Potential T-cell and B-cell Epitopes of 2019-nCoV
Vaccines work by creating immune responses against the virus directly as well as against human cells that are infected by the virus—so that they can be destroyed before the virus reproduces.
The Helix group, led by Russ Altman, is using AI algorithms to analyze the Covid-19 genome to find parts of the virus that may be best for developing vaccines. The Altman group algorithms have found some regions of the virus that might be the best to target. They have also used the algorithms to try to understand if some patients are more susceptible to getting severe disease based on their genetics.
They are interested in working with collaborators to test if injecting small parts of the virus, predicted through these algorithms, into animals can be used as a vaccine to generate an immune response that stops COVID-19.
The team is collaborating with the Qi Lab to experimentally verify predicted presented viral antigens using mass-spectrometry, and working with collaborators to create neutralizing antibodies based on immunogenic peptides from the nCOV2019 spike protein.
Neutralizing antibodies verified in animal models can be scaled up by industry partners. Patients with acute respiratory failures can potentially benefit from antibody therapeutics, however, it is likely to take many months to develop these treatments. As an example, Regeneron, with a similar idea in mind, is unlike to start Phase I trials until early summer. As an alternative, other groups are developing antibodies isolated from nCOV2019 patients who have recovered from infection as therapeutic treatments.
The Helix group is also working to gather clinical information and samples of patients with the goal of comparing the genetics of those who got very sick and those who did not, so they can try to understand and predict who will become the most ill. For this work, they are aiming to identify and understand vulnerable patient populations based on patient major histocompatibility complex (MHC) typing.
Previous studies show SARS patients with certain MHC types (e.g. HLA-Cw*0801) are likely to do worse. They are working to find clinicians with relevant COVID-19 data to test this hypothesis and identify relevant antigens.
If their analyses can identify patients with aggressive disease via MHC typing alone, it would immediately help clinicians prioritize hospital admission especially when resources become limited.
Relevant Publications or More Information
- Preprint of the work (not yet peer reviewed, has been submitted for publication to the Proceedings of the National Academy of Sciences)