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%.
Highlights
In the pharmaceutical industry, much effort is being devoted to develop new drugs [1]
The main hypothesis in the quantitative structure-activity relationship (QSAR)/QSPR approach is that all properties of a chemical substance are statistically related to its molecular structure [5]
The basic structures of 5'-O-[(N-Acyl)sulfamoyl]adenosines are shown in Fig. 1 and the various substituents have been enlisted in Tab. 1
Summary
Much effort is being devoted to develop new drugs [1]. The seven steps involved in the drug discovery process are: disease selection, target hypothesis, lead identification, lead optimization, pre-clinical trial, clinical trial and pharmacogenomic optimization. These steps are carried out sequentially, and if one of these steps is slow, it naturally slows down the entire process [2]. Mathematical descriptors of molecular structure, such as various topological indices (TIs), have been widely used in structureproperty-activity relationship studies [7]. Topological descriptors are mathematical entities encoding molecular graphs composed of vertices (corresponding to the atoms) and edges (representing the bonds among atoms). Some of the topostructural and topochemical indices, which have been successfully employed in SAR studies include Wiener’s index [11], Hosoya’s index [12], Randic’s molecular connectivity index [13], Zagreb group parameters [14, 15], Balaban’s index [16], Schultz’index [17], molecular connectivity topochemical index [18, 19], eccentric connectivity index [20], revised Wiener index [21], E-state index [22], eccentric connectivity topochemical index [23], Zagreb topochemical indices [24], and superaugmented eccentric connectivity indices [25]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
