A computationally based identification algorithm for estrogen receptor ligands: Part 1. Predicting hER alpha binding affinity

The common reactivity pattern (COREPA) approach is a 3-dimensional, quantit ative structure activity relationship (3-D QSAR) technique that permits ide ntification and quantification of specific global and local stereoelectroni c characteristics associated with a chemical's biological activity. It goes beyond conventional 3-D QSAR approaches by incorporating dynamic chemical conformational flexibility in ligand-receptor interactions. The approach pr ovides flexibility in screening chemical data sets in that it helps establi sh criteria for identifying false positives and false negatives, and is not dependent upon a predetermined and specified toxicophore or an alignment o f conformers to a lead compound. The algorithm was recently used to screen chemical data sets for rat androgen receptor binding affinity. To further e xplore the potential application of the algorithm in establishing reactivit y patterns for human estrogen receptor alpha (hER alpha) binding affinity, the stereoelectronic requirements associated with the binding affinity of 4 5 steroidal and nonsteroidal ligands to the receptor were defined. Reactivi ty patterns for relative hER alpha binding affinity (RBA; 17 beta -estradio l = 100%) were established based on global nucleophilicity, interatomic dis tances between electronegative heteroatoms, and electron donor capability o f heteroatoms, These reactivity patterns were used to establish descriptor profiles for identifying and ranking compounds with RBA of > 150%, 100-10%, 10-1%, and 1-0.1%. Increasing specificity of reactivity patterns was detec ted for ligand data sets with RBAs above 10%. Using the results of this ana lysis, an exploratory expert system was developed for use in ranking relati ve ER binding affinity potential for large chemical data sets.