EVALUATION OF QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP METHODS FOR LARGE-SCALE PREDICTION OF CHEMICALS BINDING TO THE ESTROGEN-RECEPTOR

Three different QSAR methods, Comparative Molecular Field Analysis (Co MFA), classical QSAR (utilizing the CODESSA program), and Hologram QSA R (HQSAR), are compared in.terms of their potential for screening larg e data sets of chemicals as endocrine disrupting compounds (EDCs). Whi le CoMFA and CODESSA (Comprehensive Descriptors for Structural and Sta tistical Analysis) have been commercially available for some time, HQS AR is a novel QSAR technique. HQSAR attempts to correlate molecular st ructure with biological activity for a series of compounds using molec ular holograms constructed from counts of sub-structural molecular fra gments. In addition to using r(2) and q(2) (cross-validated r(2)) in a ssessing the statistical quality of QSAR models, another statistical p arameter was defined to be the ratio of the standard error to the acti vity range. The statistical quality of the QSAR models constructed usi ng CoMFA and HQSAR techniques were comparable and were generally bette r than those produced with CODESSA. It is notable that only 2D-connect ivity, bond and elemental atom-type information were considered in bui lding HQSAR models. Since HQSAR requires no conformational analysis or structural alignment, it is straightforward to use and lends itself r eadily to the rapid screening of large numbers of compounds. Among the QSAR methods considered, HQSAR appears to offer many attractive featu res, such as speed, reproducibility and ease of use, which portend its utility for prioritizing large numbers of potential EDCs for subseque nt toxicological testing and risk assessment.