MOLECULAR FRAGMENTS ASSOCIATED WITH NONGENOTOXIC CARCINOGENS, AS DETECTED USING A SOFTWARE PROGRAM BASED ON GRAPH-THEORY - THEIR USEFULNESSTO PREDICT CARCINOGENICITY

We assembled 390 chemicals with a structure non-alerting to DNA-reacti vity (145 carcinogens and 245 non-carcinogens) for which rodent carcin ogenicity data were available. These non-alerting chemicals were defin ed by the absence in their molecules of DNA-reactive (directly or afte r metabolic activation) alerting structures, as described by Ashby and coworkers (Mutat. Res., 204(1988) 17-115; Mutat. Res., 223(1989) 73-1 03; Mutat. Res., 257 (1991) 209-227; Mutat. Res., 286 (1993) 3-74). Us ing our software program based on graph theory we analyzed the compoun ds in order to estimate the program's ability to predict non-alerting carcinogens. Our software fragmented the structural formula of the che micals into all possible fragments of contiguous atoms with size betwe en 2 and 8 (non-hydrogen) atoms and learned about statistically signif icant fragments from a training set of chemicals. These fragments were used to predict carcinogenicity or lack :hereof in a verification set of compounds. For 390 runs of the software program we used (n - 1) of the chemicals as a training set, to predict the excluded chemical at each run (as a test set). Using two different probability thresholds t o select significant fragments (P=0.05 and P=0.125 1-tailed according to binomial distribution), we performed two analyses: in the better on e (P = 0.05) 19% of the molecules tested lacked significant fragments, for the remaining 81% the observed level of accuracy of the predictio n was 66.0% against an expected level of accuracy of 51.7%. The differ ence was highly significant (P < 0.0001). We also examined the more si gnificant activating fragments (biophores) and discussed at length bot h their biological plausibility and the working hypothesis that additi onal alerting structures for carcinogenicity (not only those related t o genotoxicity) can be detected using this type of SAR approach. This new class of alerting structures could identify subfamilies of congene ric analogs active through mechanisms of receptor mediated carcinogene sis.