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has been cited by the following article:

• TITLE: Prediction of Antagonistic Activity of β-Carboline and Its Derivatives Using Topological Descriptors

  AUTHORS: Anil Kumar Soni, Gajendra Pal Singh, Vishnu Kumar Sahu

  KEYWORDS: β–carboline, antagonistic activity, PM3, connectivity index and kappa shape index

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.11 No.5, May 28, 2021

  ABSTRACT: Prediction of antagonistic activity of β-carboline and its thirteen derivatives has been made using topological descriptors viz, connectivity index, and kappa shape index of different orders. For evaluation of values of descriptor, molecular modeling and geometry optimization of all the compounds were carried out with CAChe Pro software by opting semiempirical PM3 method using MOPAC 2002. For prediction of activity multiple linear regression analysis (MLR) was performed. MLR analysis has been made by Project Leader Software associated with CAChe by using the above descriptors as independent variables and biological activity as dependent variables. We were performed leave-one-out methods and the result reflected a direct relationship between biological activity and connectivity index of zero order, while indirect relationship with connectivity index of second order and thus connectivity index is a reliable descriptor to predict the biological activity of β-carboline and its various derivatives.