Computational Tools And Resources For Metabolism-Related Property Predictions. 1. Overview Of Publicly Available (Free And Commercial) Databases And Software

Abstract

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

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The content of this article does not necessarily reflect the views or policies of the US Army, the Department of Defense or the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government.

Financial & competing interests disclosure

This work was supported in part by the Intramural Research Program of NIH, Center for Cancer Research, in part with Federal funds from the Frederick National Laboratory for Cancer Research, National Institutes of Health, under contract HHSN261200800001E, and in part by the US Department of Defense Threat Reduction Agency Grant TMTI0004_09_BH_T. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

This work was supported in part by the Intramural Research Program of NIH, Center for Cancer Research, in part with Federal funds from the Frederick National Laboratory for Cancer Research, National Institutes of Health, under contract HHSN261200800001E, and in part by the US Department of Defense Threat Reduction Agency Grant TMTI0004_09_BH_T. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.