Coevolution based immunoinformatics approach considering variability of epitopes to combat different strains: A case study using spike protein of SARS-CoV-2.

Mishra, Saurav Kumar; Priya, Prerna; Rai, Gyan Prakash; Haque, Rizwanul; Shanker, Asheesh

Mishra, Saurav Kumar; Priya, Prerna; Rai, Gyan Prakash; Haque, Rizwanul; Shanker, Asheesh.

Afiliación

Mishra SK; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India.
Priya P; Department of Botany, Purnea Mahila College, Purnia, Bihar, India.
Rai GP; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India.
Haque R; Department of Biotechnology, Central University of South Bihar, Gaya, Bihar, India.
Shanker A; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar, India. Electronic address: ashomics@gmail.com.

Comput Biol Med ; 163: 107233, 2023 09.

Article en En | MEDLINE | ID: mdl-37422941

Asunto(s)

COVID-19; Vacunas Virales; Humanos; SARS-CoV-2; COVID-19/prevención & control; Simulación del Acoplamiento Molecular; Vacunas contra la COVID-19; Glicoproteína de la Espiga del Coronavirus/química; Escherichia coli; Vacunas Virales/química; Epítopos de Linfocito T/química; Vacunas de Subunidad/química; Biología Computacional/métodos

Palabras clave

Coevolution; Immunoinformatics; SARS-CoV-2; Spike protein; Vaccine

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Vacunas Virales / COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article País de afiliación: India

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