2D-QSAR Study of a Series of Pyrazoline-Based Anti-Tubercular Agents Using Genetic Function Approximation

Hemal M. Soni¹, Popatbhai K. Patel², Mahesh T. Chhabria³, Dharmraj N. Rana⁴, Bhushan M. Mahajan¹, Pathik S. Brahmkshatriya^4*

¹M/S Piramal Enterprises Ltd., Piramal Enterprises Limited-Discovery Solutions, Plot No. 18, Pharmaceutical Special Econonic Zone, Village Matoda, Ta. Sanand, Ahmedabad, India.
²M.G. Science Institute, Dada Saheb Mavlankar Campus, Opp. Gujarat University, Ahmedabad, India.
³Department of Pharmaceutical Chemistry, L. M. College of Pharmacy, Ahmedabad, India.
⁴Oxygen Healthcare Res. Pvt. Ltd., Plot No. 35, Panchratna Industrial Estate, Near IBP Laxminarayan Petrol Pump, Changodar, Sarkhej-Bavla Road, Ahmedabad, India.

DOI: 10.4236/cc.2015.34006                

Abstract

A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to further explore the potency of the compounds, quantitative structure activity relationship study is carried out using genetic function approximation. Statistically significant (r² = 0.85) and predictive (r²_pred=0.89 and r²_m=0.74) QSAR models are developed. It is evident from the QSAR study that majority of the anti-tubercular activity is found to be driven by lipophilicity. Also, molecular solubility, Jurs and shadow descriptors influence the biological activity significantly. Also, positive contribution of molecular shadow descriptors suggests that molecules with bulkier substituents are more likely to enhance anti-tubercular activity. Since the developed QSAR models are found to be statistically significant and predictive, they potentially can be applied for predicting anti-tubercular activity of new molecules for prioritization of molecules for synthesis.

Keywords

QSAR, Genetic Function Approximation, Descriptors, Cross-Validation

Conflicts of Interest

The authors declare no conflicts of interest.

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