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Title	en Exploring functionally related enzymes using radially distributed properties of active sites around the reacting points of bound ligands
Creator	en Ueno, Keisuke en Mineta, Katsuhiko NRID 1000040374615 en Ito, Kimihito NRID 1000060396314 en Endo, Toshinori NRID 1000000323692
Accessrights	open access
Rights	http://creativecommons.org/licenses/by/2.0/ en Creative Commons Attribution 2.0 Generic
Subject	NDC 460
Description	Abstract en Background: Structural genomics approaches, particularly those solving the 3D structures of many proteins with unknown functions, have increased the desire for structure-based function predictions. However, prediction of enzyme function is difficult because one member of a superfamily may catalyze a different reaction than other members, whereas members of different superfamilies can catalyze the same reaction. In addition, conformational changes, mutations or the absence of a particular catalytic residue can prevent inference of the mechanism by which catalytic residues stabilize and promote the elementary reaction. A major hurdle for alignment-based methods for prediction of function is the absence (despite its importance) of a measure of similarity of the physicochemical properties of catalytic sites. To solve this problem, the physicochemical features radially distributed around catalytic sites should be considered in addition to structural and sequence similarities. Results: We showed that radial distribution functions (RDFs), which are associated with the local structural and physicochemical properties of catalytic active sites, are capable of clustering oxidoreductases and transferases by function. The catalytic sites of these enzymes were also characterized using the RDFs. The RDFs provided a measure of the similarity among the catalytic sites, detecting conformational changes caused by mutation of catalytic residues. Furthermore, the RDFs reinforced the classification of enzyme functions based on conventional sequence and structural alignments. Conclusions: Our results demonstrate that the application of RDFs provides advantages in the functional classification of enzymes by providing information about catalytic sites.
Publisher	en BioMed Central
Date	Issued2012-04-26
Language	eng
Resource Type	journal article
Version Type	VoR
Identifier	HDL http://hdl.handle.net/2115/50022
Relation	isIdenticalTo DOI https://doi.org/10.1186/1472-6807-12-5
Journal	PISSN 1472-6807 en BMC Structural Biology Volume Number12 Page Start5
File	fulltext BMCSB12_5.pdf 832.19 KB (application/pdf) Issued2012-04-26
Oaidate	2023-07-26