A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2.
Cell Host Microbe
; 27(4): 671-680.e2, 2020 04 08.
Article
in English
| MEDLINE | ID: covidwho-8785
ABSTRACT
Effective countermeasures against the recent emergence and rapid expansion of the 2019 novel coronavirus (SARS-CoV-2) require the development of data and tools to understand and monitor its spread and immune responses to it. However, little information is available about the targets of immune responses to SARS-CoV-2. We used the Immune Epitope Database and Analysis Resource (IEDB) to catalog available data related to other coronaviruses. This includes SARS-CoV, which has high sequence similarity to SARS-CoV-2 and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in SARS-CoV-2 that have high homology to the SARS-CoV virus. Parallel bioinformatic predictions identified a priori potential B and T cell epitopes for SARS-CoV-2. The independent identification of the same regions using two approaches reflects the high probability that these regions are promising targets for immune recognition of SARS-CoV-2. These predictions can facilitate effective vaccine design against this virus of high priority.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Coronavirus Infections
/
Computational Biology
/
Betacoronavirus
Type of study:
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Cell Host Microbe
Journal subject:
Microbiology
Year:
2020
Document Type:
Article
Affiliation country:
J.chom.2020.03.002
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