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SMARTCyp 3.0: enhanced cytochrome P450 site-of-metabolism prediction server.
Olsen, Lars; Montefiori, Marco; Tran, Khanhvi Phuc; Jørgensen, Flemming Steen.
Afiliação
  • Olsen L; Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2100, Denmark.
  • Montefiori M; Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2100, Denmark.
  • Tran KP; Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2100, Denmark.
  • Jørgensen FS; Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2100, Denmark.
Bioinformatics ; 35(17): 3174-3175, 2019 09 01.
Article em En | MEDLINE | ID: mdl-30657882
MOTIVATION: Cytochromes P450 are the most important class of drug metabolizing enzymes. Prediction of drug metabolism is important in development of new drugs, to understand and reduce adverse drug reactions and to reduce animal testing. RESULTS: SMARTCyp 3.0 is an updated version of our previous web server for prediction of site-of-metabolism for Cytochrome P450-mediated metabolism, now in Python 3 with increased structural coverage and new features. The SMARTCyp program is a first principle-based method using density functional theory determined activation energies for more than 250 molecules to identify the most likely site-of-metabolism. New features include a similarity measure between the query molecule and the model fragment, a new graphical interface and additional parameters expanding the structural coverage of the SMARTCyp program. AVAILABILITY AND IMPLEMENTATION: The SMARTCyp server is freely available for use on the web at smartcyp.sund.ku.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Dinamarca

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Dinamarca