mims-harvard/tooluniverse-protein-modification-analysis
plugin/skills/tooluniverse-protein-modification-analysis/SKILL.md
Post-translational modification (PTM) analysis — phosphorylation, ubiquitination, acetylation, glycosylation, methylation. Uses iPTMnet (sites + enzymes), ProtVar (functional consequences), UniProt (baseline), STRING, ELM (linear motifs), MassIVE/ProteomeXchange (experimental). Use for PTM site annotation, kinase-substrate identification, and PTM-disease associations.
$ install --global
skillsauthnpx skillsauth add mims-harvard/tooluniverse tooluniverse-protein-modification-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: May 26, 2026, 7:14 AM18.5s1 file scanned
SKILL.md
- name:
- tooluniverse-protein-modification-analysis
- description:
- Post-translational modification (PTM) analysis — phosphorylation, ubiquitination, acetylation, glycosylation, methylation. Uses iPTMnet (sites + enzymes), ProtVar (functional consequences), UniProt (baseline), STRING, ELM (linear motifs), MassIVE/ProteomeXchange (experimental). Use for PTM site annotation, kinase-substrate identification, and PTM-disease associations.
- disable-model-invocation:
- true
Protein Post-Translational Modification Analysis
Comprehensive PTM analysis using iPTMnet (primary), ProtVar (functional context), UniProt (baseline), STRING (interactions), ELM (linear motifs), and MassIVE/ProteomeXchange (experimental data).
LOOK UP DON'T GUESS
- PTM sites/enzymes:
iPTMnet_get_ptm_sites - Functional consequence:
ProtVar_get_function+iPTMnet_get_ptm_ppi - Proteoforms:
iPTMnet_get_proteoforms - Linear motifs:
ELM_get_instances
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
Domain Reasoning
PTMs are context-dependent: same phosphorylation site can activate or inhibit depending on kinase and effectors. Always check: which enzyme, what functional consequence, in what cell context.
KEY PRINCIPLES
- Disambiguation first -- resolve to UniProt accession before iPTMnet calls
- iPTMnet is SOAP-style -- every call requires
operationparameter - Evidence-graded -- distinguish experimental (T1) from predicted (T4)
- English-first queries
Workflow
Phase 0: Protein Disambiguation → UniProt accession
Phase 1: PTM Site Inventory → iPTMnet_get_ptm_sites
Phase 2: Proteoform Analysis → iPTMnet_get_proteoforms
Phase 3: PTM-Dependent Interactions → iPTMnet_get_ptm_ppi
Phase 4: Functional Context → ProtVar_get_function at key sites
Phase 4b: Linear Motif Context → ELM_get_instances for SLiM overlap
Phase 4c: Experimental Data → MassIVE/ProteomeXchange
Phase 5: Synthesis & Report
Phase 0: Disambiguation
iPTMnet_search(operation="search", search_term="TP53", role="Substrate")-- find UniProt IDs- If user provides UniProt accession directly, use it
- Select human entry if multiple hits
Phase 1: PTM Sites
iPTMnet_get_ptm_sites(operation="get_ptm_sites", uniprot_id="P04637") -- returns position, residue, modification type, enzyme, evidence. Group by modification type. Fallback: UniProt_get_entry_by_accession PTM annotations.
Phase 2: Proteoforms
iPTMnet_get_proteoforms(operation="get_proteoforms", uniprot_id=...) -- distinct PTM combinations. Focus on those with functional/disease annotations if >20.
Phase 3: PTM-Dependent Interactions
iPTMnet_get_ptm_ppi(operation="get_ptm_ppi", uniprot_id=...) -- interacting protein, PTM site, effect (enables/disrupts). Supplement with STRING_get_interaction_partners(identifiers=gene, species=9606, required_score=700).
Phase 4: Functional Context
ProtVar_get_function(accession=..., position=N, variant_aa=AA) -- domain, active site, binding site, conservation. Grade: active-site PTM > domain-core > disordered region.
Phase 4b: Linear Motifs (ELM)
ELM_get_instances(operation="get_instances", uniprot_id=..., motif_type="MOD") -- MOD = modification sites, DEG = degradation signals. Cross-reference with Phase 1 PTM positions. ELM_list_classes(operation="list_classes") for motif details.
Phase 4c: Experimental Data
MassIVE_search_datasets(species="9606"), MassIVE_get_dataset(accession="MSV...") for public MS datasets.
Evidence Grading
| Tier | Criteria | |------|----------| | T1 | PTM at validated active/binding site with functional data | | T2 | PTM in structured domain with ProtVar annotation | | T3 | Correlation data only (mass spec detection) | | T4 | Predicted, no experimental validation |
Tool Parameter Reference
| Tool | Key Params |
|------|-----------|
| iPTMnet_search | operation="search", search_term, role |
| iPTMnet_get_ptm_sites | operation="get_ptm_sites", uniprot_id |
| iPTMnet_get_proteoforms | operation="get_proteoforms", uniprot_id |
| iPTMnet_get_ptm_ppi | operation="get_ptm_ppi", uniprot_id |
| ELM_get_instances | operation="get_instances", uniprot_id, motif_type |
| ELM_list_classes | operation="list_classes" |
| MassIVE_search_datasets | page_size, species |
Critical: All iPTMnet and ELM tools require operation as first parameter (SOAP-style).
Fallbacks
| Situation | Fallback | |-----------|----------| | Not in iPTMnet | UniProt PTM/processing annotations | | No PTM-PPI data | STRING general PPI | | No ProtVar data | UniProt domain annotations | | No ELM data | Proceed with iPTMnet/UniProt only |
Limitations
- iPTMnet biased toward well-studied proteins
- Proteoform data covers observed combinations only
- PTM-PPI: only PTM-specific evidence; more PPIs exist in STRING
Related Skills
mims-harvard/tooluniverse-product-safety-surveillance
tools
VerifiedTrustedCommunity
Post-market safety surveillance and recall/adverse-event RETRIEVAL across the full spectrum of FDA-regulated products that are NOT covered by the drug-AE signal skills: medical devices, food / dietary supplements / cosmetics, veterinary drugs, and drug supply (shortages). Orchestrates openFDA endpoints (MAUDE device adverse events + device recalls + 510(k), CAERS food/supplement/ cosmetic adverse events, veterinary adverse events, drug shortages, and cross-product enforcement/recall reports). USE WHEN the user asks: "are there adverse events for [device / pacemaker / infusion pump / insulin pump]", "device recalls for [firm/product]", "supplement / vitamin / cosmetic adverse reactions", "is [drug] in shortage", "what injectables are on shortage", "veterinary / animal adverse events for [drug] in [dog/cat/horse]", "food recall for listeria", "MAUDE report for [device]", "CAERS reactions for [brand]". DO NOT USE for drug adverse-event SIGNAL detection or disproportionality (PRR / ROR / IC) or drug-AE association scoring — that is `tooluniverse-pharmacovigilance` / `tooluniverse-adverse-event-detection`. This skill is multi-product surveillance and retrieval, not drug-AE statistical signal mining.
1,446SKILL.mdUpdated Jun 13, 2026
mims-harvard/skills/tooluniverse-phewas
tools
VerifiedTrustedCommunity
--- name: tooluniverse-phewas description: Cross-ancestry / cross-biobank phenome-wide association (PheWAS) and replication. Given ONE variant (rsID) or ONE gene, look up every phenotype it associates with across European/UK (UKB-TOPMed), Finnish (FinnGen), Japanese (BioBank Japan), and Taiwanese (TPMI) biobanks, plus exome-wide gene-burden PheWAS (Genebass), then judge whether an association replicates across ancestries or is population-specific. Use whenever the user asks "what else is this va
1,446SKILL.mdUpdated Jun 13, 2026
mims-harvard/tooluniverse-natural-product-dereplication
tools
VerifiedTrustedCommunity
Dereplicate a putative natural product and assign its chemical taxonomy. Use to answer "is [compound] a known natural product", "what microbe/organism produces [compound]", "what chemical class is [compound]", "dereplicate this metabolite (by formula/exact mass/InChIKey/SMILES)", or "classify this molecule into ChemOnt". Searches NPAtlas for known microbial natural products (producing organism + literature reference), assigns the ChemOnt kingdom→superclass→class→subclass hierarchy via ClassyFire, resolves systematic IUPAC names to structure via OPSIN, and cross-references identity in PubChem. NOT for general drug/compound identity or ADMET (use tooluniverse-chemical-compound-retrieval / tooluniverse-small-molecule-discovery) and NOT for metabolomics pathway/enrichment analysis (use tooluniverse-metabolomics skills).
1,446SKILL.mdUpdated Jun 13, 2026
mims-harvard/tooluniverse-microbial-genome-characterization
tools
VerifiedTrustedCommunity
Genome-ASSEMBLY discovery, QC, and replicon mapping for any organism (bacteria, archaea, fungi, and beyond) using NCBI Datasets. Resolves an organism name or taxid to assemblies, picks the reference/representative or best-quality assembly, pulls assembly QC metrics (total length, contig/scaffold N50, contig count, GC%, assembly level, RefSeq category), enumerates chromosomes and plasmids via per-replicon sequence reports, and compares candidate assemblies on quality. Use for "what genomes are available for [organism]", "assembly stats / N50 / GC content for [GCF_/GCA_ accession]", "how many plasmids does [strain] have", "compare assemblies for [species]", "find the reference genome for [taxon]", "is this assembly Complete Genome or just contigs". NOT for gene-level orthology/synteny (use tooluniverse-comparative-genomics), plant gene structure (use tooluniverse-plant-genomics), de novo assembly from raw reads (no tool exists), or taxonomy-only name/lineage lookups.
1,446SKILL.mdUpdated Jun 13, 2026