A model for the recognition of protein kinases based on the entropy of 3D van der Waals interactions.
The study and prediction of kinase function (kinomics) is of major importance for proteome research due to the widespread distribution of kinases. However, the prediction of protein function based on the similarity between a functionally annotated 3D template and a query structure may fail, for instance, if a similar protein structure cannot be identified. Alternatively, function can be assigned using 3D-structural empirical parameters. In previous studies, we introduced parameters based on electrostatic entropy (Proteins 2004, 56, 715) and molecular vibration entropy (Bioinformatics 2003, 19, 2079) but ignored other important factors such as van der Waals (vdw) interactions. In the work described here, we define 3D-vdw entropies (degrees theta(k)) and use them for the first time to derive a classifier for protein kinases. The model classifies correctly 88.0% of proteins in training and more than 85.0% of proteins in validation studies. Principal components analysis of heterogeneous proteins demonstrated that degrees theta(k) codify information that is different to that described by other bulk or folding parameters. In additional validation experiments, the model recognized 129 out of 142 kinases (90.8%) and 592 out of 677 non-kinases (87.4%) not used above. This study provides a basis for further consideration of degrees theta(k) as parameters for the empirical search for structure-function relationships.
Gonzalez-Díaz
Humberto
H
Department of Organic Chemistry and Institute of Industrial Pharmacy, Faculty of Pharmacy, University of Santiago de Compostela 15782, Spain. gonzalezdiazh@yahoo.es
Saiz-Urra
Liane
L
Molina
Reinaldo
R
Santana
Lourdes
L
Uriarte
Eugenio
E
D019277:Entropy; D008958:Models, Molecular; D011336:Probability; D011487:Protein Conformation; D011494:Protein Kinases / Q000737:chemistry*; D015203:Reproducibility of Results; D055672:Static Electricity; D014961:X-Ray Diffraction
D011494:Protein Kinases