[R21] MimicMaker: an integrated platform for identifying relevant mimics of T cell antigens
Ente: National Center for Advancing Translational Sciences
Scadenza: 2028-04-30
Importo max: 434.500 EUR
Paese: US
Descrizione
SUMMARY
Advances in immunology are revolutionizing medicine. The last 10-20 years have seen the rapid development
of a range of transformative immunotherapies, with numerous others on the horizon, including new precision and
personalized therapies for cancer and infectious disease. Advances in immunology are also powering new ways
to address health conditions that emerge from immune dysfunction or dysregulation. Many immunotherapies
center on the cellular arm of the adaptive immune system. In cellular immunity, T cells use their αβ T cell
receptors (TCRs) to recognize small peptides (or “epitopes”) bound and presented by class I or class II major
histocompatibility complex (MHC) proteins. While specificity is a hallmark of T cell recognition, TCRs are also
broadly cross-reactive. The biological imperative for TCR cross-reactivity results from the limited size of an
individual’s T cell repertoire compared to the vastly larger number of potential epitopes, as well as the need for
T cells to recognize self for positive selection and homeostasis. However, TCR cross-reactivity also poses
substantial risks for new and existing immunotherapies and leads to autoimmunity and cellular rejection of
transplanted organs. TCR cross-reactivity can almost always be ascribed to the concept of molecular mimicry,
where cross-recognized peptides share key structural and physical features. However, mimicry is frequently
obscured behind structural and physicochemical complexities. These complexities have generally prevented the
prospective identification of mimics of T cell epitopes, greatly complicating derisking and pre-clinical testing in
immunotherapy and hindering our ability to address the underlying immunology of T cell driven autoimmunity
and transplant rejection. Indeed, molecular mimics have traditionally only been identified and understood after
cross-recognition – often in the form of a clinical presentation or complication – is observed. To address this
major limitation in translational immunology and advance precision immunotherapy, we have begun developing
a technology platform that, beginning with a known target epitope and its presenting MHC protein, uses data
science, AI-driven 3D structural modeling, and structure-based scoring that incorporates advances in deep
learning and structural analysis to prospectively identify molecular mimics within genetic databases. Our
platform, termed MimicMaker, directly addresses the complexities of cross-reactivity in T cell recognition. It
leverages our decades of experience in structural immunology, protein biophysics, and immunoinformatics. In
two iterative Specific Aims, we will develop and refine MimicMaker, generating and using new data from our
mouse model of virus-accelerated transplant rejection. Collaborations with industry and academia are in place
to help test, optimize, and validate the platform and, with success, facilitate its adoption and eventual
commercialization to improve outcomes in areas such
Istituzione: UNIVERSITY OF NOTRE DAME
PI: Brian M Baker
Progetto: 1R21TR006240-01
Settori: National Center for Advancing Translational Sciences
Vai al bando originale
Registrati gratis su Bandolo per trovare bandi compatibili con la tua azienda.