Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction |
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| Authors: | Drew H Bryant Mark Moll Brian Y Chen Viacheslav Y Fofanov Lydia E Kavraki |
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| Institution: | (1) Department of Computer Science, Rice University, Houston, TX, USA;(2) Center for Computational Biology and Bioinformatics, Howard Hughes Medical Institute, Columbia University, New York, NY, USA;(3) Department of Statistics, Rice University, Houston, TX, USA;(4) Department of Bioengineering, Rice University, Houston, TX, USA;(5) Department of Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, TX, USA |
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| Abstract: | Background Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of
a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined
as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation.
Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances
of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic
sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain
topology levels. |
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