Multi‐class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods

Abstract

Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi-class models by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi-class scheme with the standard multi-class Inductive Logic Programming algorithm and multi-class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms.

Determination of Toxicant Mode of Action by Augmented Top Priority Fragment Class

“…Most of the studies are still using as reference the EPAFHAM data set that lists an experimental MOA for many compounds. Two recent examples , implement a similar approach: a set of molecular descriptors is selected; a training set of compounds is classified using the descriptor set as input variables and the MOA as output variable; the result is checked against the EPAFHAM data set. All steps are repeated until a good agreement between the calculated classes and the experimental MOAs is reached.…”