p-IgGen:成对抗体生成语言模型

Oliver M Turnbull, Dino Oglic, Rebecca Croasdale-Wood, Charlotte M Deane
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引用次数: 0

摘要

摘要:抗体药物发现的一个关键挑战是设计出没有可开发性问题(如聚集、多特异性、表达能力差或溶解度低)的新型序列。在这里,我们介绍一种用于生成成对重链-轻链抗体的蛋白质语言模型 p-IgGen。该模型能生成具有天然抗体配对特性的多样化抗体样序列。我们还创建了一个经过微调的 p-IgGen 版本,该版本偏向于生成具有三维生物物理特性的抗体,这些特性在临床阶段的治疗性抗体中可以看到:模型和推理代码可在 www.github.com/oxpig/p-IgGen 免费获取。经过清理的训练数据存放在 doi.org/10.5281/zenodo.13880874。补充信息:补充数据可在 Bioinformatics online 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
p-IgGen: a paired antibody generative language model.

Summary: A key challenge in antibody drug discovery is designing novel sequences that are free from developability issues-such as aggregation, polyspecificity, poor expression, or low solubility. Here, we present p-IgGen, a protein language model for paired heavy-light chain antibody generation. The model generates diverse, antibody-like sequences with pairing properties found in natural antibodies. We also create a finetuned version of p-IgGen that biases the model to generate antibodies with 3D biophysical properties that fall within distributions seen in clinical-stage therapeutic antibodies.

Availability and implementation: The model and inference code are freely available at www.github.com/oxpig/p-IgGen. Cleaned training data are deposited at doi.org/10.5281/zenodo.13880874.

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