Accurate prediction of enzyme mutant activity based on a multibody statistical potential

Bioinformatics

Volumn 23, Issue 23, 2007, Pages 3155-3161

  Masso, Majid ^a   Vaisman, Iosif I ^a  

^a GEORGE MASON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYME; LYSOZYME;

ACCURACY; ALGORITHM; AREA UNDER THE CURVE; ARTICLE; BACTERIOPHAGE T4; BIOCHEMISTRY; ENZYME ACTIVITY; HUMAN IMMUNODEFICIENCY VIRUS 1; MACHINE LEARNING; MATHEMATICAL ANALYSIS; MOLECULAR BIOLOGY; MUTANT; NONHUMAN; NUCLEOTIDE SEQUENCE; POINT MUTATION; PREDICTION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; STRUCTURAL BIOINFORMATICS;

HUMAN IMMUNODEFICIENCY VIRUS 1;

EID: 36549064186     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm509     Document Type: Article

References (31)

1. Barber,C.B. et al. (1996) The quickhull algorithm for convex hulls. ACM Trans. Math. Softw., 22, 469-483.
2. Bava,K.A. et al. (2004) ProTherm, version 4.0: Thermodynamic database for proteins and mutants. Nucleic Acids Res., 32, D120-D121.
3. Berman,H.M. et al. (2000) The Protein Data Bank. Nucleic Acids Res., 28, 235-242.
4. Bowers,P.M. et al. (2004) Use of logic relationships to decipher protein network organization. Science, 306, 2246-2249.
5. Chasman,D. and Adams,R.M. (2001) Predicting the functional consequences of non-synonymous single nucleotide polymorphisms. J. Mol. Biol., 307, 683-706.
6. Dobson,P.D. and Doig,A.J. (2005) Predicting enzyme class from protein structure without alignments. J. Mol. Biol., 345, 187-199.
7. Fawcett,T. (2003) ROC graphs: Notes and practical considerations for researchers. Technical report HPL-2003-4. Hewlett-Packard Labs, Palo Alto.
8. Frank,E. et al. (2004) Data mining in bioinformatics using Weka. Bioinformatics, 20, 2479-2481.
9. Han,L.Y. et al. (2005) Prediction of functional class of novel viral proteins by a statistical learning method irrespective of sequence similarity. Virology, 331, 136-143.
10. Hand,D.J. and Till,R.J. (2001) A simple generalization of the area under the ROC curve to multiple class classification problems. Mach. Learn. 45, 171-186.
11. Hanley,J.A. and McNeil,B.J. (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143 29-36.
12. Kantor,R. et al. (2004) Evolution of resistance to drugs in HIV-1-infected patients failing antiretroviral therapy. AIDS, 18, 1503-1511.
13. Karchin,R. et al. (2005) Improving functional annotation of non-synonomous SNPs with information theory. Pac. Symp. Biocomput. 397-408.
14. Krishnan,V.G. and Westhead,D.R. (2003) A comparative study of machine-learning methods to predict the effects of single nucleotide polymorphisms on protein function. Bioinformatics, 19, 2199-2209.
15. Loeb,D.D. et al. (1989) Complete mutagenesis of the HIV-1 protease. Nature, 340, 397-400.
16. Masso,M. and Vaisman,I.I. (2003) Comprehensive mutagenesis of HIV-1 protease: A computational geometry approach. Biochem. Biophys. Res. Commun., 305, 322-326.
17. Masso,M. et al. (2006) Computational mutagenesis studies of protein structure-function correlations. Proteins, 64, 234-245.
18. Ng,P.C. and Henikoff,S. (2001) Predicting deleterious amino acid substitutions. Genome Res., 11, 863-874.
19. Pazos,F. and Sternberg,M.J. (2004) Automated prediction of protein function and detection of functional sites from structure. Proc. Natl Acad. Sci. USA, 101, 14754-14759.
20. Provost,F. and Domingos,P. (2001) Well-trained PETs: Improving probability estimation trees. In: CeDER Technical report IS-00-04. Stern School of Business, New York University, New York.
21. Quinlan,R. (1993) C4.5: Programs for Machine Learning. Morgan Kaufman Publishers, San Mateo, CA.
22. Ramensky,V. et al. (2002) Human non-synonymous SNPs: Server and survey. Nucleic Acids Res., 30, 3894-3900.
23. Rennell,D. et al. (1991) Systematic mutation of bacteriophage T4 lysozyme. J. Mol. Biol., 222, 67-88.
24. Saunders,C.T. and Baker,D. (2002) Evaluation of structural and evolutionary contributions to deleterious mutation prediction. J. Mol. Biol., 322, 891-901.
25. Singh,R.K. et al. (1996) Delaunay tessellation of proteins: Four body nearest-neighbor propensities of amino acid residues. J. Comput. Biol., 3, 213-221.
26. Sjolander,K. (2004) Phylogenomic inference of protein molecular function: Advances and challenges. Bioinformatics, 20, 170-179.
27. Sunyaev,S. et al. (2001) Prediction of deleterious human alleles: Hum. Mol. Genet., 10, 591-597.
28. Tian,W. et al. (2004) EFICAz: A comprehensive approach for accurate genome-scale enzyme function inference. Nucleic Acids Res. 32, 6226-6239.
29. Vaisman,I.I. et al. (1998) Compositional preferences in quadruplets of nearest neighbor residues in protein structures: statistical geometry analysis. Proc. IEEE Symp. Intell. Syst., 163-168.
30. Wang,Z. and Moult,J. (2001) SNPs, protein structure, and disease. Hum. Mutat., 17, 263-270.
31. Witten,I.H. and Frank,E. (2000) Data Mining. Morgan Kaufmann, San Francisco.