Antibody Discovery and Optimisation by Computational Design

由于它们能够紧密和特异地结合大多数分子靶点，抗体越来越多地被用于生物医学研究、诊断和医学，在这些领域，它们是增长最快的治疗类别。结构和生物数据库的大小和质量的快速激增使得引入创新的理性抗体设计的计算方法成为可能。拟议的研究的目标是通过使用包括基于片段的合理设计、人工智能方法的开发和部署、体外实验验证和体外亲和力成熟的多学科方法来开发和建立抗体发现和优化的新的计算技术。在计算机上的合理设计大大降低了为感兴趣的目标发现新抗体所需的时间和成本，而不是利用动物，并且能够更好地控制所获得的抗体的性质。例如，它允许获得与目标(抗原)内特定感兴趣区域(表位)结合的抗体，这对于已有的抗体发现技术来说仍然是一个关键的挑战，但对许多应用来说是关键的。计算设计还可以更好地控制抗体成功开发所必需的其他性质，包括稳定性和溶解性。这项拟议的研究代表着朝着建立计算设计作为产生新抗体的竞争技术的方向迈出了重要的一步。计算方法有望使可靠而廉价的一代药物能够对抗--以及研究--许多关键疾病。总体而言，这些方法提供的独特机会将能够解决新的问题，通过促进实验加速发现，简化治疗性抗体的开发，并为行业投资提供新的途径。

Because of their ability to bind most molecular targets tightly and specifically, antibodies are increasingly used in biomedical research, diagnostics, and medicine, where they are the fastest-growing class of therapeutics. The rapid surge in the size and quality of structural and biological databases is allowing to introduce innovative computational methods of rational antibody design.The goal of the proposed research is to develop and establish novel computational technologies of antibody discovery and optimisation, by using a multidisciplinary approach that encompasses fragment-based rational design, the development and deployment of artificial intelligence methods, in vitro experimental validation, and in vitro affinity maturation.Rational design at a computer substantially lowers the time and costs required to discover novel antibodies for a target of interest, does not exploit animals, and enables a much better control over the properties of the obtained antibodies. For example, it allows to obtain antibodies binding to specific regions of interest (epitopes) within the target (antigen), which remains a critical challenge with established technologies of antibody discovery, but is of key importance for many applications. Computational design also offers a better control over other properties essential for successful antibody development, including stability and solubility. The proposed research represents a significant step forward towards the establishment of computational design as a competitive technology for the generation of novel antibodies. Computational approaches promise to enable the reliable and inexpensive generation of drugs to combat - and tools to study - many crucial diseases. Overall, the unique opportunities offered by these approaches will enable to address new questions, accelerate discoveries by facilitating experiments, streamline therapeutic antibody development, and provide novel avenues for industry investment.