tooluniverse-drug-target-validation - Claude MCP Skill

# Drug Target Validation Pipeline

Validate drug target hypotheses using multi-dimensional computational evidence before committing to wet-lab work. Produces a quantitative Target Validation Score (0-100) with priority tier classification and GO/NO-GO recommendation.

## Key Principles

1. **Report-first** - Create report file FIRST, then populate progressively
2. **Target disambiguation FIRST** - Resolve all identifiers before analysis
3. **Evidence grading** - Grade all evidence as T1 (experimental) to T4 (computational)
4. **Disease-specific** - Tailor analysis to disease context when provided
5. **Modality-aware** - Consider small molecule vs biologics tractability
6. **Safety-first** - Prominently flag safety concerns early
7. **Quantitative scoring** - Every dimension scored numerically (0-100 composite)
8. **Negative results documented** - "No data" is data; empty sections are failures
9. **Source references** - Every statement must cite tool/database
10. **English-first queries** - Always use English terms in tool calls; respond in user's language

## When to Use

Apply when users ask about:
- "Is [target] a good drug target for [disease]?"
- Target validation, druggability assessment, or target prioritization
- Safety risks of modulating a target
- Chemical starting points for target validation
- GO/NO-GO recommendation for a target

**Not for** (use other skills): general target biology (`tooluniverse-target-research`), drug compound profiling (`tooluniverse-drug-research`), variant interpretation (`tooluniverse-variant-interpretation`), disease research (`tooluniverse-disease-research`).

## Input Parameters

| Parameter | Required | Description | Example |
|-----------|----------|-------------|---------|
| **target** | Yes | Gene symbol, protein name, or UniProt ID | `EGFR`, `P00533` |
| **disease** | No | Disease/indication for context | `Non-small cell lung cancer` |
| **modality** | No | Preferred therapeutic modality | `small molecule`, `antibody`, `PROTAC` |

## Reference Files

- **SCORING_CRITERIA.md** - Detailed scoring matrices, evidence grading, priority tiers, score calculation
- **REPORT_TEMPLATE.md** - Full report template, completeness checklist, section format examples
- **TOOL_REFERENCE.md** - Verified tool parameters, known corrections, fallback chains, modality-specific guidance, phase-by-phase tool lists
- **QUICK_START.md** - Quick start guide

---

## Scoring Overview

**Total: 0-100 points** across 5 dimensions (details in SCORING_CRITERIA.md):

| Dimension | Max | Sub-dimensions |
|-----------|-----|----------------|
| Disease Association | 30 | Genetic (10) + Literature (10) + Pathway (10) |
| Druggability | 25 | Structure (10) + Chemical matter (10) + Target class (5) |
| Safety Profile | 20 | Expression (5) + Genetic validation (10) + ADRs (5) |
| Clinical Precedent | 15 | Based on highest clinical stage achieved |
| Validation Evidence | 10 | Functional studies (5) + Disease models (5) |

**Priority Tiers**: 80-100 = Tier 1 (GO) | 60-79 = Tier 2 (CONDITIONAL GO) | 40-59 = Tier 3 (CAUTION) | 0-39 = Tier 4 (NO-GO)

**Evidence Grades**: T1 (clinical proof) > T2 (functional studies) > T3 (associations) > T4 (predictions)

---

## Pipeline Phases

### Phase 0: Target Disambiguation (ALWAYS FIRST)

Resolve target to ALL identifiers before any analysis.

**Steps**:
1. `MyGene_query_genes` - Get initial IDs (Ensembl, UniProt, Entrez)
2. `ensembl_lookup_gene` - Get versioned Ensembl ID (species="homo_sapiens" REQUIRED)
3. `ensembl_get_xrefs` - Cross-references (HGNC, etc.)
4. `OpenTargets_get_target_id_description_by_name` - Verify OT target
5. `ChEMBL_search_targets` - Get ChEMBL target ID
6. `UniProt_get_function_by_accession` - Function summary (returns list of strings)
7. `UniProt_get_alternative_names_by_accession` - Collision detection

**Output**: Table of verified identifiers (Gene Symbol, Ensembl, UniProt, Entrez, ChEMBL, HGNC) plus protein function and target class.

### Phase 1: Disease Association (0-30 pts)

Quantify target-disease association from genetic, literature, and pathway evidence.

**Key tools**:
- `OpenTargets_get_diseases_phenotypes_by_target_ensembl` - Disease associations
- `OpenTargets_target_disease_evidence` - Detailed evidence (needs `efoId` + `ensemblId`)
- `OpenTargets_get_evidence_by_datasource` - Evidence by data source
- `gwas_get_snps_for_gene` / `gwas_search_studies` - GWAS evidence
- `gnomad_get_gene_constraints` - Genetic constraint (pLI, LOEUF)
- `PubMed_search_articles` - Literature (returns plain list of dicts)
- `OpenTargets_get_publications_by_target_ensemblID` - OT publications (uses `entityId`)

### Phase 2: Druggability (0-25 pts)

Assess whether the target is amenable to therapeutic intervention.

**Key tools**:
- `OpenTargets_get_target_tractability_by_ensemblID` - Tractability (SM, AB, PR, OC)
- `OpenTargets_get_target_classes_by_ensemblID` - Target classification
- `Pharos_get_target` - TDL: Tclin > Tchem > Tbio > Tdark
- `DGIdb_get_gene_druggability` - Druggability categories
- `alphafold_get_prediction` (param: `qualifier`) / `alphafold_get_summary`
- `ProteinsPlus_predict_binding_sites` - Pocket detection
- `OpenTargets_get_chemical_probes_by_target_ensemblID` - Chemical probes
- `OpenTargets_get_target_enabling_packages_by_ensemblID` - TEPs

### Phase 3: Chemical Matter (feeds Phase 2 scoring)

Identify existing chemical starting points for target validation.

**Key tools**:
- `ChEMBL_search_targets` + `ChEMBL_get_target_activities` - Bioactivity data (note: `target_chembl_id__exact` with double underscore)
- `BindingDB_get_ligands_by_uniprot` - Binding data (affinity in nM)
- `PubChem_search_assays_by_target_gene` + `PubChem_get_assay_active_compounds` - HTS data
- `OpenTargets_get_associated_drugs_by_target_ensemblID` - Known drugs (`size` REQUIRED)
- `ChEMBL_search_mechanisms` - Drug mechanisms
- `DGIdb_get_gene_info` - Drug-gene interactions

### Phase 4: Clinical Precedent (0-15 pts)

Assess clinical validation from approved drugs and clinical trials.

**Key tools**:
- `FDA_get_mechanism_of_action_by_drug_name` / `FDA_get_indications_by_drug_name`
- `drugbank_get_targets_by_drug_name_or_drugbank_id` (ALL params required: `query`, `case_sensitive`, `exact_match`, `limit`)
- `search_clinical_trials` (`query_term` REQUIRED)
- `OpenTargets_get_drug_warnings_by_chemblId` / `OpenTargets_get_drug_adverse_events_by_chemblId`

### Phase 5: Safety (0-20 pts)

Identify safety risks from expression, genetics, and known adverse events.

**Key tools**:
- `OpenTargets_get_target_safety_profile_by_ensemblID` - Safety liabilities
- `GTEx_get_median_gene_expression` - Tissue expression (`operation="median"` REQUIRED)
- `HPA_search_genes_by_query` / `HPA_get_comprehensive_gene_details_by_ensembl_id`
- `OpenTargets_get_biological_mouse_models_by_ensemblID` - KO phenotypes
- `FDA_get_adverse_reactions_by_drug_name` / `FDA_get_boxed_warning_info_by_drug_name`
- `OpenTargets_get_target_homologues_by_ensemblID` - Paralog risks

**Critical tissues to check**: heart, liver, kidney, brain, bone marrow.

### Phase 6: Pathway Context

Understand the target's role in biological networks and disease pathways.

**Key tools**:
- `Reactome_map_uniprot_to_pathways` (param: `id`, NOT `uniprot_id`)
- `STRING_get_protein_interactions` (param: `protein_ids` as array, `species=9606`)
- `intact_get_interactions` - Experimental PPI
- `OpenTargets_get_target_gene_ontology_by_ensemblID` - GO terms
- `STRING_functional_enrichment` - Enrichment analysis

**Assess**: pathway redundancy, compensation risk, feedback loops.

### Phase 7: Validation Evidence (0-10 pts)

Assess existing functional validation data.

**Key tools**:
- `DepMap_get_gene_dependencies` - Essentiality (score < -0.5 = essential)
- `PubMed_search_articles` - Search for CRISPR/siRNA/knockout studies
- `CTD_get_gene_diseases` - Gene-disease associations

### Phase 8: Structural Insights

Leverage structural biology for druggability and mechanism understanding.

**Key tools**:
- `UniProt_get_entry_by_accession` - Extract PDB cross-references
- `get_protein_metadata_by_pdb_id` / `pdbe_get_entry_summary` / `pdbe_get_entry_quality`
- `alphafold_get_prediction` / `alphafold_get_summary` - pLDDT confidence
- `ProteinsPlus_predict_binding_sites` - Druggable pockets
- `InterPro_get_protein_domains` / `InterPro_get_domain_details` - Domain architecture

### Phase 9: Literature Deep Dive

Comprehensive collision-aware literature analysis.

**Steps**:
1. **Collision detection**: Search `"{gene_symbol}"[Title]` in PubMed; if >20% off-topic, add filters (AND protein OR gene OR receptor)
2. **Publication metrics**: Total count, 5-year trend, drug-focused subset
3. **Key reviews**: `review[pt]` filter in PubMed
4. **Citation metrics**: `openalex_search_works` for impact data
5. **Broader coverage**: `EuropePMC_search_articles`

### Phase 10: Validation Roadmap (Synthesis)

Synthesize all phases into actionable output:
1. **Target Validation Score** (0-100) with component breakdown
2. **Priority Tier** (1-4) assignment
3. **GO/NO-GO Recommendation** with justification
4. **Recommended Validation Experiments**
5. **Tool Compounds for Testing**
6. **Biomarker Strategy**
7. **Key Risks and Mitigations**

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## Report Output

Create file: `[TARGET]_[DISEASE]_validation_report.md`

Use the full template from **REPORT_TEMPLATE.md**. Key sections:
- Executive Summary (score, tier, recommendation, key findings, critical risks)
- Validation Scorecard (all 12 sub-scores with evidence)
- Sections 1-14 covering each phase
- Completeness Checklist (mandatory before finalizing)

Complete the **Completeness Checklist** (in REPORT_TEMPLATE.md) before finalizing to verify all phases were covered, all scores justified, and negative results documented.