tooluniverse-drug-target-validation

name

tooluniverse-drug-target-validation

description

Comprehensive computational validation of drug targets for early-stage drug discovery. Evaluates targets across 10 dimensions (disambiguation, disease association, druggability, chemical matter, clinical precedent, safety, pathway context, validation evidence, structural insights, validation roadmap) using 60+ ToolUniverse tools. Produces a quantitative Target Validation Score (0-100) with GO/NO-GO recommendation. Use when users ask about target validation, druggability assessment, target prioritization, or "is X a good drug target for Y?"

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

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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)

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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.