Using Chemical Structural Indicators for Periodic Classification of Local Anaesthetics

Abstract

Algorithms for classification and taxonomy based on criteria as information entropy and its production are proposed. Some local anaesthetics, currently in use, are classified using five characteristic chemical properties of different portions of their molecules. Many classification algorithms are based on information entropy. When applying the procedures to sets of moderate size, an excessive number of results appear compatible with data and the number suffers a combinatorial explosion. However, after the equipartition conjecture one has a selection criterion between different variants resulting from classification between hierarchical trees. Information entropy and principal component analyses agree. A table of periodic properties of anaesthetics is obtained. The first three features denote the group while the last two indicate the period in the table. The anaesthetics in the same group and period are suggested to present maximum similarity in properties. Furthermore the ones with only the same group will present important resemblance.