Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK.
Master in Bioinformatics for Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
Nat Commun. 2023 Apr 6;14(1):1937. doi: 10.1038/s41467-023-37668-6.
Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
生物制剂，如抗体和酶，在研究、生物技术、诊断和治疗中至关重要。通常，具有合适功能的生物制剂被发现，但由于可开发性问题，其开发受到阻碍。稳定性和溶解度是支持可开发性潜力的关键生物物理特性，因为它们决定了聚集，与生产产量和多特异性相关，并且对于获得肠外和口服递送至关重要。虽然已经取得了优化个别特性的进展，但多个特性的协同优化仍然非常困难且耗时，因为改善一种特性的突变往往会对其他特性产生负面影响。在这项工作中，我们引入了一种完全自动化的计算策略，用于同时优化构象稳定性和溶解度，我们在六个抗体上进行了实验验证，包括两种已批准的治疗药物。我们在 42 个设计上的结果表明，该计算程序在提高可开发性潜力方面非常有效，同时不影响抗原结合。我们将该方法作为一个网络服务器提供，网址为www-cohsoftware.ch.cam.ac.uk。
