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Experimental versus predicted affinities for ligand binding to estrogen receptor: iterative selection and rescoring of docked poses systematically improves the correlation

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Abstract

The computational determination of binding modes for a ligand into a protein receptor is much more successful than the prediction of relative binding affinities (RBAs) for a set of ligands. Here we consider the binding of a set of 26 synthetic A-CD ligands into the estrogen receptor ERα. We show that the MOE default scoring function (London dG) used to rank the docked poses leads to a negligible correlation with experimental RBAs. However, switching to an energy-based scoring function, using a multiple linear regression to fit experimental RBAs, selecting top-ranked poses and then iteratively repeating this process leads to exponential convergence in 4–7 iterations and a very strong correlation. The method is robust, as shown by various validation tests. This approach may be of general use in improving the quality of predicted binding affinities.

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Notes

  1. uDock and auxiliary programs are available free of charge from Dr. Hooman Shadnia’s website at www.shadnia.com (2013).

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Acknowledgments

This work was funded by the Canadian Breast Cancer Foundation (Ontario Region) grants to J. S. Wright and T. Durst. We are grateful to the CBCF for support for this work.

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Authors and Affiliations

  1. Department of Chemistry, Carleton University, 1125 Colonel By Dr., Ottawa, K1S 5B6, Canada

    James S. Wright & James M. Anderson

  2. Chemical Computing Group, 1010 Sherbrooke St. W., Montreal, QC, H3A 2R7, Canada

    Hooman Shadnia

  3. Department of Chemistry, University of Ottawa, D’Iorio Hall, 10 Marie Curie St., Ottawa, K1N 6N5, Canada

    Tony Durst

  4. Department of Chemistry, University of Illinois, Urbana, IL, 61801, USA

    John A. Katzenellenbogen

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  1. James S. Wright
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  2. James M. Anderson
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Correspondence to James S. Wright.

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Wright, J.S., Anderson, J.M., Shadnia, H. et al. Experimental versus predicted affinities for ligand binding to estrogen receptor: iterative selection and rescoring of docked poses systematically improves the correlation. J Comput Aided Mol Des 27, 707–721 (2013). https://doi.org/10.1007/s10822-013-9670-6

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  • DOI: https://doi.org/10.1007/s10822-013-9670-6

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