What disease, viral, and pathogenic information does the ELM resource include?

ELM (the Eukaryotic Linear Motif resource at elm.eu.org) organizes disease- and pathogen-related motif data into three dedicated sections under its ELM DB: ELM related diseases, ELM viral instances, and ELM pathogenic abuse. Together these connect short linear motifs (SLiMs) to human disease associations, to motifs found in viral proteins, and to cases where pathogens exploit host motifs. If you are studying how a motif contributes to infection or disease, these are the entry points to check before running a prediction.

The three disease- and pathogen-focused sections

These sit alongside the core ELM DB sections (ELM classes, ELM instances, ELM experiments, ELM GO Terms, ELM PDB structures, ELM binding domains, ELM interactions, ELM pathways, and renamed ELM entries), so you can cross-reference a disease- or virus-linked motif against its structural and functional annotation.

How the viral and pathogenic content is structured

• Viral instances are catalogued as instances, meaning they are concrete occurrences of a motif in a specific viral protein, tied back to the parent ELM class that defines the pattern.
• Pathogenic abuse entries describe motifs that pathogens use to interfere with host processes, rather than motifs that are simply present in a pathogen.
• Related diseases links motif data to disease context, useful when you want to move from a sequence pattern to a possible clinical or functional relevance.

Because these are database sections rather than separate tools, you browse or query them the same way as other ELM DB content, and you can pull them programmatically through the ELM API or in bulk via ELM downloads.

SARS-CoV-2 and COVID-19 content

ELM has featured SARS-CoV-2 work directly. The site highlights:

• COVID-19 SLiM Links, collecting motif-related resources for SARS-CoV-2.
• An article on SLiM signatures in the SARS-CoV-2 entry system, published in Science Signaling.
• Validation experiments for SARS-CoV-2 entry system SLiMs, covering the SPIKE CendR and NRP1 receptor in SARS-CoV-2 cell entry.
• An HSTalks interview (Gibson and Yamauchi) on SARS-CoV-2 entry SLiMs.

This makes ELM useful if you want worked examples of how viral entry motifs are identified and then experimentally validated, not just listed.

Using these sections in practice

1. Start from the ELM DB menu and open ELM related diseases, ELM viral instances, or ELM pathogenic abuse depending on whether your question is about disease association, viral proteins, or host exploitation.
2. Cross-check the parent ELM class for any instance you find, to see the defining pattern, binding domains, and switches.
3. Confirm with experiments using the ELM experiments section, since database entries and validated instances are tracked separately.
4. Scale up if needed with the ELM API or ELM downloads, or use gget elm for large-scale local queries as highlighted in the featured paper.

A practical example: if you are investigating how a viral protein disrupts an immune pathway, you would look for its motif in ELM viral instances, check whether a matching entry appears under ELM pathogenic abuse, and then verify the interaction against ELM interactions and ELM pathways.

What to keep in mind

• These sections describe curated motif–disease and motif–pathogen relationships; they are research annotations, not clinical diagnostic or treatment guidance.
• Viral and pathogenic entries are updated as new classes and instances are released, so check the ELM database updates notes for recent additions and revisions.
• The resource is in English and centers on eukaryotic linear motifs, so non-eukaryotic or non-motif mechanisms fall outside its scope.