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Topochemical Models for Prediction of Telomerase Inhibitory Activity of Flavonoids
Author(s) -
Dureja Harish,
Madan Anil Kumar
Publication year - 2007
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2007.00526.x
Subject(s) - topological index , chemistry , adjacency list , telomerase , index (typography) , similarity (geometry) , set (abstract data type) , molecular descriptor , computational biology , computer science , artificial intelligence , biology , stereochemistry , biochemistry , quantitative structure–activity relationship , computational chemistry , algorithm , gene , world wide web , programming language , image (mathematics)
In the present study, the relationship between the topochemical indices and telomerase inhibitory activity of flavonoids has been investigated. Three topochemical indices, Wiener's topochemical index (a distance‐based topochemical descriptor), molecular connectivity topochemical index (an adjacency‐based topochemical descriptor) and superadjacency topochemical index (an adjacency cum distance‐based topochemical descriptor) were used for the present investigation. The values of the Wiener's topochemical index, molecular connectivity topochemical index and superadjacency topochemical index for each of the 30 analogues comprising the data set were computed using an in‐house computer program. Resultant data was analysed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each analogue involved in the data set using these models, which was then compared with the reported telomerase inhibitory activity. Statistical significance of proposed models was investigated using intercorrelation analysis. Accuracy of prediction using proposed models was found to vary from 80% to 83%.