Background: Alterations in GABAnergic system are implicated in the pathophysiology of
schizophrenia. Available antipsychotics that target GABA receptor form a desirable therapeutic
strategy in the treatment regimen of schizophrenia, unfortunately, suffer serious setback due to their
prolonged side effects. The present investigation focuses on developing QSAR models from the
biological activity of herbal compounds and their derivatives that promise to be alternative candidates
to GABA uptake inhibitors.
Methods: Three sets of compounds were undertaken in the study to develop QSAR models. The first
set consisted of nine compounds which included Magnolol, Honokiol and other GABA acting
established compounds. The second set consisted of 16 derivatives of N-diarylalkenylpiperidinecarboxylic
acid. The third QSAR dataset was made up of thirty two compounds which were
Magnolol and Honokiol derivatives. Multiple linear regressions (MLR) and support vector machine
(SVM) supervised quantitative structure-activity relationship (QSAR) models were developed to
predict the biological activity of these three sets. The purpose of taking three QSAR sets of diverse
chemical structures but identical in their GABA targeting and pharmacological action was to identify
common chemical structure features responsible for structure-activity relationship (SAR).
Results: Linear and non-linear QSAR models confirmed that the three sets shared common structural
descriptors derived from WHIM (Weighted Holistic Invariant Molecular descriptors), 3D-MoRSE
and Eigenvalue classes.
Conclusion: It was concluded that properties like electro negativity and polarizability play a crucial
role in controlling the activity of herbal compounds against GABA receptor.