2D-QSAR model development and analysis on variant groups of anti -tuberculosis drugs



Neeraja Dwivedi1, 2, 3*, Bhartendu Nath Mishra1, Vishwa Mohan Katoch3



1Department of Biotechnology, Institute of Engineering & Technology, Lucknow-226021, India; 2Department of Biotechnology, College of Engineering & Technology, IFTM, Lodhipur-Rajput, Delhi Road, Moradabad-244001, India; 3Department of Health Research (Govt. of India) & Indian Council of Medical Research, Ansari Nagar, NewDelhi-110029, India


Email; *Corresponding author





Article Type

Prediction Model



Received August 18, 2011; Accepted August 19, 2011; Published September 06, 2011



A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R2 = 0.74) and predictive accuracy was 72% (RCV2 = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.



2D-QSAR, Mycobacterium tuberculosis, MDR, MIC, TPSA



Dwivedi et al. Bioinformation 7(2): 82-90 (2011)

Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.