ProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity

Journal of Proteomics

Volumn 129, Issue , 2015, Pages 16-24

  Xu, T ^a,b   Park, S K ^a   Venable, J D ^a   Wohlschlegel, J A ^a   Diedrich, J K ^a   Cociorva, D ^a   Lu, B ^a   Liao, L ^a   Hewel, J ^a   Han, X ^a   Wong, C C L ^a   Fonslow, B ^a   Delahunty, C ^a   Gao, Y ^a   Shah, H ^a   Yates, J R ^a  

^a SCRIPPS RESEARCH INSTITUTE   (United States)

^b DOW AGROSCIENCES LLC   (United States)

Author keywords

Bioinformatics; Identification; Mass spectrometry; ProLuCID; Proteomics; Sequest

Indexed keywords

SALIVA PROTEIN; PROTEIN;

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ANIMAL CELL; ARTICLE; DATA ANALYSIS SOFTWARE; DATA ANALYSIS SOFTWARE (DEVICE); DEVICE COMPARISON; DISCRIMINANT ANALYSIS; HUMAN; HUMAN CELL; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DATABASE; RADIOISOTOPE DISTRIBUTION; RAT; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; TANDEM MASS SPECTROMETRY; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; DATA MINING; MOLECULAR GENETICS; PEPTIDE MAPPING; PROCEDURES; REPRODUCIBILITY; SEQUENCE ANALYSIS; SOFTWARE;

ALGORITHMS; AMINO ACID SEQUENCE; DATA MINING; DATABASES, PROTEIN; MOLECULAR SEQUENCE DATA; PATTERN RECOGNITION, AUTOMATED; PEPTIDE MAPPING; PROTEINS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; TANDEM MASS SPECTROMETRY;

EID: 84945483526     PISSN: 18743919     EISSN: 18767737     Source Type: Journal    
DOI: 10.1016/j.jprot.2015.07.001     Document Type: Article

References (51)

1. Link A.J., et al. Direct analysis of protein complexes using mass spectrometry. Nat. Biotechnol. 1999, 17:676-682. 10.1038/10890.
2. Washburn M.P., Wolters D., Yates J.R. Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 2001, 19:242-247.
3. Nesvizhskii A.I. Protein identification by tandem mass spectrometry and sequence database searching. Methods Mol. Biol. 2006, 367:87-120.
4. Zhang Y., Fonslow B.R., Shan B., Baek M.C., Yates J.R. Protein analysis by shotgun/bottom-up proteomics. Chem. Rev. 2013, 10.1021/cr3003533.
5. Olsen J.V., et al. Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap. Mol. Cell. Proteomics 2005, 4:2010-2021.
6. Olsen J.V., et al. A dual pressure linear ion trap Orbitrap instrument with very high sequencing speed. Mol. Cell. Proteomics 2009, 8:2759-2769. (M900375-MCP200 [pii]). 10.1074/mcp.M900375-MCP200.
7. Second T.P., et al. Dual-pressure linear ion trap mass spectrometer improving the analysis of complex protein mixtures. Anal. Chem. 2009, 81:7757-7765. 10.1021/ac901278y.
8. Eng J.K., Mccormack A.L., Yates J.R. An approach to correlate tandem mass-spectral data of peptides with amino-acid-sequences in a protein database. J. Am. Soc. Mass Spectrom. 1994, 5:976-989.
9. Diament B.J., Noble W.S. Faster SEQUEST searching for peptide identification from tandem mass spectra. J. Proteome Res. 2011, 10:3871-3879. 10.1021/pr101196n.
10. Eng J.K., Fischer B., Grossmann J., Maccoss M.J. A fast SEQUEST cross correlation algorithm. J. Proteome Res. 2008, 7:4598-4602. 10.1021/pr800420s.
11. Mann M., Wilm M. Error-tolerant identification of peptides in sequence databases by peptide sequence tags. Anal. Chem. 1994, 66:4390-4399.
12. Sunyaev S., Liska A.J., Golod A., Shevchenko A. MultiTag: multiple error-tolerant sequence tag search for the sequence-similarity identification of proteins by mass spectrometry. Anal. Chem. 2003, 75:1307-1315.
13. Tabb D.L., Saraf A., Yates J.R. GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model. Anal. Chem. 2003, 75:6415-6421. 10.1021/ac0347462.
14. Frank A., Tanner S., Bafna V., Pevzner P. Peptide sequence tags for fast database search in mass-spectrometry. J. Proteome Res. 2005, 4:1287-1295. 10.1021/pr050011x.
15. Tanner S., et al. InsPecT: identification of posttranslationally modified peptides from tandem mass spectra. Anal. Chem. 2005, 77:4626-4639. 10.1021/ac050102d.
16. Shevchenko A., Chernushevich I., Wilm M., Mann M. De Novo peptide sequencing by nanoelectrospray tandem mass spectrometry using triple quadrupole and quadrupole/time-of-flight instruments. Methods Mol. Biol. 2000, 146:1-16. (1-59259-045-4-1 [pii]). 10.1385/1-59259-045-4:1.
17. Chen T., Kao M.Y., Tepel M., Rush J., Church G.M. A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry. J. Comput. Biol. 2001, 8:325-337. 10.1089/10665270152530872.
18. Johnson R.S., Taylor J.A. Searching sequence databases via de novo peptide sequencing by tandem mass spectrometry. Mol. Biotechnol. 2002, 22:301-315. (MB:22:3:301 [pii]). 10.1385/MB:22:3:301.
19. Ma B., et al. PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun. Mass Spectrom. 2003, 17:2337-2342. 10.1002/rcm.1196.
20. Lu B., Chen T. A suffix tree approach to the interpretation of tandem mass spectra: applications to peptides of non-specific digestion and post-translational modifications. Bioinformatics 2003, 19(Suppl. 2):II113-II121.
21. Searle B.C., et al. High-throughput identification of proteins and unanticipated sequence modifications using a mass-based alignment algorithm for MS/MS de novo sequencing results. Anal. Chem. 2004, 76:2220-2230. 10.1021/ac035258x.
22. Chi H., et al. pNovo: de novo peptide sequencing and identification using HCD spectra. J. Proteome Res. 2010, 9:2713-2724. 10.1021/pr100182k.
23. Chi H., et al. pNovo+: de novo peptide sequencing using complementary HCD and ETD tandem mass spectra. J. Proteome Res. 2013, 12:615-625. 10.1021/pr3006843.
24. Frank A., Pevzner P. PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal. Chem. 2005, 77:964-973.
25. Perkins D.N., Pappin D.J., Creasy D.M., Cottrell J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 1999, 20:3551-3567.
26. Clauser K.R., Baker P., Burlingame A.L. Role of accurate mass measurement (+/- 10ppm) in protein identification strategies employing MS or MS/MS and database searching. Anal. Chem. 1999, 71:2871-2882.
27. Fenyo D., Qin J., Chait B.T. Protein identification using mass spectrometric information. Electrophoresis 1998, 19:998-1005. 10.1002/elps.1150190615.
28. Zhang N., Aebersold R., Schwikowski B. ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Proteomics 2002, 2:1406-1412. 10.1002/1615-9861(200210)2:10<1406::AID-PROT1406>3.0.CO;2-9.
29. Sadygov R.G., Yates J.R. A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases. Anal. Chem. 2003, 75:3792-3798.
30. Craig R., Beavis R.C. TANDEM: matching proteins with tandem mass spectra. Bioinformatics 2004, 20:1466-1467. 10.1093/bioinformatics/bth092.
31. Geer L.Y., et al. Open mass spectrometry search algorithm. J. Proteome Res. 2004, 3:958-964.
32. Sadygov R., Wohlschlegel J., Park S.K., Xu T., Yates J.R. Central limit theorem as an approximation for intensity-based scoring function. Anal. Chem. 2006, 78:89-95.
33. Searle B.C., et al. Identification of protein modifications using MS/MS de novo sequencing and the OpenSea alignment algorithm. J. Proteome Res. 2005, 4:546-554.
34. Tang W.H., et al. Discovering known and unanticipated protein modifications using MS/MS database searching. Anal. Chem. 2005, 77:3931-3946.
35. Bandeira N., Tsur D., Frank A., Pevzner P.A. Protein identification by spectral networks analysis. Proc. Natl. Acad. Sci. U. S. A. 2007, 104:6140-6145. (0701130104 [pii]). 10.1073/pnas.0701130104.
36. Na S., Bandeira N., Paek E. Fast multi-blind modification search through tandem mass spectrometry. Mol. Cell. Proteomics 2012, 11. (M111 010199). 10.1074/mcp.M111.010199.
37. Han X., He L., Xin L., Shan B., Ma B. PeaksPTM: mass spectrometry-based identification of peptides with unspecified modifications. J. Proteome Res. 2011, 10:2930-2936. 10.1021/pr200153k.
38. Kapp E.A., et al. An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis. Proteomics 2005, 5:3475-3490. 10.1002/pmic.200500126.
39. Hu Q., et al. The Orbitrap: a new mass spectrometer. J. Mass Spectrom. 2005, 40:430-443.
40. Yates J.R., Cociorva D., Liao L., Zabrouskov V. Performance of a linear ion trap-Orbitrap hybrid for peptide analysis. Anal. Chem. 2006, 78:493-500. 10.1021/ac0514624.
41. Venable J.D., Wohlschlegel J., McClatchy D.B., Park S.K., Yates J.R. Relative quantification of stable isotope labeled peptides using a linear ion trap-orbitrap hybrid mass spectrometer. Anal. Chem. 2007, 79:3056-3064.
42. Tabb D.L., McDonald W.H., Yates J.R. DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics. J. Proteome Res. 2002, 1:21-26.
43. Cociorva D., Tabb D.L., Yates J.R. Validation of tandem mass spectrometry database search results using DTASelect. Current protocols in bioinformatics / editoral board, Andreas D. Baxevanis . . . [et al.] 2007, (Chapter 13, Unit 13 14). 10.1002/0471250953.bi1304s16.
44. Keller A., Nesvizhskii A.I., Kolker E., Aebersold R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 2002, 74:5383-5392.
45. Carvalho P.C., et al. Search engine processor: filtering and organizing peptide spectrum matches. Proteomics 2012, 12:944-949. 10.1002/pmic.201100529.
46. Lu B., Xu T., Park S.K., Yates J.R. Shotgun protein identification and quantification by mass spectrometry. Methods Mol. Biol. 2009, 564:261-288. 10.1007/978-1-60761-157-8_15.
47. Rockwood A.L., VanOrden S.L., Smith R.D. Ultrahigh resolution isotope distribution calculations. Rapid Commun. Mass Spectrom. 1996, 10:54-59.
48. Grubbs F.E. Procedures for detecting outlying observations in samples. Technometrics 1969, 11:1-21.
49. MacCoss M.J., Wu C.C., Liu H., Sadygov R., Yates J.R. A correlation algorithm for the automated quantitative analysis of shotgun proteomics data. Anal. Chem. 2003, 75:6912-6921.
50. Swets J.A. Measuring the accuracy of diagnostic systems. Science 1988, 240:1285-1293.
51. Carvalho P.C., et al. YADA: a tool for taking the most out of high-resolution spectra. Bioinformatics 2009, 25:2734-2736. 10.1093/bioinformatics/btp489.