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The present antipsychotic drugs have known to show serious concerns like extra pyramidal side effects therefore, pursuit for novel antipsychotic GABAnergic drugs has lately focused on the folkloric medicine from plant derivatives as better treatment option of schizophrenia. The present study centers to identify potential inhibitors of plant origin for GABA receptor through in silico approaches. Three compound datasets were undertaken in the study. The first set consisted of seven compounds which included Magnolol, Honokiol and other plant derivatives. The second set consisted of 16 derivatives of N-diarylalkenyl-piperidinecarboxylic acid synthesized by Zheng et al., 2006. The third dataset had thirty two compounds which were Magnolol and Honokiol analogues synthesized by Fuchs et al., 2014. All the compounds were docked at the allosteric site of the GABA (A) receptor. The compounds were further tested for ADMET and biological activity. We observed Honokiol and its derivatives demonstrated superior druglike properties than any compound undertaken in the study. Further, compound 61 [2-(4-methoxyphenyl)-4-propylphenol] of dataset three - a synthetic derivative of honokiol had better profile than its parent compound. In a possible attempt to identify compound with even better efficacious compound than 61, virtual screening was performed, 135 compounds akin to compound 61 were retrieved. Interestingly none of the 135 compounds showed better druggable properties than compound 61. Our in silico pharmacological profiling of compounds is in coherence and is complemented by the findings of Fuchs et al, which also revealed compound 61 to be the good potentiator of GABA receptor.AbbreviationsGABA (A) R - Gamma Amino Butyric Acid Receptor, subtype A, GPCR - G Protein Coupled Receptor, OPLS - Optimized Potentials for Liquid Simulations, PDB - Protein Data Bank, PLP - Piece wise Linear Potential, T.E.S.T - Toxicity Estimation Software Tool, TCM - Traditional Chinese Medicine.

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-diarylalkenyl-piperidinecarboxylic 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.

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