Literature DB >> 16250655

MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist.

Gabriele Cruciani1, Emanuele Carosati, Benoit De Boeck, Kantharaj Ethirajulu, Claire Mackie, Trevor Howe, Riccardo Vianello.   

Abstract

Identification of metabolic biotransformations can significantly affect the drug discovery process. Since bioavailability, activity, toxicity, distribution, and final elimination all depend on metabolic biotransformations, it would be extremely advantageous if this information could be produced early in the discovery phase. Once obtained, this information can help chemists to judge whether a potential candidate should be eliminated from the pipeline or modified to improve chemical stability or safety of new compounds. The use of in silico methods to predict the site of metabolism in phase I cytochrome-mediated reactions is a starting point in any metabolic pathway prediction. This paper presents a new method, specifically designed for chemists, that provides the cytochrome involved and the site of metabolism for any human cytochrome P450 (CYP) mediated reaction acting on new substrates. The methodology can be applied automatically to all the cytochromes for which 3D structure is known and can be used by chemists to detect positions that should be protected in order to avoid metabolic degradation or to check the suitability of a new scaffold or prodrug. The fully automated procedure is also a valuable new tool in early ADME-Tox assays (absorption, distribution, metabolism, and excretion toxicity assays), where drug safety and metabolic profile patterns must be evaluated as soon, and as early, as possible.

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Year:  2005        PMID: 16250655     DOI: 10.1021/jm050529c

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  90 in total

1.  Accurate prediction of glucuronidation of structurally diverse phenolics by human UGT1A9 using combined experimental and in silico approaches.

Authors:  Baojian Wu; Xiaoqiang Wang; Shuxing Zhang; Ming Hu
Journal:  Pharm Res       Date:  2012-06       Impact factor: 4.200

Review 2.  Predicting the oxidative metabolism of statins: an application of the MetaSite algorithm.

Authors:  Giulia Caron; Giuseppe Ermondi; Bernard Testa
Journal:  Pharm Res       Date:  2007-03       Impact factor: 4.200

Review 3.  From laptop to benchtop to bedside: structure-based drug design on protein targets.

Authors:  Lu Chen; John K Morrow; Hoang T Tran; Sharangdhar S Phatak; Lei Du-Cuny; Shuxing Zhang
Journal:  Curr Pharm Des       Date:  2012       Impact factor: 3.116

4.  Empirical regioselectivity models for human cytochromes P450 3A4, 2D6, and 2C9.

Authors:  Robert P Sheridan; Kenneth R Korzekwa; Rhonda A Torres; Matthew J Walker
Journal:  J Med Chem       Date:  2007-06-19       Impact factor: 7.446

Review 5.  Modeling kinetics of subcellular disposition of chemicals.

Authors:  Stefan Balaz
Journal:  Chem Rev       Date:  2009-05       Impact factor: 60.622

Review 6.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

7.  QSAR modeling: where have you been? Where are you going to?

Authors:  Artem Cherkasov; Eugene N Muratov; Denis Fourches; Alexandre Varnek; Igor I Baskin; Mark Cronin; John Dearden; Paola Gramatica; Yvonne C Martin; Roberto Todeschini; Viviana Consonni; Victor E Kuz'min; Richard Cramer; Romualdo Benigni; Chihae Yang; James Rathman; Lothar Terfloth; Johann Gasteiger; Ann Richard; Alexander Tropsha
Journal:  J Med Chem       Date:  2014-01-06       Impact factor: 7.446

Review 8.  Correlating structure and function of drug-metabolizing enzymes: progress and ongoing challenges.

Authors:  Eric F Johnson; J Patrick Connick; James R Reed; Wayne L Backes; Manoj C Desai; Lianhong Xu; D Fernando Estrada; Jennifer S Laurence; Emily E Scott
Journal:  Drug Metab Dispos       Date:  2013-10-15       Impact factor: 3.922

9.  Dehydrogenation of the indoline-containing drug 4-chloro-N-(2-methyl-1-indolinyl)-3-sulfamoylbenzamide (indapamide) by CYP3A4: correlation with in silico predictions.

Authors:  Hao Sun; Chad Moore; Patrick M Dansette; Santosh Kumar; James R Halpert; Garold S Yost
Journal:  Drug Metab Dispos       Date:  2008-12-12       Impact factor: 3.922

10.  Probing Mechanisms of CYP3A Time-Dependent Inhibition Using a Truncated Model System.

Authors:  Xiaojing Wang; Minghua Sun; Connie New; Spencer Nam; Wesley P Blackaby; Alastair J Hodges; David Nash; Mizio Matteucci; Joseph P Lyssikatos; Peter W Fan; Suzanne Tay; Jae H Chang
Journal:  ACS Med Chem Lett       Date:  2015-07-12       Impact factor: 4.345

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