Computational methods for rapid structural modelling of antigen-antibody interactions to improve identification of antigen-specific antibodies from Ig

Lead Research Organisation: University of Oxford
Department Name: Statistics


The exquisite antigen recognition specificity of antibodies has made them useful as diagnostics, research agents and the most successful class of biopharmaceuticals. The ability to discover better antibody-based therapeutics needs knowledge of the 3D shape of individual antibodies within the context of the entire antibody repertoire. Next-generation sequencing methodologies (Ig-seq) can rapidly yield millions of antibody gene sequences. However, so far, the inability to routinely overlay antibody structure on large Ig-seq datasets has limited their potential for antibody drug discovery. In this project we will use computational methodologies to bridge between the two fields by allowing structural annotation of Ig-seq experiments which will pave the way for more advanced antibody-based therapeutics.
The project falls within the remit of the MRC delivery plan in both its connection to priority challenges (e.g. applications in serology and thus both outbreak control and in vaccine development, the latter of which will be realised through working with Oxford Vaccine Group, as well as accelerating discovery of antibody-based therapeutics) and its alignment with MRC skill priorities. The relevant MRC skill priorities are quantitative and interdisciplinary skills. The key quantitative skills of mathematics, statistics and computation are central to the project in the form of protein structure prediction. Structure prediction itself is interdisciplinary, drawing on chemistry, statistics and insight from the life sciences. Furthermore, the aim of the project is to connect these structural models, produced computationally, with the kind of large-scale and rapidly accruing sequence data that is at the focus of the MRC's research spotlight on informatics. Informatics and computation have been identified as key steps in the MRC's strategy for transforming health research, and thus the project, in linking high throughput sequence data to structural biology via computation, fits neatly into the MRC's initiative for biomedical informatics. The project is co-supervised and funded by Kymab.


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