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?"
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.
A valid drug target must pass 4 gates in order. Failing an early gate makes later gates irrelevant:
Do not proceed to Phase 3 (Chemical Matter) before completing Phase 1 (Disease Association). Gate 1 failures should prompt a NO-GO or pivot recommendation.
LOOK UP DON'T GUESS: Never assume a target is druggable based on its protein family alone, never assume expression is low in a tissue without checking GTEx or HPA, never assume no competitors without searching ClinicalTrials.gov.
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.
Apply when users ask about:
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).
| 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 |
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)
Resolve target to ALL identifiers before any analysis.
Steps:
MyGene_query_genes - Get initial IDs (Ensembl, UniProt, Entrez)ensembl_lookup_gene - Get versioned Ensembl ID (species="homo_sapiens" REQUIRED)ensembl_get_xrefs - Cross-references (HGNC, etc.)OpenTargets_get_target_id_description_by_name - Verify OT targetChEMBL_search_targets - Get ChEMBL target IDUniProt_get_function_by_accession - Function summary (returns list of strings)UniProt_get_alternative_names_by_accession - Collision detectionOutput: Table of verified identifiers (Gene Symbol, Ensembl, UniProt, Entrez, ChEMBL, HGNC) plus protein function and target class.
Quantify target-disease association from genetic, literature, and pathway evidence.
Key tools:
OpenTargets_get_diseases_phenotypes_by_target_ensembl - Disease associationsOpenTargets_target_disease_evidence - Detailed evidence (needs efoId + ensemblId)OpenTargets_get_evidence_by_datasource - Evidence by data sourcegwas_get_snps_for_gene / gwas_search_studies - GWAS evidencegnomad_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)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 classificationPharos_get_target - TDL: Tclin > Tchem > Tbio > TdarkDGIdb_get_gene_druggability - Druggability categoriesalphafold_get_prediction (param: qualifier) / alphafold_get_summaryProteinsPlus_predict_binding_sites - Pocket detectionOpenTargets_get_chemical_probes_by_target_ensemblID - Chemical probesOpenTargets_get_target_enabling_packages_by_ensemblID - TEPsTCDB_get_transporter - For SLC/ABC transporter targets: TC classification, family, PDB structures (param: uniprot_accession)TCDB_search_by_substrate - Find transporters by substrate (param: substrate_name)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 dataOpenTargets_get_associated_drugs_by_target_ensemblID - Known drugs (size REQUIRED)ChEMBL_search_mechanisms - Drug mechanismsDGIdb_get_gene_info - Drug-gene interactionsAssess clinical validation from approved drugs and clinical trials.
Key tools:
FDA_get_mechanism_of_action_by_drug_name / FDA_get_indications_by_drug_namedrugbank_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_chemblIdIdentify safety risks from expression, genetics, and known adverse events.
Key tools:
OpenTargets_get_target_safety_profile_by_ensemblID - Safety liabilitiesGTEx_get_median_gene_expression - Tissue expression (operation="median" REQUIRED)HPA_search_genes_by_query / HPA_get_comprehensive_gene_details_by_ensembl_idOpenTargets_get_biological_mouse_models_by_ensemblID - KO phenotypesFDA_get_adverse_reactions_by_drug_name / FDA_get_boxed_warning_info_by_drug_nameOpenTargets_get_target_homologues_by_ensemblID - Paralog risksCritical tissues to check: heart, liver, kidney, brain, bone marrow.
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 PPIOpenTargets_get_target_gene_ontology_by_ensemblID - GO termsSTRING_functional_enrichment - Enrichment analysisAssess: pathway redundancy, compensation risk, feedback loops.
Assess existing functional validation data.
Key tools:
DepMap_get_gene_dependencies - Essentiality (score < -0.5 = essential)PubMed_search_articles - Search for CRISPR/siRNA/knockout studiesCTD_get_gene_diseases - Gene-disease associationsLeverage structural biology for druggability and mechanism understanding.
Key tools:
UniProt_get_entry_by_accession - Extract PDB cross-referencesget_protein_metadata_by_pdb_id / pdbe_get_entry_summary / pdbe_get_entry_qualityalphafold_get_prediction / alphafold_get_summary - pLDDT confidenceProteinsPlus_predict_binding_sites - Druggable pocketsInterPro_get_protein_domains / InterPro_get_domain_details - Domain architectureComprehensive collision-aware literature analysis.
Steps:
"{gene_symbol}"[Title] in PubMed; if >20% off-topic, add filters (AND protein OR gene OR receptor)review[pt] filter in PubMedopenalex_search_works for impact dataEuropePMC_search_articlesSynthesize all phases into actionable output:
Create file: [TARGET]_[DISEASE]_validation_report.md
Use the full template from REPORT_TEMPLATE.md. Key sections:
Complete the Completeness Checklist (in REPORT_TEMPLATE.md) before finalizing to verify all phases were covered, all scores justified, and negative results documented.