A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

被引:675
作者
Grifoni, Alba [1 ]
Sidney, John [1 ]
Zhang, Yun [2 ]
Scheuermann, Richard H. [1 ,2 ,3 ]
Peters, Bjoern [1 ,4 ]
Sette, Alessandro [1 ,4 ]
机构
[1] La Jolla Inst Immunol, Div Vaccine Discovery, La Jolla, CA 92037 USA
[2] J Craig Venter Inst, La Jolla, CA 92037 USA
[3] Univ Calif San Diego, Dept Pathol, San Diego, CA 92093 USA
[4] Univ Calif San Diego, Dept Med, San Diego, CA 92093 USA
关键词
SYNTHETIC PEPTIDES; CELL EPITOPES; SARS; SPIKE; PROTEINS; DATABASE;
D O I
10.1016/j.chom.2020.03.002
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
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.
引用
收藏
页码:671 / +
页数:12
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