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A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2.
Cell Host Microbe. 2020 04 08; 27(4):671-680.e2.CH

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.

Authors+Show Affiliations

Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA 92037, USA.Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA 92037, USA.J. Craig Venter Institute, La Jolla, CA 92037, USA.Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA 92037, USA; J. Craig Venter Institute, La Jolla, CA 92037, USA; Department of Pathology, University of California, San Diego, San Diego, CA 92093, USA.Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA 92037, USA; Department of Medicine, University of California, San Diego, San Diego, CA 92093, USA.Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA 92037, USA; Department of Medicine, University of California, San Diego, San Diego, CA 92093, USA. Electronic address: alex@lji.org.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

32183941

Citation

Grifoni, Alba, et al. "A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2." Cell Host & Microbe, vol. 27, no. 4, 2020, pp. 671-680.e2.
Grifoni A, Sidney J, Zhang Y, et al. A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. Cell Host Microbe. 2020;27(4):671-680.e2.
Grifoni, A., Sidney, J., Zhang, Y., Scheuermann, R. H., Peters, B., & Sette, A. (2020). A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. Cell Host & Microbe, 27(4), 671-e2. https://doi.org/10.1016/j.chom.2020.03.002
Grifoni A, et al. A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. Cell Host Microbe. 2020 04 8;27(4):671-680.e2. PubMed PMID: 32183941.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. AU - Grifoni,Alba, AU - Sidney,John, AU - Zhang,Yun, AU - Scheuermann,Richard H, AU - Peters,Bjoern, AU - Sette,Alessandro, Y1 - 2020/03/16/ PY - 2020/02/13/received PY - 2020/02/26/revised PY - 2020/03/05/accepted PY - 2020/3/19/pubmed PY - 2020/4/15/medline PY - 2020/3/19/entrez KW - B cell epitope KW - COVID-19 KW - SARS-CoV KW - SARS-CoV-2 KW - T cell epitope KW - coronavirus KW - infectious disease KW - sequence conservation SP - 671 EP - 680.e2 JF - Cell host & microbe JO - Cell Host Microbe VL - 27 IS - 4 N2 - 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. SN - 1934-6069 UR - https://www.unboundmedicine.com/medline/citation/32183941/A_Sequence_Homology_and_Bioinformatic_Approach_Can_Predict_Candidate_Targets_for_Immune_Responses_to_SARS_CoV_2_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1931-3128(20)30166-9 DB - PRIME DP - Unbound Medicine ER -