Metric learning for enzyme active-site search

Bioinformatics

Volumn 26, Issue 21, 2010, Pages 2698-2704

  Kato, Tsuyoshi ^a,b   Nagano, Nozomi ^b  

^a UNIVERSITY OF TOKYO   (Japan)

^b NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYME;

ALGORITHM; ARTICLE; CHEMISTRY; ENZYME ACTIVE SITE; PROTEIN DATABASE;

ALGORITHMS; CATALYTIC DOMAIN; DATABASES, PROTEIN; ENZYMES;

EID: 77958500041     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btq519     Document Type: Article

References (26)

1. Amari,S. and Nagaoka,H. (2000) Methods of Information Geometry. AMS and Oxford University Press, New York.
2. Ashkenazy,H. et al. (2010) Consurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res., 38 (Web Server issue), W529-W533.
3. Barker,J.A. and Thornton,J.M. (2003) An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis. Bioinformatics, 19, 1644-1649.
4. Bartlett,G.J. et al. (2002) Analysis of catalytic residues in enzyme active sites. J. Mol. Biol., 324, 105-121.
5. Boyd,S. and Vandenberghe,L. (2004) Convex Optimization. Cambridge University Press, Cambridge, UK.
6. Chou,K.C. and Cai,Y.D. (2004) A novel approach to predict active sites of enzyme molecules. Proteins, 55, 77-82.
7. Dantzig,G.B. (2004) Linear Programming and Extensions. Princeton University Press, Princeton, NJ.
8. Fetrow,J.S. and Skolnick,J. (1998) Method for prediction of protein function from sequence using the sequence-to-structure-to-function paradigm with application to glutaredoxins/thioredoxins and t1 ribonucleases. J. Mol. Biol., 281, 949-968.
9. Gherardini,P.F. et al. (2007) Convergent evolution of enzyme active sites is not a rare phenomenon. J. Mol. Biol., 372, 817-845.
10. Hastie,T. et al. (2003) The Elements of Statistical Learning. Springer, New York, NY.
11. Hinrichs,C. et al. (2009) Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset. Neuroimage, 48, 138-149.
12. Ivanisenko,V.A. et al. (2004) PDBSiteScan: a program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins. Nucleic Acids Res., 32, W549-W554.
13. Kato,T. et al. (2004) A new variational framework for rigid-body alignment. In Fred,A. et al. (eds) Structural, Syntactic, and Statistical Pattern Recognition, Vol. 3138. Springer, Berlin/Heidelberg, pp. 171-179.
14. Kato,T. et al. (2005) Selective integration of multiple biological data for supervised network inference. Bioinformatics, 21, 2488-2495.
15. Kleywegt,G.J. (1999) Recognition of spatial motifs in protein structures. J. Mol. Biol., 285, 1887-1897.
16. Laskowski,R.A. et al. (2005) Protein function prediction using local 3D templates. J. Mol. Biol., 351, 614-626.
17. Loewenstein,Y. et al. (2009) Protein function annotation by homology-based inference. Genome Biol., 10, 207.
18. Nagano,N. et al. (2007) Systematic comparison of catalytic mechanisms of hydrolysis and transfer. Proteins, 66, 147-159.
19. Nagano,N. (2005) EzCatDB: the enzyme catalytic-mechanism database. Nucleic Acids Res., 33, D407-D412.
20. Rosner,B. (2000) Fundamentals of Biostatistics, 5th edn. Duxbury, Pacific Grove, CA.
21. Stark,A. and Russell,R.B. (2003) Annotation in three dimensions. pints: Patterns in non-homologous tertiary structures. Nucleic Acids Res., 31, 3341-334.
22. Torrance,J.W. et al. (2005) Using a library of structural templates to recognise catalytic sites and explore their evolution in homologous families. J. Mol. Biol., 347, 565-581.
23. Wallace,A.C. et al. (1997) TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. application to enzyme active sites. Protein Sci., 6, 2308-2323.
24. Webb,E.C. (1992) Enzyme Nomenclature 1992. Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology. Academic Press Inc., New York.
25. Wright,C.S. (1972) Comparison of the active site stereochemistry and substrate conformation in -chymotrypsin and subtilisin BPN. J. Mol. Biol., 67, 151-163.
26. Yu,S. et al. (2010) L2-norm multiple kernel learning and its application to biomedical data fusion. BMC Bioinformatics, 11, 309.