IIBR:Informatics:RAPID: Structure-based identification of SARS-derived peptides with potential to induce broad protective immunity

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We are now living through a pandemic age caused by a novel strain of coronavirus (SARS-CoV-2) with a fast-growing number of confirmed cases all over the world. Several efforts are underway to produce new drug inhibitors, repurpose existing drugs and devise combination treatments. At the same time, vaccine development is targeting both neutralizing antibodies against envelope proteins of the virus, and long-term cell-mediated immunity based on T cell lymphocytes. T cell responses are particularly important for fighting viral infections, because they can find and eliminate infected cells. This project will use advanced methods of computational structural analysis to identify conserved small fragments (peptides) of SARS-CoV-2 viral proteins that can be used as targets for a broad-spectrum peptide-based vaccine, which could provide protective immunity against several strains of SARS-CoV-2 and potentially other SARS-like coronaviruses. The workflow will be shared by broad virology research community and any identified peptides will be directly related to SARS-CoV variants and other pathogen study, which will shorten vaccine and drug development cycle for any possible future new coronaviruses. Educating and training future researchers are planned through graduate and post-doc research mentoring, professional development, and career guidance. This project will develop a computational pipeline to enable the identification of peptides that are conserved across different SARS-CoV strains, and that can potentially be used to induce broad protective cellular immunity against these viruses. The approach is based on the combined use of gold-standard sequence-based methods, and new cutting-edge methods for the structural modeling and analysis of peptides bound to different Human Leukocyte Antigen (HLA) receptors. HLAs are responsible for displaying the peptides to T-cell lymphocytes, and the proposed pipeline will enable the identification of conserved hot-spots capable of triggering T-cell responses against multiple SARS-CoV variants. In the context of this project, research will target conserved peptides from the Nucleocapsid (N) protein of SARS-CoV-2. If needed, optimization of predicted peptides will be conducted for different prevalent HLA alleles. The proposed computational pipeline will be built using general software-engineering principles, making it also applicable to study different proteins from SARS-CoV variants, and even other pathogens. The work done on this project can be found in http://www.kavrakilab.org/nsf-rapid-sarscov2.html This RAPID award is made by the Infrastructure Innovation for Biological Research (IIBR Informatics) Program in the Division of Biological Infrastructure, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.