The challenge
Understanding and possibly controlling antigen recognition by the T cell may benefit autoimmunity, rejection of transplanted organs (allorecognition), may facilitate breakthroughs in antibody-ligand and neuroreceptor/transmitter interactions and could even assist personalized cancer immunotherapy. However, although recognition of a peptide (p)-Major Histocompatibility Complex (MHC) by a T Cell receptor (TCR) – a prerequisite for the initiation of the adaptive immune response (IR) – is well understood, the mechanism by which pMHC-TCR primary atomic structure translates to IR triggering remains unknown, hindering systematic control of the IR functional outcome and of its therapeutic potential.
Our research
Aiming to address T cell receptor-ligand triggering at its most fundamental level (i.e. atomic or sub-atomic/quantum), we developed BioRank, a hybrid framework combining large-scale, high-throughput molecular dynamics, first principles’ (atomistic) computational analysis and machine learning which we tested across the entire range of Class I pMHC-TCR complexes and determined high out-of-sample prediction accuracy. This R&D is based on our prior work, highlighting that atomic coordination (i.e. a set of statistics emanating from protein atomic structure) is correlated to the functional outcome of the IR. At the same time, our study elucidated at least one quantum motif differentiated agonist from antagonist peptide variants.
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BioRank presentation