Eukaryotic Linear Motif (ELM) Resource for Protein Analysis
In the complex world of protein interactions, small sequences often play a disproportionately large role in determining cellular function. The Eukaryotic Linear Motif (ELM) resource, developed at the European Molecular Biology Laboratory (EMBL), serves as a critical computational biology tool designed specifically for the investigation of short linear motifs (SLiMs) within eukaryotic proteins.
SLiMs are short, conserved sequences of amino acids that mediate protein-protein interactions and post-translational modifications. Because they are brief, they allow for flexible and dynamic signaling within the cell. The ELM database stands as the largest collection of linear motif classes, providing a comprehensive library of annotated and experimentally validated motif instances.
Key Facts
- Developer: European Molecular Biology Laboratory (EMBL).
- Primary Purpose: Investigating and predicting short linear motifs (SLiMs) in eukaryotic proteins.
- Methodology: Uses regular expression rules to define motif patterns.
- Scope: As of 2010, the resource contained 146 different motifs and over 1,300 experimentally determined instances.
- Access: Available via the website elm.eu.org.
How the ELM Prediction Pipeline Works
The ELM resource employs a sophisticated prediction pipeline to identify putative motif instances within protein sequences. At its core, linear motifs are specified as patterns using regular expression rules—a sequence of characters that defines a search pattern for the computer to match against the protein's amino acid sequence.
To ensure high accuracy and scientific reliability, the developers are continuously refining the system. This includes the implementation of context-based rules and logical filters, which are specifically designed to reduce the number of false positive matches, ensuring that the identified motifs are biologically relevant.
[ไม่มีภาพประกอบ]Advanced Filtering and Data Integration
The ELM server provides researchers with powerful tools to narrow down their search and validate their findings. Users can filter motif data based on several critical biological parameters:
- Cell Compartment: Identifying where the protein resides within the cell.
- Phylogeny: Filtering by evolutionary relationships and species.
- Structure: Analyzing the physical arrangement of the protein.
- Globular Domain Clash: Utilizing the SMART and Pfam databases to ensure a motif is not buried within a folded globular domain, which would make it inaccessible for interaction.
Beyond known instances, the system also identifies and displays positionally conserved matches in sequences that are similar to existing ELM instance sequences, aiding in the discovery of new functional motifs.
| Feature | Details |
|---|---|
| Primary Citation | Dinkel & al. (2012) |
| Release Date | 2011 |
| Motif Count (2010) | 146 different motifs |
| Validated Instances (2010) | 1,300+ instances |
| External Database Integration | SMART / Pfam |
Frequently Asked Questions
What are SLiMs?
SLiMs, or short linear motifs, are brief sequences of amino acids in proteins that are essential for mediating interactions and signaling within eukaryotic cells.
Who developed the ELM resource?
The resource was developed by researchers at the European Molecular Biology Laboratory (EMBL), with key contributions from Holger Dinkel and Toby Gibson.
How does ELM reduce false positive results?
ELM reduces false positives by applying context-based rules and logical filters to the initial regular expression matches.
What is a globular domain clash?
A globular domain clash occurs when a predicted linear motif is located inside a folded part of the protein (a globular domain), which would prevent it from interacting with other molecules. ELM uses SMART and Pfam databases to detect these clashes.
Where can I access the ELM database?
The resource is accessible online at elm.eu.org.