Literature DB >> 17249383

Methods for predicting human drug metabolism.

Larry J Jolivette1, Sean Ekins.   

Abstract

Drug metabolism information is a necessary component of drug discovery and development. The key issues in drug metabolism include identifying: the enzyme(s) involved, the site(s) of metabolism, the resulting metabolite(s), and the rate of metabolism. Methods for predicting human drug metabolism from in vitro and computational methodologies and determining relationships between the structure and metabolic activity of molecules are also critically important for understanding potential drug interactions and toxicity. There are numerous experimental and computational approaches that have been developed in order to predict human metabolism which have their own limitations. It is apparent that few of the computational tools for metabolism prediction alone provide the major integrated functions needed to assist in drug discovery. Similarly the different in vitro methods for human drug metabolism themselves have implicit limitations. The utilization of these methods for pharmaceutical and other applications as well as their integration is discussed as it is likely that hybrid methods will provide the most success.

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Year:  2007        PMID: 17249383     DOI: 10.1016/s0065-2423(06)43005-5

Source DB:  PubMed          Journal:  Adv Clin Chem        ISSN: 0065-2423            Impact factor:   5.394


  6 in total

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4.  Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

Authors:  Alexander L Perryman; Thomas P Stratton; Sean Ekins; Joel S Freundlich
Journal:  Pharm Res       Date:  2015-09-28       Impact factor: 4.200

5.  DrugBank: a knowledgebase for drugs, drug actions and drug targets.

Authors:  David S Wishart; Craig Knox; An Chi Guo; Dean Cheng; Savita Shrivastava; Dan Tzur; Bijaya Gautam; Murtaza Hassanali
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6.  Computational molecular modeling for evaluating the toxicity of environmental chemicals: prioritizing bioassay requirements.

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  6 in total

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