BCL::Align-Sequence alignment and fold recognition with a custom scoring function online

Gene

Volumn 422, Issue 1-2, 2008, Pages 41-46

  Dong, Elizabeth ^a   Smith, Jarrod ^a   Heinze, Sten ^a   Alexander, Nathan ^a   Meiler, Jens ^a  

^a VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Dynamic programming; Fold recognition; Multiple sequence alignment; Needleman Wunsch algorithm; Parametric sequence alignment

Indexed keywords

MEMBRANE PROTEIN;

ACCURACY; ARTICLE; GENETIC ALGORITHM; MOLECULAR DYNAMICS; MOLECULAR WEIGHT; MONTE CARLO METHOD; PRIORITY JOURNAL; PROTEIN FAMILY; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; ROC CURVE; SCORING SYSTEM; SEQUENCE ALIGNMENT; STANDARD;

ALGORITHMS; INTERNET; MONTE CARLO METHOD; PROTEIN FOLDING; PROTEIN STRUCTURE, SECONDARY; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 49049115520     PISSN: 03781119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.gene.2008.06.006     Document Type: Article

References (40)

1. Altschul S.F., Gish W., Miller W., Myers E.W., and Lipman D.J. Basic local alignment search tool. J. Mol. Biol. 215 (1990) 403-410
2. Altschul S.F., Madden T.L., Schaffer A.A., Zhang J., Zhang Z., Miller W., and Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25 (1997) 3389-3402
3. Bairoch A., and Apweiler R. The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1998. Nucleic Acids Res. 26 (1998) 38-42
4. Barton G.J., and Sternberg M.J. Evaluation and improvements in the automatic alignment of protein sequences. Protein Eng. 1 (1987) 89-94
5. Benson D.A., Karsch-Mizrachi I., Lipman D.J., Ostell J., and Wheeler D.L. GenBank. Nucleic Acids Res. 34 (2006) D16-D20
6. Benson D.A., Karsch-Mizrachi I., Lipman D.J., Ostell J., and Wheeler D.L. GenBank. Nucleic Acids Res. 35 (2007) D21-D25
7. Berman H.M., Westbrook J., Feng Z., Gilliland G., Bhat T.N., Weissig H., Shindyalov I.N., and Bourne P.E. The protein data bank. Nucleic Acids Res. 28 (2000) 235-242
8. Blackshields G., Wallace I.M., Larkin M., and Higgins D.G. Analysis and comparison of benchmarks for multiple sequence alignment. In Silico Biol. 6 (2006) 321-339
9. Boutonnet N.S., Rooman M.J., Ochagavia M.E., Richelle J., and Wodak S.J. Optimal protein structure alignments by multiple linkage clustering: application to distantly related proteins. Protein Eng. 8 (1995) 647-662
10. Castillo-Davis C.I., Kondrashov F.A., Hartl D.L., and Kulathinal R.J. The functional genomic distribution of protein divergence in two animal phyla: coevolution, genomic conflict, and constraint. Genome Res. 14 (2004) 802-811
11. Chivian D., and Baker D. Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection. Nucleic Acids Res. 34 (2006) e112
12. Cline M., Hughey R., and Karplus K. Predicting reliable regions in protein sequence alignments. Bioinformatics 18 (2002) 306-314
13. Dayhoff M.O., Schwartz R.M., and Orcutt B.C. A model of evolutionary change in proteins. In: Dayhoff M.O. (Ed). Atlas of Protein Sequence and Structure (1978), National Biomedical Research Foundation, Washington, D.C. 345-352
14. Do C.B., Mahabhashyam M.S., Brudno M., and Batzoglou S. ProbCons: probabilistic consistency-based multiple sequence alignment. Genome Res. 15 (2005) 330-340
15. Edgar R.C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32 (2004) 1792-1797
16. Edgar R.C., and Sjolander K. A comparison of scoring functions for protein sequence profile alignment. Bioinformatics 20 (2004) 1301-1308
17. Feng D.F., and Doolittle R.F. Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J. Mol. Evol. 25 (1987) 351-360
18. Ginalski K., Elofsson A., Fischer D., and Rychlewski L. 3D-Jury: a simple approach to improve protein structure predictions. Bioinformatics 19 (2003) 1015-1018
19. Ginalski K., Pas J., Wyrwicz L.S., von Grotthuss M., Bujnicki J.M., and Rychlewski L. ORFeus: detection of distant homology using sequence profiles and predicted secondary structure. Nucleic Acids Res. 31 (2003) 3804-3907
20. Henikoff S., and Henikoff J.G. Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. U.S.A. 89 (1992) 10915-10919
21. Hogeweg P., and Hesper B. The alignment of sets of sequences and the construction of phyletic trees: an integrated method. J. Mol. Evol. 20 (1984) 175-186
22. Hughey R., and Krogh A. Hidden Markov models for sequence analysis: extension and analysis of the basic method. Comput. Appl. Biosci. 12 (1996) 95-107
23. Jones D.T. GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences. J. Mol. Biol. 287 (1999) 797-815
24. Karplus K., Barrett C., and Hughey R. Hidden Markov models for detecting remote protein homologies. Bioinformatics 14 (1998) 846-856
25. Lindahl E., and Elofsson A. Identification of related proteins on family, superfamily and fold level. J. Mol. Biol. 295 (2000) 613-625
26. Lundstrom J., Rychlewski L., Bujnicki J., and Elofsson A. Pcons: a neural-network-based consensus predictor that improves fold recognition. Protein Sci. 10 (2001) 2354-2362
27. Meiler J., and Baker D. Coupled prediction of protein secondary and tertiary structure. Proc. Natl. Acad. Sci. U. S. A. 100 (2003) 12105-12110
28. Mewes H.W., Heumann K., Kaps A., Mayer K., Pfeiffer F., Stocker S., and Frishman D. MIPS: a database for genomes and protein sequences. Nucleic Acids Res. 27 (1999) 44-48
29. Needleman S.B., and Wunsch C.D. A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48 (1970) 443-453
30. Notredame C., Higgins D.G., and Heringa J. T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 302 (2000) 205-217
31. Phillips A., Janies D., and Wheeler W. Multiple sequence alignment in phylogenetic analysis. Mol. Phylogenet. Evol. 16 (2000) 317-330
32. Rost B., and Sander C. Improved prediction of protein secondary structure by use of sequence profiles and neural networks. Proc. Natl. Acad. Sci. U. S. A. 90 (1993) 7558-7562
33. Rychlewski L., Jaroszewski L., Li W., and Godzik A. Comparison of sequence profiles. Strategies for structural predictions using sequence information. Protein Sci. 9 (2000) 232-241
34. Sauder J.M., Arthur J.W., and Dunbrack Jr. R.L. Large-scale comparison of protein sequence alignment algorithms with structure alignments. Proteins 40 (2000) 6-22
35. Shindyalov I.N., and Bourne P.E. Protein structure alignment by incremental combinatorial extension (CE) of the optimal path. Protein Eng. 11 (1998) 739-747
36. Thompson J.D., Higgins D.G., and Gibson T.J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22 (1994) 4673-4680
37. Thompson J.D., Plewniak F., and Poch O. A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Res. 27 (1999) 2682-2690
38. Van Walle I., Lasters I., and Wyns L. Align-m-a new algorithm for multiple alignment of highly divergent sequences. Bioinformatics 20 (2004) 1428-1435
39. Van Walle I., Lasters I., and Wyns L. SABmark-a benchmark for sequence alignment that covers the entire known fold space. Bioinformatics 21 (2005) 1267-1268
40. Wang G., and Dunbrack Jr. R.L. PISCES: a protein sequence culling server. Bioinformatics 19 (2003) 1589-1591