AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering
AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering
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DOI：
10.1101/2023.04.28.538712
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发表时间：
2023-09
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影响因子：
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通讯作者：
Aubin Ramon;Montader Ali;Misha Atkinson;Alessio Saturnino;Kieran Didi;Cristina Visentin;Stefano Ricagno;Xing Xu;Matthew Greenig;Pietro Sormanni
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作者：
Aubin Ramon;Montader Ali;Misha Atkinson;Alessio Saturnino;Kieran Didi;Cristina Visentin;Stefano Ricagno;Xing Xu;Matthew Greenig;Pietro Sormanni
单抗已经成为关键的治疗药物，随着2019年第一种纳米体药物的批准，纳米体的势头正在迅速增强。尽管如此，这些生物制剂作为治疗药物的开发仍然是一个挑战。尽管已建立的体外定向进化技术相对快速且部署成本较低，但产生治疗性抗体的黄金标准仍然是从动物免疫或患者中发现。免疫系统衍生的抗体在体内往往具有良好的性质，包括较长的半衰期，与自身抗原的低反应性，以及低毒性。在这里，我们介绍了AbNatiV，一个深度学习工具，用于评估抗体和纳米体的原生性，即它们属于免疫系统来源的人类抗体或骆驼纳米体分布的可能性。AbNatiV是一个多用途的工具，可以准确地预测来自任何来源的FV序列的原生性，包括合成库和计算设计。它提供了一个可解释的分数来预测免疫原性的可能性，以及一个残基水平的概况，可以指导抗体和纳米体的工程设计，这些抗体和纳米体与免疫系统衍生的抗体和纳米体没有区别。我们进一步介绍了一种自动化的人性化管道，我们将其应用于两个纳米实体。湿法实验室实验表明，与依赖传统结构和残基频率分析的人源化纳米体不同，AbNatiV人源化纳米体保持了与野生型相当或更好的结合和稳定性。我们将AbNatiV作为可下载软件和网络服务器提供。
Monoclonal antibodies have emerged as key therapeutics, and nanobodies are rapidly gaining momentum following the approval of the first nanobody drug in 2019. Nonetheless, the development of these biologics as therapeutics remains a challenge. Despite the availability of established in vitro directed evolution technologies that are relatively fast and cheap to deploy, the gold standard for generating therapeutic antibodies remains discovery from animal immunization or patients. Immune-system derived antibodies tend to have favourable properties in vivo, including long half-life, low reactivity with self-antigens, and low toxicity. Here, we present AbNatiV, a deep-learning tool for assessing the nativeness of antibodies and nanobodies, i.e., their likelihood of belonging to the distribution of immune-system derived human antibodies or camelid nanobodies. AbNatiV is a multi-purpose tool that accurately predicts the nativeness of Fv sequences from any source, including synthetic libraries and computational design. It provides an interpretable score that predicts the likelihood of immunogenicity, and a residue-level profile that can guide the engineering of antibodies and nanobodies indistinguishable from immune-system-derived ones. We further introduce an automated humanisation pipeline, which we applied to two nanobodies. Wet-lab experiments show that AbNatiV-humanized nanobodies retain binding and stability at par or better than their wild type, unlike nanobodies humanised relying on conventional structural and residue-frequency analysis. We make AbNatiV available as downloadable software and as a webserver.