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Davide Malacarne,¹ Raffaele Pesenti,² Massimo Paolucci,² and Silvio Parodi³

¹Istituto Nazionale per la Ricerca sul Cancro, Genova, Italy; ²Dipartimento di Informatica Sistemistica e Telematica, Facoltà di Ingegneria, Università di Genova, Genova, Italy; ³Istituto di Oncologia Clinica e Sperimentale, Facoltà di Medicina e Chirurgia, Università di Genova, Genova, Italy

Abstract
For a database of 826 chemicals tested for carcinogenicity, we fragmented the structural formula of the chemicals into all possible contiguous-atom fragments with size between two and eight (nonhydrogen) atoms. The fragmentation was obtained using a new software program based on graph theory. We used 80% of the chemicals as a training set, and 20% as a test set. The two sets were obtained by random sorting. From the training sets, an average (8 computer runs with independently sorted chemicals) of 315 different fragments were significantly (p<0.125) associated with carcinogenicity or lack thereof. Even using this relatively low level of statistical significance, 23% of the molecules of the test sets lacked significant fragments. For 77% of the molecules of the test sets, we used the presence of significant fragments to predict carcinogenicity. The average level of accuracy of the predictions in the test sets was 67.5%. Chemicals containing only positive fragments were predicted with an accuracy of 78.7%. The level of accuracy was around 60% for chemicals characterized by contradictory fragments or only negative fragments. In a parallel manner, we performed eight paired runs in which carcinogenicity was attributed randomly to the molecules of the training sets. The fragments generated by these pseudo-training sets were devoid of any predictivity in the corresponding test sets. Using an independent software program, we confirmed (for the complex biological endpoint of carcinogenicity) the validity of a structure-activity relationship approach of the type proposed by Klopman and Rosenkranz with their CASE program. Key words: carcinogenicity prediction, computer-aided programs, molecular connectivity, molecular fragments, structure-activity relationships. Environ Health Perspect 101:000-000(1993) .

Address correspondence to S. Parodi, Istituto di Oncologia Clinica e Sperimentale, Viale Benedetto XV, 10 16132 Genova Italy.

We are grateful to R. Benigni and A. Mugnoli for their useful suggestions. We thank G. Frigerio and T. Wiley for their careful assistance in preparing the manuscript. This work was supported by grant "Finalizzato CNR/ACRO," no. 92.02343.PF39(*) , grant "STEP" of the European Community, no. Ct.91-0146(DTEE) , and grants MURST 40-60% to S. Parodi.