FlexSLiM: a Novel Approach for Short Linear Motif Discovery in Protein Sequences

ABSTRACT

Short linear motifs are 3 to 11 amino acid long peptide patterns that play important regulatory roles in modulating protein activities. Although they are abundant in proteins, it is often difficult to discover them by experiments, because of the low affinity binding and transient interaction of short linear motifs with their partners. Moreover, available computational methods cannot effectively predict short linear motifs, due to their short and degenerate nature. Here we developed a novel approach, FlexSLiM, for reliable discovery of short linear motifs in protein sequences. By testing on simulated data and benchmark experimental data, we demonstrated that FlexSLiM more effectively identifies short linear motifs than existing methods. We provide a general tool that will advance the understanding of short linear motifs, which will facilitate the research on protein targeting signals, protein post-translational modifications, and many others.

References

1. H. Dinkel, K. Van Roey, S. Michael, M. Kumar, B. Uyar, B. Altenberg, V. Milchevskaya, M. Schneider, H. Kuhn, A. Behrendt, S. L. Dahl, V. Damerell, S. Diebel, S. Kalman, S. Klein, A. C. Knudsen, C. Mader, S. Merrill, A. Staudt, V. Thiel, L. Welti, N. E. Davey, F. Diella, and T. J. Gibson, "ELM 2016--data update and new functionality of the eukaryotic linear motif resource," Nucleic Acids Res, vol. 44, no. D1, pp. D294--300, Jan 4, 2016.
2. S. Lemeer, and A. J. R. Heck, "The phosphoproteomics data explosion," Current Opinion in Chemical Biology, vol. 13, no. 4, pp. 414--420, Oct, 2009.
3. S. P. Mirza, and M. Olivier, "Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry," Physiological Genomics, vol. 33, no. 1, pp. 3--11, Mar 14, 2008.
4. H. Dumortier, J. K. Gunnewiek, J. P. Roussel, Y. van Aarssen, J. P. Briand, W. J. van Venrooij, and S. Muller, "At least three linear regions but not the zinc-finger domain of U1C protein are exposed at the surface of the protein in solution and on the human spliceosomal U1 snRNP particle," Nucleic Acids Research, vol. 26, no. 23, pp. 5486--5491, Dec 1, 1998.
5. M. Kikuchi, M. Kataoka, T. Kojima, T. Horibe, K. Fujieda, T. Kimura, and T. Tanaka, "Single chain antibodies that recognize the N-glycosylation site," Archives of Biochemistry and Biophysics, vol. 422, no. 2, pp. 221--229, Feb 15, 2004.
6. S. Basu, and D. Plewczynski, "AMS 3.0: prediction of post-translational modifications," BMC Bioinformatics, vol. 11, pp. 210, Apr 28, 2010.
7. R. Gutman, C. Berezin, R. Wollman, Y. Rosenberg, and N. Ben-Tal, "QuasiMotiFinder: protein annotation by searching for evolutionarily conserved motif-like patterns," Nucleic Acids Research, vol. 33, pp. W255-W261, Jul 1, 2005.
8. T. Mi, J. C. Merlin, S. Deverasetty, M. R. Gryk, T. J. Bill, A. W. Brooks, L. Y. Lee, V. Rathnayake, C. A. Ross, D. P. Sargeant, C. L. Strong, P. Watts, S. Rajasekaran, and M. R. Schiller, "Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences," Nucleic Acids Research, vol. 40, no. D1, pp. D252--D260, Jan, 2012.
9. J. C. Obenauer, L. C. Cantley, and M. B. Yaffe, "Scansite 2.0: proteome-wide prediction of cell signaling interactions using short sequence motifs," Nucleic Acids Research, vol. 31, no. 13, pp. 3635--3641, Jul 1, 2003.
10. C. Ramu, "SIRW: a web server for the Simple Indexing and Retrieval System that combines sequence motif searches with keyword searches," Nucleic Acids Research, vol. 31, no. 13, pp. 3771--3774, Jul 1, 2003.
11. E. Olorin, K. T. O'Brien, N. Palopoli, A. Perez-Bercoff, D. C. Shields, and R. J. Edwards, "SLiMScape 3.x: a Cytoscape 3 app for discovery of Short Linear Motifs in protein interaction networks," F1000Res, vol. 4, pp. 477, 2015.
12. H. Y. K. Lam, P. M. Kim, J. Mok, R. Tonikian, S. S. Sidhu, B. E. Turk, M. Snyder, and M. B. Gerstein, "MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains," Bmc Bioinformatics, vol. 11, May 11, 2010.
13. D. Schwartz, and S. P. Gygi, "An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets," Nature Biotechnology, vol. 23, no. 11, pp. 1391--1398, Nov, 2005.
14. M. Fuxreiter, P. Tompa, and I. Simon, "Local structural disorder imparts plasticity on linear motifs," Bioinformatics, vol. 23, no. 8, pp. 950--6, Apr 15, 2007.
15. R. J. Edwards, N. E. Davey, and D. C. Shields, "SLiMFinder: a probabilistic method for identifying over-represented, convergently evolved, short linear motifs in proteins," PLoS One, vol. 2, no. 10, pp. e967, Oct 3, 2007.
16. J. Hu, and F. Zhang, "BayesMotif: de novo protein sorting motif discovery from impure datasets," BMC Bioinformatics, vol. 11 Suppl 1, pp. S66, Jan 18, 2010.
17. W. Hugo, F. Song, Z. Aung, S. K. Ng, and W. K. Sung, "SLiM on Diet: finding short linear motifs on domain interaction interfaces in Protein Data Bank," Bioinformatics, vol. 26, no. 8, pp. 1036--42, Apr 15, 2010.
18. D. S. Lieber, O. Elemento, and S. Tavazoie, "Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes," Plos One, vol. 5, no. 12, Dec 29, 2010.
19. V. Neduva, and R. B. Russell, "DILIMOT: discovery of linear motifs in proteins," Nucleic Acids Research, vol. 34, pp. W350-W355, Jul 1, 2006.
20. I. Rigoutsos, and A. Floratos, "Combinatorial pattern discovery in biological sequences: the TEIRESIAS algorithm (vol 14, pg 55, 1998)," Bioinformatics, vol. 14, no. 2, pp. 229--229, 1998.
21. S. H. Tan, W. Hugo, W. K. Sung, and S. K. Ng, "A correlated motif approach for finding short linear motifs from protein interaction networks," Bmc Bioinformatics, vol. 7, Nov 16, 2006.
22. N. E. Davey, J. L. Cowan, D. C. Shields, T. J. Gibson, M. J. Coldwell, and R. J. Edwards, "SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions," Nucleic Acids Res, vol. 40, no. 21, pp. 10628--41, Nov, 2012.
23. N. E. Davey, K. Van Roey, R. J. Weatheritt, G. Toedt, B. Uyar, B. Altenberg, A. Budd, F. Diella, H. Dinkel, and T. J. Gibson, "Attributes of short linear motifs," Mol Biosyst, vol. 8, no. 1, pp. 268--81, Jan, 2012.
24. G. Grahne, and J. F. Zhu, "Fast algorithms for frequent itemset mining using FP-trees," Ieee Transactions on Knowledge and Data Engineering, vol. 17, no. 10, pp. 1347--1362, Oct, 2005.
25. J. W. Han, J. Pei, and Y. W. Yin, "Mining frequent patterns without candidate generation," Sigmod Record, vol. 29, no. 2, pp. 1--12, Jun, 2000.
26. D. R. Zerbino, P. Achuthan, W. Akanni, M. R. Amode, D. Barrell, J. Bhai, K. Billis, C. Cummins, A. Gall, C. G. Giron, L. Gil, L. Gordon, L. Haggerty, E. Haskell, T. Hourlier, O. G. Izuogu, S. H. Janacek, T. Juettemann, J. K. To, M. R. Laird, I. Lavidas, Z. Liu, J. E. Loveland, T. Maurel, W. McLaren, B. Moore, J. Mudge, D. N. Murphy, V. Newman, M. Nuhn, D. Ogeh, C. K. Ong, A. Parker, M. Patricio, H. S. Riat, H. Schuilenburg, D. Sheppard, H. Sparrow, K. Taylor, A. Thormann, A. Vullo, B. Walts, A. Zadissa, A. Frankish, S. E. Hunt, M. Kostadima, N. Langridge, F. J. Martin, M. Muffato, E. Perry, M. Ruffier, D. M. Staines, S. J. Trevanion, B. L. Aken, F. Cunningham, A. Yates, and P. Flicek, "Ensembl 2018," Nucleic Acids Res, vol. 46, no. D1, pp. D754-D761, Jan 4, 2018.
27. M. Glittenberg, C. Pitsouli, C. Garvey, C. Delidakis, and S. Bray, "Role of conserved intracellular motifs in Serrate signalling, cis-inhibition and endocytosis," EMBO J, vol. 25, no. 20, pp. 4697--706, Oct 18, 2006.
28. J. E. Hopcroft, and J. D. Ullman, Introduction to automata theory, languages, and computation, Reading, Mass.: Addison-Wesley, 1979.
29. G. Nuel, L. Regad, J. Martin, and A. C. Camproux, "Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data," Algorithms for Molecular Biology, vol. 5, Jan 26, 2010.
30. P. Ribeca, and E. Raineri, "Faster exact Markovian probability functions for motif occurrences: a DFA-only approach," Bioinformatics, vol. 24, no. 24, pp. 2839--2848, Dec 15, 2008.
31. Z. Dosztanyi, V. Csizmok, P. Tompa, and I. Simon, "IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content," Bioinformatics, vol. 21, no. 16, pp. 3433--4, Aug 15, 2005.
32. J. C. Wootton, and S. Federhen, "Statistics of Local Complexity in Amino-Acid-Sequences and Sequence Databases," Computers & Chemistry, vol. 17, no. 2, pp. 149--163, Jun, 1993.
33. C. M. Gould, F. Diella, A. Via, P. Puntervoll, C. Gemund, S. Chabanis-Davidson, S. Michael, A. Sayadi, J. C. Bryne, C. Chica, M. Seiler, N. E. Davey, N. Haslam, R. J. Weatheritt, A. Budd, T. Hughes, J. Pas, L. Rychlewski, G. Trave, R. Aasland, M. Helmer-Citterich, R. Linding, and T. J. Gibson, "ELM: the status of the 2010 eukaryotic linear motif resource," Nucleic Acids Res, vol. 38, no. Database issue, pp. D167--80, Jan, 2010.
34. F. Yu, Z. Chen, Y. Diao, T. V. Lakshman, and R. H. Katz, "Fast and memory-efficient regular expression matching for deep packet inspection."

Index Terms

• Information systems

  • Information retrieval

    • Specialized information retrieval

      • Environment-specific retrieval

        • Desktop search

• Theory of computation

  • Design and analysis of algorithms

    • Data structures design and analysis

      • Pattern matching