Current and prospective computational approaches and challenges for developing COVID-19 vaccines

Area of Science:

• Virology
• Immunology
• Computational Biology

Background:

• Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, is a zoonotic coronavirus first identified in late 2019.
• The global spread of SARS-CoV-2 has driven an unprecedented global effort to develop effective vaccines.

Purpose of the Study:

• To review existing computational methods used in SARS-CoV-2 vaccine development.
• To identify and propose novel in silico approaches, including bioinformatics and pharmacokinetic (PK) modeling, for future vaccine design.

Main Methods:

• Review of current computational tools applied in reverse vaccinology for SARS-CoV-2.
• Identification of unexplored bioinformatic approaches and PK modeling for vaccine design.

Main Results:

• Computational tools are already utilized for antigen selection, epitope prediction, and toxicity/allergenicity assessment in SARS-CoV-2 vaccine development.
• Bioinformatic approaches and PK modeling represent promising, yet currently unexplored, in silico methods for enhancing vaccine design.

Conclusions:

• Computational methods significantly expedite the vaccine development process for emerging infectious diseases like COVID-19.
• The proposed in silico techniques can be applied not only to SARS-CoV-2 but also to rapidly develop vaccines against future novel viruses with pandemic potential.