De novodesign of anti-variant COVID-19 Vaccine

Abstract

Recent studies have shown the efficacy of hybrid COVID-19 vaccines using wild-type nucleocapsid (N) and Spike (S) protein. We upgrade this strategy by one step further using clinically proven spike protein (but with delta and post-delta omicron mutations) and nucleocapsid peptides conferring T-cell immunity. As per the latest research nucleocapsid peptides are perfect immunological replacement of nucleocapsid protein. Therefore, peptide linking strategy is pursued (economic for cellular biosynthesis than whole protein). One envelope peptide with potent T-cell response is also chosen. This peptide is also functionally indispensable for the virus. All these peptides were clustered in our designed cytoplasmic domain separated by non-immunogenic helical linkers. We also propose the idea of introduction of any T-cell peptide similar to other Human Corona Viruses (HuCoV) in these linker regions whenever required. In addition to COVID, the same approach can be applied for any emergency or even long-term unsolved outbreaks of Influenza, Dengue and West Nile Virus etc. In this era of novelty as presented by subunit and nucleic acid vaccines, multiepitope strategies like this can help to combat multiple diseases successfully in real time to give hope for better future.

Assessing the Generalization Capabilities of TCR Binding Predictors via Peptide Distance Analysis

“…Structural validation in the lab of these models is currently underway, with some researchers reporting partial success, even when solving for previously unknown structures (Van Breugel et al, 2022). Successful applications of sequence-to-shape models in protein research include vaccine design (Goswami et al, 2022), binding affinity ranking (Chang and Perez, 2023), protein sequence design (Castorina et al, 2022; Watson et al, 2022) and benchmarking (Castorina et al, 2023).…”

“…Successful applications of sequence-to-shape models in protein research include vaccine design (Goswami et al, 2022), binding affinity ranking (Chang and Perez, 2023), protein sequence design (Castorina et al, 2022;Watson et al, 2022) and benchmarking (Castorina et al, 2023).…”