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Telomerase inhibitory activity by stabilization of G-quartet: A QSAR approach using 2D autocorrelation descriptors
1, 2 , 2 , * 2 , 1 , 2 , 3
1  Department of Chemistry. Central University of Las Villas. Santa Clara 54830, Villa Clara, Cuba
2  Molecular Simulation & Drug Design Group, Centre of Chemical Bioactive, Central University of Las Villas, Santa Clara 54830, Villa Clara, Cuba
3  Department of Organic Chemistry, Vigo University, C.P. 36200 Vigo, Spain

Abstract: A QSAR approach on a dataset of 546 inhibitors of telomerase activity, by interaction with G-quadruplex DNA, was carried out using 2D autocorrelation descriptors. A linear discriminant analysis (LDA) was made on a training set of 437 compounds and it was assessed with 109 compounds belongs to the test set. The model good classified the 80.09% of the dataset and the percentage of good prediction was 78.89%. Only 5 compounds were not classified. The 2D autocorrelation descriptors are able to explain the factors that stabilize the G-quadruplex structure and consequently the inhibition of telomerase by this biological mechanism.
Keywords: Telomerase inhibitors, G-quadruplex, molecular descriptors, QSAR