title: 2D autocorrelation modelling of the inhibitory activity of cytokinin-derived cyclin-dependent kinase inhibitors.
abstract: The inhibitory activity towards p34(cdc2)/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.
authors.affiliation: Unit of Service, Drug Design Department, Experimental Sugar Cane Station Villa Clara-Cienfuegos, Ranchuelo, Villa Clara, CP 53100, Cuba.
authors.forename: Maykel Pérez
authors.initials: MP
authors.lastname: González
authors.forename: Julio
authors.initials: J
authors.lastname: Caballero
authors.forename: Aliuska Morales
authors.initials: AM
authors.lastname: Helguera
authors.forename: Miguel
authors.initials: M
authors.lastname: Garriga
authors.forename: Gerardo
authors.initials: G
authors.lastname: González
authors.forename: Michael
authors.initials: M
authors.lastname: Fernández
mesh_terms: D000818:Animals; D016203:CDC2 Protein Kinase / Q000037:antagonists & inhibitors; D018844:Cyclin-Dependent Kinases / Q000037:antagonists & inhibitors*; D003583:Cytokinins / Q000737:chemistry / Q000494:pharmacology*; D005260:Female; D066298:In Vitro Techniques; D008433:Mathematics; D008954:Models, Biological; D016571:Neural Networks, Computer; D047428:Protein Kinase Inhibitors / Q000737:chemistry / Q000494:pharmacology; D012044:Regression Analysis; D013215:Starfish / Q000201:enzymology; D013329:Structure-Activity Relationship
chemical_list: D003583:Cytokinins; D047428:Protein Kinase Inhibitors; D016203:CDC2 Protein Kinase; D018844:Cyclin-Dependent Kinases