly and stability.

DOI: 10.1038/s41592-025-02913-x

Source: https://www.nature.com/articles/s41592-025-02913-x