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A Web-Based Method for the Identification of IL6-Based Immunotoxicity in Vaccine Candidates.
Dhall, Anjali; Patiyal, Sumeet; Sharma, Neelam; Usmani, Salman Sadullah; Raghava, Gajendra P S.
  • Dhall A; Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
  • Patiyal S; Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
  • Sharma N; Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
  • Usmani SS; Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
  • Raghava GPS; Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India. raghava@iiitd.ac.in.
Methods Mol Biol ; 2673: 317-327, 2023.
Artículo en Inglés | MEDLINE | ID: covidwho-20234868
ABSTRACT
Interleukin 6 (IL6) is a major pro-inflammatory cytokine that plays a pivotal role in both innate and adaptive immune responses. In the past, a number of studies reported that high level of IL6 promotes the proliferation of cancer, autoimmune disorders, and cytokine storm in COVID-19 patients. Thus, it is extremely important to identify and remove the antigenic regions from a therapeutic protein or vaccine candidate that may induce IL6-associated immunotoxicity. In order to overcome this challenge, our group has developed a computational tool, IL6pred, for discovering IL6-inducing peptides in a vaccine candidate. The aim of this chapter is to describe the potential applications and methodology of IL6pred. It sheds light on the prediction, designing, and scanning modules of IL6pred webserver and standalone package ( https//webs.iiitd.edu.in/raghava/il6pred/ ).
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Vacunas / COVID-19 Tipo de estudio: Estudio pronóstico Tópicos: Vacunas Límite: Humanos Idioma: Inglés Revista: Methods Mol Biol Asunto de la revista: Biologia Molecular Año: 2023 Tipo del documento: Artículo País de afiliación: 978-1-0716-3239-0_22

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Vacunas / COVID-19 Tipo de estudio: Estudio pronóstico Tópicos: Vacunas Límite: Humanos Idioma: Inglés Revista: Methods Mol Biol Asunto de la revista: Biologia Molecular Año: 2023 Tipo del documento: Artículo País de afiliación: 978-1-0716-3239-0_22