Prediction of eye irritation from organic chemicals using membrane-interaction QSAR analysis

Eye irritation potency of a compound or mixture has traditionally been evaluated using the Draize rabbit-eye test (Draize et at, 1944), In order to aid predictions of eye irritation and to explore possible corresponding mechanisms of eye irritation, a methodology termed "membrane-interaction QSAR analysis" (MI-QSAR) has been developed (Kulkami and Hopfinger 1999). A set of Draize eye-irritation data established by the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) (Bagley et al., 1992) was used as a structurally diverse training set in an MI-QSAR analysis, Significant QSAR models were constructed based primarily upon aqueous solvation-free energy of the solute and the strength of solute binding to a model phospholipid (DMPC) monolayer, The results demonstrate that inclusion of parameters to model membrane interactions of potentially irritating chemicals provides significantly better predictions of eye irritation for structurally diverse compounds than does modeling based solely on physiochemical properties of chemicals, The specific MI-QSAR models reported here are, in fact, close to the upper limit in both significance and robustness that can be expected for the variability inherent to the eye-irritation scores of the ECETOC training set. The MI-QSAR models can be used with high reliability to classify compounds of low- and high-predicted eye irritation scores, Thus, the models offer the opportunity to reduce animal testing for compounds predicted to fall into these two extreme eye-irritation score sets, The MI-QSAR paradigm may also be applicable to other toxicological endpoints, such as skin irritation, where interactions with cellular membranes are likely.