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Computational Prediction and Validation of an Expert’s Evaluation of Chemical Probes
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    Computational Prediction and Validation of an Expert’s Evaluation of Chemical Probes
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    Collaborative Drug Discovery, Inc., 1633 Bayshore Highway, Suite 342, Burlingame, California 94010, United States
    Christopher A. Lipinski, Ph.D., LLC., 10 Connshire Drive, Waterford, Connecticut 06385-4122, United States
    § Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay Varina, North Carolina 27526, United States
    *E-mail: [email protected]. Phone: (215)-687-1320.
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    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2014, 54, 10, 2996–3004
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    https://doi.org/10.1021/ci500445u
    Published September 22, 2014
    Copyright © 2014 American Chemical Society

    Abstract

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    In a decade with over half a billion dollars of investment, more than 300 chemical probes have been identified to have biological activity through NIH funded screening efforts. We have collected the evaluations of an experienced medicinal chemist on the likely chemistry quality of these probes based on a number of criteria including literature related to the probe and potential chemical reactivity. Over 20% of these probes were found to be undesirable. Analysis of the molecular properties of these compounds scored as desirable suggested higher pKa, molecular weight, heavy atom count, and rotatable bond number. We were particularly interested whether the human evaluation aspect of medicinal chemistry due diligence could be computationally predicted. We used a process of sequential Bayesian model building and iterative testing as we included additional probes. Following external validation of these methods and comparing different machine learning methods, we identified Bayesian models with accuracy comparable to other measures of drug-likeness and filtering rules created to date.

    Copyright © 2014 American Chemical Society

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    Supporting Information

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    Additional supplemental data. This material is available free of charge via the Internet at http://pubs.acs.org. All computational models are available from the authors upon request. All molecules are available in CDD Public (https://app.collaborativedrug.com/register) and at http://molsync.com/demo/probes.php.

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    Cited By

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    This article is cited by 21 publications.

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    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2014, 54, 10, 2996–3004
    Click to copy citationCitation copied!
    https://doi.org/10.1021/ci500445u
    Published September 22, 2014
    Copyright © 2014 American Chemical Society

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