Automatic epitope recognition in proteins oriented to the system for macromolecular interaction assessment MIAX.
In the present work we evaluate the performance of an algorithm for the automatic recognition of binding sites in proteins as well as in other macromolecules whose interactions are involved in many cellular and physiological processes. The algorithm is a combination of an unsupervised learning algorithm - based on Kohonen self organizing maps - to characterize the properties of patches of protein solvent accessible surfaces and a filtering algorithm to establish both the physical boundaries of the patches as well as the level of contribution of different and distant atoms involved in the interaction. We have found that the algorithm performs extremely well in a set of randomly selected protein complexes for which the interaction interfaces are extracted and compared with the results of the algorithm. A statistical evaluation of the algorithm is additionally performed by analysis of the degree of hydrophobicity and hydrophilicity of the output patches and comparison with that of the observed interface constituent amino acids.
Yoshimori
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Toyohashi University of Technology, Ecological Engineering, 1-1, Tempaku, Toyohashi, Aichi 331-8580, Japan. yosimori@translell.eco.tut.ac.jp
Del Carpio
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CA
D000465:Algorithms; D001665:Binding Sites; D019295:Computational Biology; D000939:Epitopes; D046911:Macromolecular Substances; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry* / Q000276:immunology* / Q000378:metabolism
D000939:Epitopes; D046911:Macromolecular Substances; D011506:Proteins