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Cheminformatics in the Identification of Drug Classes for the Treatment of Type 2 Diabetes.
Finn, Paul W.
Afiliação
  • Finn PW; School of Computing, University of Buckingham, Buckingham, UK. paul.finn@buckingham.ac.uk.
Methods Mol Biol ; 2076: 71-84, 2020.
Article em En | MEDLINE | ID: mdl-31586322
ABSTRACT
Computer-Aided Drug Design has developed into a powerful suite of methods that complement experimental approaches to the identification of new pharmacologically active compounds. In particular, virtual screening has become a standard tool for lead identification. Diverse examples of the application of virtual screening applied to T2DM target proteins have been reported. While several of these indicate successful identification of new lead compounds from synthetic chemical and natural product databases, many of them have been performed on a small scale and with limited validation. Careful study design and collaboration with cheminformaticians and computational chemists will enable these approaches to fulfil their potential for T2DM.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Descoberta de Drogas / Quimioinformática / Hipoglicemiantes Tipo de estudo: Diagnostic_studies / Etiology_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Descoberta de Drogas / Quimioinformática / Hipoglicemiantes Tipo de estudo: Diagnostic_studies / Etiology_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article