Correlation weighting of valence shells in QSAR analysis of toxicity

Abstract

In the rainbow trout ( Oncorhynchus mykiss), we studied the acute toxicity LC 50-96h of 274 organic pesticides with a wide variety of molecular structures. Optimization of correlation weights of local and global graph invariants (OCWLGI) gave quantitative structure–activity relationships (QSARs) for predicting toxicity. We used a labeled hydrogen-filled graph (LHFG) to elucidate the molecular structure. We also used the extended connectivity of zero ( 0EC k ), first ( 1EC k ), and second ( 2EC k ) order, numbers of path lengths 2 (P2 k ) and 3 (P3 k ) starting from a given vertex in the LHFG, and valence shells of second order (S2 k ). S2 k is the sum of the degree of vertices at distance 2 from a given vertex k. The presence of three-, five-, and six-member cycles and hydrogen bond indices suggested they might be used as global LHFG invariants. We applied this method to a broad set of pesticides, to predict toxicity for the trout. The best model used weighted S2 k and global LHFG invariants. Statistical characteristics of this model are as follows: n = 233, r 2 = 0.7689, r 2(pred) = 0.7688, s = 0.75, F = 769 (training set); n = 41, r 2 = 0.6421, r 2(pred) = 0.4241, s = 1.14, F = 70 (test set).