Automated docking of estrogens and SERMs into an estrogen receptor alpha and beta isoform using the PMF forcefield and the Lamarckian genetic algorithm.

Kiss, G.; Allen, N.W.

A diverse set of estrogens and selective estrogen receptor modulators (SERMs) whose relative binding affinities (RBAs), with respect to 17 β-estradiol are known, are automatically docked into a particular estrogen receptor alpha and beta (ER α and ER β) in silico, utilizing the Lamarckian genetic docking algorithm and the potentials of mean force (PMF) function. After division into distinct classes (estrogens, SERMs), the ligands are ranked based upon the calculated ligand:receptor interaction energies, as well as experimental RBAs. Comparison of both rankings shows good agreement within the distinct ligand classes. The presented results indicate that the PMF may be applied to the estrogen receptor:ligand complexes, and the ranking of ligands within distinct classes is a very useful pre-screening tool for development of novel estrogen receptor ligands.

ESTROGEN receptors; SELECTIVE estrogen receptor modulators; GENETIC algorithms; LIGANDS (Chemistry); PHYSICAL & theoretical chemistry

Theoretical Chemistry Accounts: Theory, Computation, & Modeling, 2007, Vol 117, Issue 2, p305

1432-881X

Academic Journal

10.1007/s00214-006-0138-9