Over half of known industrial pollutants have minimal toxic effect, in line with the concept of "baseline toxicity"; such toxicity usually correlates well with lipophilicity. The remainder require additional descriptors in order to model their toxicity by the QSAR approach. Hence, it has not been possible, to date, to develop common stable QSAR models for the toxicity of diverse chemicals with various modes of action on the basis of simple regression relationships. Any new methodology has to take such different modes of action into account. In our work, we used for this purpose an original combination of the similarity concept and physicochemical descriptors calculated by HYBOT, in order to construct stable QSAR models of guppy toxicity. The training set comprised 293 diverse chemicals. Experimental value(s) of one or more nearest related chemicals were used to take structural features and possible modes of toxic action into account. In addition, molecular polarisability and hydrogen bond descriptors for the chemicals of interest and related compounds were used to calculate any additional contribution in toxicity by means of linear regression relationships. Final comparison of calculated and experimental toxicity values gave good results, with standard deviation close to the experimental error.

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