The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Attributes of short linear motifs
Abstract
Traditionally, protein–protein interactions were thought to be mediated by large, structured domains. However, it has become clear that the interactome comprises a wide range of binding interfaces with varying degrees of flexibility, ranging from rigid globular domains to disordered regions that natively lack structure. Enrichment for disorder in highly connected hub proteins and its correlation with organism complexity hint at the functional importance of disordered regions. Nevertheless, they have not yet been extensively characterised. Shifting the attention from globular domains to disordered regions of the proteome might bring us closer to elucidating the dense and complex connectivity of the interactome. An important class of disordered interfaces are the compact mono-partite, short linear motifs (SLiMs, or eukaryotic linear motifs (ELMs)). They are evolutionarily plastic and interact with relatively low affinity due to the limited number of residues that make direct contact with the binding partner. These features confer to SLiMs the ability to evolve convergently and mediate transient interactions, which is imperative to network evolution and to maintain robust cellsignalling, respectively. The ability to discriminate biologically relevant SLiMs by means of different attributes will improve our understanding of the complexity of the interactome and aid development of bioinformatics tools for motif discovery. In this paper, the curated instances currently available in the Eukaryotic Linear Motif (ELM) database are analysed to provide a clear overview of the defining attributes of SLiMs. These analyses suggest that functional SLiMs have higher levels of conservation than their surrounding residues, frequently evolve convergently, preferentially occur in disordered regions and often form a secondary structure when bound to their interaction partner. These results advocate searching for small groupings of residues in disordered regions with higher relative conservation and a propensity to form the secondary structure. Finally, the most interesting conclusions are examined in regard to their functional consequences.
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Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
Intrinsically unstructured proteins and their functions
Dyson, H. J., & Wright, P. E. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1589 · Cited by 3,871
The Pfam protein families database
Finn, R. D., Mistry, J., Tate, J., Coggill, P., Heger, A., Pollington, J. E., Gavin, O. L., Gunasekaran, P., Ceric, G., Forslund, K., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp985 · Cited by 2,694
Structure of the MDM2 Oncoprotein Bound to the p53 Tumor Suppressor Transactivation Domain
Kussie, P. H., Gorina, S., Marechal, V., Elenbaas, B., Moreau, J., Levine, A. J., & Pavletich, N. P. (1996) · Science · doi:10.1126/science.274.5289.948 · Cited by 2,206
Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks
Neduva, V., Linding, R., Su-Angrand, I., Stark, A., Masi, F. D., Gibson, T. J., Lewis, J., Serrano, L., & Russell, R. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030405 · Cited by 359
Self-citationLinear motifs: Evolutionary interaction switches
Neduva, V., & Russell, R. B. (2005) · FEBS Letters · doi:10.1016/j.febslet.2005.04.005 · Cited by 352
Disorder and Sequence Repeats in Hub Proteins and Their Implications for Network Evolution
Dosztányi, Z., Chen, J., Dunker, A. K., Simon, I., & Tompa, P. (2006) · Journal of Proteome Research · doi:10.1021/pr060171o · Cited by 341
Cited by
A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains
Irimia, M., Weatheritt, R. J., Ellis, J. D., Parikshak, N. N., Gonatopoulos-Pournatzis, T., Babor, M., Quesnel-Vallières, M., Tapial, J., Raj, B., O’Hanlon, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.035 · Cited by 693
“4), in line with the average length of linear motifs (Davey et al., 2012).”
BackgroundSelf-citationBuljan, M., Chalancon, G., Eustermann, S., Wagner, G. P., Fuxreiter, M., Bateman, A., & Babu, M. M. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.05.039 · Cited by 396
Proteome-wide analysis of chaperone-mediated autophagy targeting motifs
Kirchner, P., Bourdenx, M., Madrigal-Matute, J., Tiano, S., Diaz, A., Bartholdy, B. A., Will, B., & Cuervo, A. M. (2019) · PLOS Biology · doi:10.1371/journal.pbio.3000301 · Cited by 257
Interactions by disorder – A matter of context
Bugge, K., Brakti, I., Fernandes, C. B., Dreier, J. E., Lundsgaard, J. E., Olsen, J. G., Skriver, K., & Kragelund, B. B. (2020) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2020.00110 · Cited by 155
“Short linear motifs (SLiMs) are more prevalent in IDPs, and the human proteome is estimated to contain > 100.000 – possibly a million – SLiM instances (Davey et al., 2012; Tompa et al., 2014).”
BackgroundInfluentialIvarsson, Y., Arnold, R., McLaughlin, M., Nim, S., Joshi, R., Ray, D., Liu, B., Teyra, J., Pawson, T., Moffat, J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312296111 · Cited by 135
Describing sequence–ensemble relationships for intrinsically disordered proteins
Mao, A. H., Lyle, N., & Pappu, R. V. (2013) · Biochemical Journal · doi:10.1042/bj20121346 · Cited by 135
Elongation factor Tu is a multifunctional and processed moonlighting protein
Widjaja, M., Harvey, K. L., Hagemann, L., Berry, I. J., Jarocki, V. M., Raymond, B. B. A., Tacchi, J. L., Gründel, A., Steele, J. R., Padula, M. P., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-10644-z · Cited by 131
Goldman, A., Roy, J., Bodenmiller, B., Wanka, S., Landry, C. R., Aebersold, R., & Cyert, M. S. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.05.012 · Cited by 109
Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation
Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Djokic, M., Strom, J. M., Schönfeld, J., Geist, J. L., et al. (2024) · Molecular Systems Biology · doi:10.1038/s44320-023-00005-6 · Cited by 105
“Motifs are short stretches of amino acids in disordered regions of proteins that usually adopt a more rigid structure upon binding to folded domains in interaction partners (Davey et al , 2012).”
BackgroundSelf-citationSystematic discovery of protein interaction interfaces using AlphaFold and experimental validation
Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Đokić, M., Strom, J. M., Schönfeld, J., Geist, J. L., et al. (2023) · doi:10.1101/2023.08.07.552219 · Cited by 105
Self-citationBraun, J. E., Huntzinger, E., & Izaurralde, E. (2012) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a012328 · Cited by 61
Next Generation Protein Structure Predictions and Genetic Variant Interpretation
Diwan, G. D., Gonzalez-Sanchez, J. C., Apic, G., & Russell, R. B. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167180 · Cited by 30
Jankowski, M. S., Griffith, D., Shastry, D. G., Pelham, J. F., Ginell, G. M., Thomas, J., Karande, P., Holehouse, A. S., & Hurley, J. M. (2024) · Nature Communications · doi:10.1038/s41467-024-47761-z · Cited by 23
Intrinsic protein disorder and protein modifications in the processing of biological signals
Phillips, A. H., & Kriwacki, R. W. (2020) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2019.09.003 · Cited by 21
Protein intrinsically disordered regions have a non-random, modular architecture
McConnell, B. S., & Parker, M. W. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad732 · Cited by 17
Soft disorder modulates the assembly path of protein complexes
Seoane, B., & Carbone, A. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010713 · Cited by 15
The pathogen-encoded signalling receptor Tir exploits host-like intrinsic disorder for infection
Vieira, M. F. M., Hernandez, G., Zhong, Q., Arbesú, M., Veloso, T., Gomes, T., Martins, M. L., Monteiro, H., Frazão, C., Frankel, G., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-05856-9 · Cited by 14
Reys, V., & Labesse, G. (2022) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00964 · Cited by 9
Halpin, J. C., Whitney, D., Rigoldi, F., Sivaraman, V., Singer, A., & Keating, A. E. (2022) · Protein Science · doi:10.1002/pro.4429 · Cited by 7
Singer, A., Ramos, A., & Keating, A. E. (2024) · Protein Science · doi:10.1002/pro.5094 · Cited by 6
Metadata
- Authors
- Davey, N. E., Van Roey, K., Weatheritt, R. J., Toedt, G., Uyar, B., Altenberg, B., Budd, A., Diella, F., Dinkel, H., & Gibson, T. J.
- Venue
- Molecular BioSystems
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-09-12
- Volume
- 8
- Issue
- 1
- Pages
- 268-281
- ISSN
- 1742-2051 (ISSN-L)
- 1742-206X
- OpenAlex
- W2023333666
- Cited by
- 628
- References
- 8
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- closed
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