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Models for predicting IKKA and IKKB blockade.
Hu, Haipeng; Snyder, James P.
Afiliação
  • Hu H; Department of Chemistry, Emory University, Atlanta, Georgia 30322, USA. hhu2@emory.edu
J Chem Inf Model ; 52(12): 3190-9, 2012 Dec 21.
Article em En | MEDLINE | ID: mdl-23157456
We describe the application of different methods in the development of QSAR models for IKKA and IKKB inhibition. The results show that the best QSAR models provide highly accurate predictions for existing IkB-kinase (IKK) inhibitors. The exceptions, corresponding to 5% of the known collection of inhibitors, are five classes of compounds incorporating the nitrile or sulfonamide moieties, small compounds with molecular weights of less than 300, and two classes of blockers considered to be type II kinase inhibitors. Comparison of our novel IKKB homology model and the recently reported IKKB crystal structure implies that a predictive protein-antagonist complex structure is more likely to exist as an inactive form in the crystalline state as observed in the recent protein X-ray structure.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Relação Quantitativa Estrutura-Atividade / Inibidores de Proteínas Quinases / Quinase I-kappa B / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2012 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Relação Quantitativa Estrutura-Atividade / Inibidores de Proteínas Quinases / Quinase I-kappa B / Descoberta de Drogas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2012 Tipo de documento: Article