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Development of MLR and SVM Aided QSAR Models to Identify Common SAR of GABA Uptake Herbal Inhibitors used in the Treatment of Schizophrenia

[ Vol. 15 , Issue. 8 ]

Author(s):

Sahila Mohammed Marunnan, Babitha Pallikkara Pulikkal, Anitha Jabamalairaj, Srinivas Bandaru, Mukesh Yadav, Anuraj Nayarisseri and Victor Arokia Doss*   Pages 1085 - 1092 ( 8 )

Abstract:


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.

Keywords:

Schizophrenia, Linear and non-linear QSAR models, MLR and SVM.

Affiliation:

Department of Biochemistry and Bioinformatics, Karpagam University, Coimbatore- 641 021, Tamil Nadu, Research and Development Centre, Bharathiyar University, Coimbatore-641046, Tamil Nadu, Department of Bioinformatics, SIAS-Centre for Scientific Research, Safi Institute of Advanced Study (SIAS), Rasiya Nagar, Vazhayoor East, Malappuram-673633, Kerala, Bioinformatics Research Laboratory, Eminent Biosciences, Vijaynagar, Indore-452010, Bioinformatics Research Laboratory, Eminent Biosciences, Vijaynagar, Indore-452010, Bioinformatics Research Laboratory, Eminent Biosciences, Vijaynagar, Indore-452010, Department of Biochemistry, PSG College of Arts and Science, Coimbatore-641 014

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