Predicting TCR structures and binding in-silico

T-cell receptors (TCRs) are the proteins that determine the immune response of T-cells to different antigen fragments presented by the major histocompatibility complex (MHC). The long-term goal of this project is to improve the state-of-the art for in-silico TCR-peptide MHC target prediction. TCRs are vital components of the immune system and can be synthetically engineered to promote immune responses against a multitude of diseases, including cancer. The immune response is catalysed by TCRs binding to certain peptides presented by the MHC. As such it is critical to better understand the binding processes of TCRs and their selectivity, which is determined by the structural and physicochemical properties of the interaction sites. Improving in-silico modelling approaches has the potential to reduce the costs of synthetic TCR engineering and to accelerate the discovery of new targets and biologic therapies for instance against cancer. While in-silico and particularly deep learning methods for structure and binding predictions of protein interactions have shown promise, they are not yet robust or accurate enough to provide useful information about TCR targets and binding. This project proposes to develop and train novel deep learning architectures to improve the in-silico predictions of TCR to peptide MHC complexes. The project will initially benchmark existing in-silico modelling approaches, before identifying and experimenting in key areas in which deep learning methods are likely to yield substantial improvements. This will include analysis of TCR structure predictions, peptide MHC structure predictions and docking predictions. The project will include a review of existing protein docking methods and will implement the latest deep learning methods, for example equivariant graph networks, in TCR immunology research. Given the demonstrated success of deep learning methods in immunology for antibody-antigen complex predictions, and the parallels thereof to TCR-peptide MHC complexes, we expect the transfer of methods to translate to experimental success. The application of deep learning methods to TCR complex predictions has become of greater interest since the release of the Alphafold protein structure prediction network, and initial publications exploring this research space have been published in the last 18 months. The goal of this project is to improve the state-of-the art for in-silico TCR-peptide MHC target and complex prediction. The in-silico models will be integrated into and developed alongside open-source software packages, enabling other researchers to use and analyse the developed methods. The project falls within the EPSRC research areas 'biological informatics', 'computational and theoretical chemistry', and 'mathematical biology'.

The main impact of the SABS CDT will be the difference made by the scientists trained within it, both during their DPhils and throughout their future careers.

The impact of the students during their DPhil should be measured by the culture change that the centre engenders in graduate training, in working at the interface between mathematical/physical sciences and the biomedical sciences, and in cross sector industry/academia working practices.

Current SABS projects are already changing the mechanisms of industry academic collaboration, for example as described by one of our Industrial Partners

"UCB and Roche are currently supervising a joint DPhil project and have put in two more joint proposals, which would have not been possible without the connections and the operational freedom offered by SABS-IDC and its open innovation culture, a one-of-the-kind in UK's CDTs."

New collaborations are also being generated: over 25% of current research projects are entirely new partnerships brokered by the Centre. The renewal of SABS will allow it to continue to strengthen and broaden this effect, building new bridges and starting new collaborations, and changing the culture of academic industrial partnerships. It will also continue to ensure that all of its research is made publically available through its Open Innovation structure, and help to create other centres with similar aims.

For all of our partners however, the students themselves are considered to be the ultimate output: as one our partners describes it,

"I believe the current SABS-IDC has met our original goals of developing young research scientists in a multidisciplinary environment with direct industrial experience and application. As a result, the graduating students have training and research experience that is directly applicable to the needs of modern lifescience R&D, in areas such as pharmaceuticals and biotechnology."

However, it is not only within the industrial realm that students have impact; in the later years of their DPhils, over 40% of SABS students, facilitated by the Centre, have undertaken various forms of public engagement. This includes visiting schools, working alongside Zooniverse to develop citizen science projects, and to produce educational resources in the area of crystal images. In the new Centre all students will be required to undertake outreach activities in order to increase engagement with the public.

The impact of the students after they have finished should be measured by how they carry on this novel approach to research, be it in the sector or outside it. As our industrial letters of support make clear, though no SABS students have yet completed their DPhils, there is a clear expectation that they will play a significant role in shaping the UK economy in the future. For example, as one of our partners comments about our students

"UCB has been in constant search for such talents, who would thrive in pharmaceutical research, but they are rare to find in conventional postgraduate programmes. Personally I am interested in recruiting SABS-IDC students to my group once they are ready for the job market."

To demonstrate the type of impact that SABS alumni will have, we consider the impact being made by the alumni of the i-DTC programmes from which this proposal has grown. Examples include two start-up companies, both of which already have investment in the millions. Several students also now hold senior positions in industry and in research facilities and institutes. They have also been named on 30 granted or pending patents, 15 of these arising directly from their DPhil work.

The examples of past success given above indicate the types of impact we expect the graduates from SABS to achieve, and offer clear evidence that SABS students will become future research leaders, driving innovation and changing research culture.