Computational design of SARS-CoV-2 spike glycoproteins to increase immunogenicity by T cell epitope engineering.
Comput Struct Biotechnol J
; 19: 518-529, 2021.
Article
in English
| MEDLINE | ID: covidwho-1002467
ABSTRACT
The development of effective and safe vaccines is the ultimate way to efficiently stop the ongoing COVID-19 pandemic, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Built on the fact that SARS-CoV-2 utilizes the association of its Spike (S) protein with the human angiotensin-converting enzyme 2 (ACE2) receptor to invade host cells, we computationally redesigned the S protein sequence to improve its immunogenicity and antigenicity. Toward this purpose, we extended an evolutionary protein design algorithm, EvoDesign, to create thousands of stable S protein variants that perturb the core protein sequence but keep the surface conformation and B cell epitopes. The T cell epitope content and similarity scores of the perturbed sequences were calculated and evaluated. Out of 22,914 designs with favorable stability energy, 301 candidates contained at least two pre-existing immunity-related epitopes and had promising immunogenic potential. The benchmark tests showed that, although the epitope restraints were not included in the scoring function of EvoDesign, the top S protein design successfully recovered 31 out of the 32 major histocompatibility complex (MHC)-II T cell promiscuous epitopes in the native S protein, where two epitopes were present in all seven human coronaviruses. Moreover, the newly designed S protein introduced nine new MHC-II T cell promiscuous epitopes that do not exist in the wildtype SARS-CoV-2. These results demonstrated a new and effective avenue to enhance a target protein's immunogenicity using rational protein design, which could be applied for new vaccine design against COVID-19 and other pathogens.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Experimental Studies
/
Prognostic study
Topics:
Vaccines
/
Variants
Language:
English
Journal:
Comput Struct Biotechnol J
Year:
2021
Document Type:
Article
Affiliation country:
J.csbj.2020.12.039
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