Title: Fourth generation detour matrix-based topological descriptors for QSAR/QSPR - Part-2: application in development of models for prediction of biological activity

Authors: Rakesh Kumar Marwaha; A.K. Madan

Addresses: Faculty of Pharmaceutical Sciences, M.D. University, Rohtak 124-001, India ' Faculty of Pharmaceutical Sciences, Pt. B.D. Sharma University of Health Sciences, Rohtak 124-001, India

Abstract: Augmented path eccentric connectivity topochemical indices (reported in part-1 of the manuscript) along with 42 diverse non-correlating molecular descriptors (shortlisted from a large pool of 2D and 3D MDs) were successfully utilised for the development of models through decision tree, random forest and moving average analysis for the prediction of antitubercular activity of aza and diazabiphenyl analogues of active compound (6S)-2-Nitro-{[4-(trifluoromethoxy)benzyl]oxy}-6,7-dihydro-5H-imidazo[2,1-b][1,3] oxazine (PA-824). The statistical significance of the proposed models was assessed through overall accuracy of prediction, intercorrelation analysis, sensitivity, specificity and Matthew's correlation coefficient (MCC). The accuracy of prediction of the proposed models varied from a minimum of 81% to a maximum of ∼99%. High accuracy of prediction amalgamated with high MCC values clearly indicates robustness of the proposed models. The said models offer a vast potential for providing lead structures for the development of potent antitubercular drugs.

Keywords: tuberculosis; TB drugs; antitubercular activity; PA-824 analogues; path eccentricity; chemical detour matrix; chemical path; Wiener index; Balaban index; Randic molecular connectivity index; antitubercular drugs; drug design; eccentric connectivity index; computational chemistry; topological indices; structure activity-property relationship; toxicity; pharmacokinetics; similarity-dissimilarity; lead identification; optimisation; chemical structures; Matthew's correlation coefficient; total size index; atomic mass; Gutman MTI; valence vertex degrees; WHIM index; atomic van der Waals volume; modelling.

DOI: 10.1504/IJCBDD.2014.058583

International Journal of Computational Biology and Drug Design, 2014 Vol.7 No.1, pp.1 - 30

Received: 22 May 2012
Accepted: 18 Dec 2012

Published online: 08 Jan 2014 *

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