Comparison of estrogen receptor alpha and beta subtypes based on comparative molecular field analysis (CoMFA)

A substantial body of evidence indicates that both humans and wildlife suff er adverse health effects from exposure to environmental chemicals that are capable of interacting with the endocrine system. The recent cloning of th e estrogen receptor beta subtype (ER-beta) suggests that the selective effe cts of estrogenic compounds may arise in part by the control of different s ubsets of estrogen-responsive promoters by the two ER subtypes, ER-alpha an d ER-beta. In order to identify the structural prerequisites for ligand-ER binding and to discriminate ER-alpha and ER-beta in terms of their ligand-b inding specificities, Comparative Molecular Field Analysis (CoMFA) was empl oyed to construct a three-dimensional Quantitative Structure-Activity Relat ionship (3D-QSAR) model on a data set of 31 structurally-diverse compounds for which competitive binding affinities have been measured against both ER -alpha and ER-beta. Structural alignment of the molecules in CoMFA was achi eved by maximizing overlap of their steric and electrostatic fields using t he Steric and Electrostalic ALignment (SEAL) algorithm. The final CoMFA mod els, generated by correlating the calculated 3D steric and electrostatic fi elds with the experimentally observed binding affinities using partial leas t-squares (PLS) regression, exhibited excellent self-consistency (r(2) > 0. 99) as well as high internal predictive ability (q(2) > 0.65) based on cros s validation. CoMFA-predicted values of RBA for a test set of compounds out side of the training set were consistent with experimental observations. Th ese CoMFA models can serve as guides for the rational design of ER ligands that possess preferential binding affinities for either ER-alpha or ER-beta . These models can also prove useful in risk assessment programs to identif y real or suspected EDCs.