Decision Tree for Mechanism of Antitumor Drugs Action Prediction

Abstract

Classification by the mechanism of action of antitumor drugs using quantitative descriptors has been carried out in this study. The dataset of drugs includes 115 compounds with known activity and mechanism of action. The structures have been taken from the National Cancer Institute database. The dataset includes: 30 structures with the mechanism of alkylation action, 23 compounds are topoisomerase I inhibitors, 16 structures are topoisomerase II inhibitors, 17 compounds are DNA/RNA antimetabolites (dihydrofolate reductase inhibitors), 16 molecules are DNA antimetabolites, and 13 compounds are antimitotic drugs. A decision tree has been constructed for determination of each class of the compounds using 3D descriptors that have been computed by MERA software. Analysis of the results has shown that each mechanism of drug action is characterized by a set of descriptors. Important quantum-chemical descriptors of structures with mechanism for alkylation action, DNA/RNA antimetabolites, and DNA antimetabolites have been determined. Quantum-chemical and geometric descriptors for structures of topoisomerase II inhibitors and geometric descriptors for structures of topoisomerase I inhibitors have been established. An important energy descriptor for antimitotic drugs has been determined. The typical descriptor values for active and inactive structures for each mechanism of action have been determined. The quality recognition of active structures for each mechanism of drugs action has been determined. The highest recognition quality value of active and inactive compounds is observed in the decision tree of topoisomerase II inhibitors. The minimal recognition quality value of active and inactive compounds is observed in the decision tree of DNA/RNA-antimetabolites. The suggested decision trees can be used for determination of the action mechanism of antitumor drugs.