Research Article
Models for Antitubercular Activity of 5′-O−[(N−Acyl)sulfamoyl]adenosines

Rakesh K. GOYAL, Harish DUREJA, Gajendra SINGH and Anil Kumar MADAN

Scientia Pharmaceutica, 2010, 78(4), 791-820. DOI: 10.3797/scipharm.1006-03

Abstract

The relationship between topological indices and antitubercular activity of 5’-O- [(N-Acyl)sulfamoyl]adenosines has been investigated. A data set consisting of 31 analogues of 5’-O-[(N-Acyl)sulfamoyl]adenosines was selected for the present study. The values of numerous topostructural and topochemical indices for each of 31 differently substituted analogues of the data set were computed using an in-house computer program. Resulting data was analyzed and suitable models were developed through decision tree, random forest and moving average analysis (MAA). The goodness of the models was assessed by calculating overall accuracy of prediction, sensitivity, specificity and Mathews correlation coefficient. Pendentic eccentricity index - a novel highly discriminating, non-correlating pendenticity based topochemical descriptor - was also conceptualized and successfully utilized for the development of a model for antitubercular activity of 5’-O-[(N-Acyl)sulfamoyl]adenosines. The proposed index exhibited not only high sensitivity towards both the presence as well as relative position(s) of pendent/heteroatom(s) but also led to significant reduction in degeneracy. Random forest correctly classified the analogues into active and inactive with an accuracy of 67.74%. A decision tree was also employed for determining the importance of molecular descriptors. The decision tree learned the information from the input data with an accuracy of 100% and correctly predicted the cross-validated (10 fold) data with accuracy up to 77.4%. Statistical significance of proposed models was also investigated using intercorrelation analysis. Accuracy of prediction of proposed MAA models ranged from 90.4 to 91.6%.

ASCI-ID: 5014-38

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