EBSCO Logo
Connecting you to content on EBSCOhost
Results
Title

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

Authors

Wright, James; Anderson, James; Shadnia, Hooman; Durst, Tony; Katzenellenbogen, John

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.

Subjects

LIGAND binding (Biochemistry); ESTROGEN receptors; MOLECULAR docking; PROTEIN receptors; REGRESSION analysis; ITERATIVE methods (Mathematics)

Publication

Journal of Computer-Aided Molecular Design, 2013, Vol 27, Issue 8, p707

ISSN

0920-654X

Publication type

Academic Journal

DOI

10.1007/s10822-013-9670-6

EBSCO Connect | Privacy policy | Terms of use | Copyright | Manage my cookies
Journals | Subjects | Sitemap
© 2025 EBSCO Industries, Inc. All rights reserved