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Martínez, Y.A.* ; Guo, X.* ; Portales-Pérez, D.P.* ; Rivera, G.* ; Castañeda-Delgado, J.E.* ; Garcia Perez, C. ; Enciso-Moreno, J.A.* ; Lara-Ramírez, E.E.*

The analysis on the human protein domain targets and host-like interacting motifs for the MERS-CoV and SARS-CoV/CoV-2 infers the molecular mimicry of coronavirus.

PLoS ONE 16:e0246901 (2021)
Verlagsversion Forschungsdaten DOI
Open Access Gold
Creative Commons Lizenzvertrag
The MERS-CoV, SARS-CoV, and SARS-CoV-2 are highly pathogenic viruses that can cause severe pneumonic diseases in humans. Unfortunately, there is a non-available effective treatment to combat these viruses. Domain-motif interactions (DMIs) are an essential means by which viruses mimic and hijack the biological processes of host cells. To disentangle how viruses achieve this process can help to develop new rational therapies. Data mining was performed to obtain DMIs stored as regular expressions (regexp) in 3DID and ELM databases. The mined regexp information was mapped on the coronaviruses’ proteomes. Most motifs on viral protein that could interact with human proteins are shared across the coronavirus species, indicating that molecular mimicry is a common strategy for coronavirus infection. Enrichment ontology analysis for protein domains showed a shared biological process and molecular function terms related to carbon source utilization and potassium channel regulation. Some of the mapped motifs were nested on B, and T cell epitopes, suggesting that it could be as an alternative way for reverse vaccinology. The information obtained in this study could be used for further theoretic and experimental explorations on coronavirus infection mechanism and development of medicines for treatment.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 16, Heft: 2, Seiten: , Artikelnummer: e0246901 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort Lawrence, Kan.
Begutachtungsstatus Peer reviewed
Förderungen CONACYT