Discovering substructures able to predicting toxicity against fish

What is it about?

In this paper we discuss the problem of predicting the fish toxicity property of chemical compounds, and show how this can be approached using a computational intelligence method. There are two views on assessing toxicities: one says that such properties can be derived from the whole molecular structure, the other that some specific functional substructures, called Structural Alerts (SA), are able to explain the toxicity. In this work, our data mining method, called SARpy, is applied to mine molecular fragments that act like SAs and can predict the lethal toxicity for the fathead minnow fish.

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Why is it important?

The new model shows marked prediction skills and, more interestingly, it is based on mined structural alerts. Discovering new knowledge about substructures statistically strongly connected to toxicity opens to other future in-silico methods.

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