First computational design using lambda-superstrings and in vivo validation of SARS-CoV-2 vaccine

Area of Science:

• Immunology
• Vaccinology
• Computational Biology

Background:

• Coronavirus disease 2019 (COVID-19) remains a global health threat, necessitating continuous vaccine development despite existing advancements.
• Uncertainty regarding the long-term efficacy and duration of immunity from current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines underscores the need for alternative vaccine strategies.
• Peptide-based vaccines offer a promising avenue for developing new vaccines against SARS-CoV-2.

Purpose of the Study:

• To computationally design novel peptide vaccine candidates against SARS-CoV-2 using lambda-superstring optimization.
• To evaluate the immunogenicity, immune response type, and cytokine profile of a dendritic cell (DC) vaccine vector loaded with a SARS-CoV-2 Spike protein peptide (DC-CoVPSA).
• To establish proof of concept for the lambda-superstring optimization technique and the DC-CoVPSA vaccine in human subjects.

Main Methods:

• Computational design of monopeptide and multipeptide vaccine candidates using lambda-superstring optimization.
• Synthesis of a 22-amino acid peptide (CoVPSA) from the SARS-CoV-2 Spike protein NTD domain and its loading onto a DC vaccine vector.
• In vivo immunogenicity testing in animal models and ex vivo analysis of immune responses and cytokine profiles (Th1-Th17).
• Proof of concept human trials involving asymptomatic COVID-19 patients, vaccinated volunteers, and control donors, with current RNA-vaccine epitopes as positive control.

Main Results:

• The CoVPSA peptide demonstrated significant immunogenicity in vivo when delivered via a DC vaccine vector.
• The DC-CoVPSA vaccine elicited robust cellular and humoral immune responses, characterized by a predominant Th1-Th17 cytokine profile indicative of effective antiviral activity.
• The lambda-superstring optimization technique was validated, and proof of concept was successfully established in human subjects.

Conclusions:

• The lambda-superstring optimization technique is a valid and effective method for identifying optimal epitopes from the SARS-CoV-2 Spike protein for peptide-based vaccine development.
• The developed DC vaccine vector (DC-CoVPSA) represents a promising candidate for a peptide-based vaccine against COVID-19.
• This approach is adaptable for various vector platforms, offering flexibility in future vaccine design against SARS-CoV-2.