QSAR models for analgesic activity prediction of terpenes and their derivatives

Abstract

In the present study, quantitative structure-activity relationship (QSAR) models were developed to predict analgesic activity of some mono-/bicyclic terpenoids and their esters with neurotransmitter amino acids. All the models were developed using structural descriptors calculated by SiRMS approach based on the simplex representation of the molecular structure. Log P, molecular refraction, electronegativity, and molecular mass were used as integral descriptors additionally to calculated 2D simplex descriptors. Predictive QSAR models were obtained using the partial least squares (PLS) method. The analysis of structural factors influence on the manifestation of analgesic activity for studied compounds was carried out in the following pharmacological tests: capsaicin, formalin, allylisothiocyanate, and “hot plate” tests. We found that the most significant contribution to analgesic action in all pharmacological tests exhibited molecular fragments representing menthol and borneol residues. Also, we may conclude that –OH group substitution in terpenoid molecules for GABA or glycine residues leads to enhancement of analgesic effect due to the presence of additional highly reactive C=O and N–H groups playing the role of H-bond donors/acceptors.