Prediction of Eye Irritation from Organic Chemicals Using Membrane-Interaction QSAR Analysis

Amit Kulkarni 2 A. J. Hopfinger 2 Rosemarie Osborne 0 Leon H. Bruner 1 Edward D. Thompson 0 0 The Procter & Gamble Company , Miami Valley Laboratories, P.O. Box 538707, Cincinnati, Ohio 45253- 8707 1 Procter & Gamble Technical Centre, Ltd. , Lovett House, Lovett Road, Stains, Middlesex TW18 3AZ, England 2 Laboratory of Molecular Modeling and Design (M/C 781), College of Pharmacy, The University of Illinois at Chicago , 833 South Wood Street, Chicago, Illinois 60612-7231 Eye irritation potency of a compound or mixture has traditionally been evaluated using the Draize rabbit-eye test (Draize et al., 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 (Kulkarni 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. - weighted score; the highest average score across test animals on the various grading days is termed the maximum average score (MAS). Recent work indicates that the extent (area and depth) of injury produced in the cornea is the principle factor determining acute responses and their eventual repair in that tissue (Jester et al., 1998). However, mechanisms of eye irritation are not yet understood on a biochemical level (Bruner et al., 1998). The in vivo rabbit eye-irritation test has frequently been criticized on animal welfare grounds (Rowan, 1984). Many laboratories have been working to develop in vitro alternatives to this test (Balls et al., 1999; Brantom et al., 1997). At the present time, the in vitro alternatives may have a role as screens or adjuncts to the Draize rabbit-eye test, but none are sufficiently well validated to replace the test completely (Balls et al., 1999). International agencies have proposed and adopted step-wise approaches for eye-irritation assessments with the goal of reducing the need for animal eye-irritation tests (OECD 1996). Although structure-activity and structure-property analyses are recommended as early steps in the assessment process, a systematic approach for these analyses has not yet been widely accepted. The current work is directed toward this need. Quantitative structure-activity relationship (QSAR) analysis provides a tool to relate the magnitude of a particular property, such as an eye-irritation score, to one or more physicochemical and/or structural parameters of a molecule. Hence, QSAR analysis can be used to estimate eye irritation. Traditional QSAR methods are normally limited in application to series of chemical analogs for which the dependent property (eye irritation) is derived from a set of intramolecular descriptors based upon an assumed common mechanism of action. However, eye-irritation assessments are normally sought for structurally diverse compounds. Thus, QSAR analysis is relatively limited in utility in applications that estimate eye irritation for diverse classes of chemicals. The European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) established a standard data set for chemicals whose Draize rabbit eye-irritation scores have been measured according to OECD Guideline 405 (1987). The ECETOC data set has come to be used as a standard in the evaluation of in vitro and QSAR methods to estimate eye irritation. A history of the applications of QSAR and molecular modeling to eye irritation in general, and the ECETOC data set in particular, has been given (Kulkarni and Hopfinger, 1999). Several QSAR, data clustering, and molecular modeling studies have been performed using the ECETOC data set. However, all of these studies only employed intramolecular physicochemical properties of the compounds of the training set as correlation descriptors (Barratt, 1995). These previous studies were based on the then prevalent views on the application of QSAR and modeling methods to preclinical drug discovery. It has been generally assumed that predicting eye irritation is methodology-equivalent to designing an active pharmaceutical agent. None of the previous studies were successful in developing a significant statistical QSAR model spanning all the compounds of the ECETOC data set, because this data set is composed of structurally diverse chemicals. In principle, progress might be made in the QSAR analysis of any chemically diverse data set, including the ECETOC eye-irritation data set, if the receptor linked to the eyeirritation response is known and included in constructing QSAR models. This receptor-based approach to molecular design has been successfully used in building high-affinity ligands and is generally called structure-based design (Kubinyi, 1993). In the case of eye irritation, uptake and diffusion of an irritant into the keratocytes of the corneal epithelium may be a significant event. That is, each test molecule placed in the eye must diffuse through the cell membrane of the keratocytes comprising the outer 7 or so layers of the corneal epithelium of the eye. We have thus hypothesized that interactions of test molecules with cell membranes are at least partly, responsible for eye irritation. Moreover, the phospholipid-rich regions of a membrane bilayer of the cell might comprise the general receptor for eye irritation. In order to test this hypothesis, we simulated the uptake and interaction of each of the ECETOC (solute) molecules with a model phospholipid membrane, as a part of our QSAR analysis of the ECETOC eye-irritation data set. In these simulations, the estimated membrane-solute interaction properties from the molecular simulations are added to the intramolecular physicochemical property descriptors to provide an extended set of tri (...truncated)