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A QSAR modeling approach for predicting myeloid antimicrobial peptides with high sequence similarity.
Waghu, Faiza Hanif; Gawde, Ulka; Gomatam, Anish; Coutinho, Evans; Idicula-Thomas, Susan.
  • Waghu FH; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India.
  • Gawde U; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India.
  • Gomatam A; Molecular Simulations Group, Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Mumbai, India.
  • Coutinho E; Molecular Simulations Group, Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Mumbai, India.
  • Idicula-Thomas S; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India.
Chem Biol Drug Des ; 96(6): 1408-1417, 2020 12.
Article en En | MEDLINE | ID: mdl-32569448
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Citotóxicas Formadoras de Poros Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article
Texto completo
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Citotóxicas Formadoras de Poros Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article