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2D Autocorrelation Modelling of the Inhibitory Activity of Cytokinin-Derived Cyclin-Dependent Kinase Inhibitors

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Abstract

The inhibitory activity towards p34cdc 2/cyclin b kinase (CBK) enzyme of 30 cytokinin-derived compounds has been successfully modelled using 2D spatial autocorrelation vectors. Predictive linear and non-linear models were obtained by forward stepwise multi-linear regression analysis (MRA) and artificial neural network (ANN) approaches respectively. A variable selection routine that selected relevant non-linear information from the data set was employed prior to networks training.

The best ANN with three input variables was able to explain about 87% data variance in comparison with 80% by the linear equation using the same number of descriptors. Similarly, the neural network had higher predictive power. The MRA model showed a linear dependence between the inhibitory activities and the spatial distributions of masses, electronegativities and van der Waals volumes on the inhibitors molecules. Meanwhile, ANN model evidenced the occurrence of non-linear relationships between the inhibitory activity and the mass distribution at different topological distance on the cytokinin-derived compounds. Furthermore, inhibitors were well distributed regarding its activity levels in a Kohonen self-organizing map (SOM) built using the input variables of the best neural network.

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Authors and Affiliations

  1. Unit of Service, Drug Design Department, Experimental Sugar Cane Station “Villa Clara-Cienfuegos,”Ranchuelo, Villa Clara, C.P, 53100, Cuba

    Maykel Pérez González

  2. Chemical Bioactive Center, Central University of Las Villas, Santa Clara, Villa Clara, C.P, 54830, Cuba

    Maykel Pérez González & Aliuska Morales Helguera

  3. Molecular Modeling Group, Center for Biotechnological Studies, Faculty of Agronomy, University of Matanzas, Matanzas, Matanzas, C.P, 44740, Cuba

    Julio Caballero & Michael Fernández

  4. Probiotic Group, Center for Biotechnological Studies, Faculty of Agronomy, University of Matanzas, Matanzas, Matanzas, C.P, 44740, Cuba

    Julio Caballero & Michael Fernández

  5. Department of Chemistry, Faculty of Chemistry and Pharmacy, Central University of Las Villas, Santa Clara, Villa Clara, C.P, 54830, Cuba

    Aliuska Morales Helguera

  6. Plant Biotechnology Group, Center for Biotechnological Studies, Faculty of Agronomy, University of Matanzas, Matanzas, Matanzas, C.P, 44740, Cuba

    Miguel Garriga & Gerardo González

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  1. Maykel Pérez González
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  2. Julio Caballero
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  3. Aliuska Morales Helguera
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  4. Miguel Garriga
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  5. Gerardo González
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  6. Michael Fernández
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Correspondence to Michael Fernández.

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González, M.P., Caballero, J., Helguera, A.M. et al. 2D Autocorrelation Modelling of the Inhibitory Activity of Cytokinin-Derived Cyclin-Dependent Kinase Inhibitors. Bull. Math. Biol. 68, 735–751 (2006). https://doi.org/10.1007/s11538-005-9006-3

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  • DOI: https://doi.org/10.1007/s11538-005-9006-3

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