Kumar Manjeet and Michael Sushama and Alvarado-Valverde Jesús and Zeke András and Lazar Tamas and Glavina Juliana and Nagy-Kanta Eszter and Donagh Juan Mac and Kálmán Zsófia Etelka and Pascarelli Stefano and Palopoli Nicolas and Dobson László and Suarez Carmen Florencia and Van Roey Kim and Krystkowiak Izabella and Griffin Juan Esteban and Nagpal Anurag and Bhardwaj Rajesh and Diella Francesca and Mészáros Bálint and Dean Kellie and Davey Norman E and Pancsa Rita and Chemes Lucía B and Gibson Toby J:
ELM—the Eukaryotic Linear Motif resource—2024 update.
NUCLEIC ACIDS RESEARCH, 52 (D1).
D442-D455.
ISSN 0305-1048
(2024)
| Item Type: |
Article
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| Creators: |
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| Abstract: |
Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org. |
| Journal or Publication Title: |
NUCLEIC ACIDS RESEARCH |
| Date: |
2024 |
| Volume: |
52 |
| Number: |
D1 |
| Page Range: |
D442-D455 |
| ISSN: |
0305-1048 |
| Institution: |
Pázmány Péter Katolikus Egyetem |
| Kar: |
Információs Technológiai és Bionikai Kar (2013.07.-) |
| Nyelv: |
angol |
| MTMT rekordazonosító: |
34391702 |
| DOI azonosító: |
10.1093/nar/gkad1058 |
| Scopus azonosító: |
85181797305 |
| WoS azonosító: |
001104930200001 |
| Date Deposited: |
2026. Mar. 09. 14:58 |
| Last Modified: |
2026. Mar. 09. 14:58 |
| URI: |
https://publikacio.ppke.hu/id/eprint/3486 |
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