tooluniverse-gwas-drug-discovery

安装量: 111
排名: #7683

安装

npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-gwas-drug-discovery
GWAS-to-Drug Target Discovery
Transform genome-wide association studies (GWAS) into actionable drug targets and repurposing opportunities.
IMPORTANT
Always use English terms in tool calls. Respond in the user's language.
Overview
This skill bridges genetic discoveries from GWAS with drug development by:
Identifying genetic risk factors
- Finding genes associated with diseases
Assessing druggability
- Evaluating which genes can be targeted by drugs
Prioritizing targets
- Ranking candidates by genetic evidence strength
Finding existing drugs
- Discovering approved/investigational compounds
Identifying repurposing opportunities
- Matching drugs to new indications
Key insight
Targets with genetic support have 2x higher probability of clinical approval (Nelson et al., Nature Genetics 2015).
Workflow Steps
Step 1: GWAS Gene Discovery
Input
Disease/trait name (e.g., "type 2 diabetes", "Alzheimer disease")
Process
Query GWAS Catalog for associations, filter by significance (p < 5x10^-8), map variants to genes, aggregate evidence.
Tools
:
gwas_get_associations_for_trait
- Get associations by disease
gwas_search_associations
- Flexible search
gwas_get_associations_for_snp
- SNP-specific associations
OpenTargets_search_gwas_studies_by_disease
- Curated GWAS data
OpenTargets_get_variant_credible_sets
- Fine-mapped loci with L2G predictions
Step 2: Druggability Assessment
Input
Gene list from Step 1
Process
Check target class, assess tractability, evaluate safety, check for tool compounds or structures.
Tools
:
OpenTargets_get_target_tractability_by_ensemblID
- Druggability assessment
OpenTargets_get_target_classes_by_ensemblID
- Target classification
OpenTargets_get_target_safety_profile_by_ensemblID
- Safety data
OpenTargets_get_target_genomic_location_by_ensemblID
- Genomic context
Step 3: Target Prioritization
Scoring Formula
:
Target Score = (GWAS Score x 0.4) + (Druggability x 0.3) + (Clinical Evidence x 0.2) + (Novelty x 0.1)
Rank targets by composite score. Generate target dossiers.
Step 4: Existing Drug Search
Process
Search drug-target associations, find approved drugs and clinical candidates, get MOA and indication data. Tools : OpenTargets_get_associated_drugs_by_disease_efoId - Known drugs for disease OpenTargets_get_drug_mechanisms_of_action_by_chemblId - Drug MOA ChEMBL_get_target_activities - Bioactivity data ChEMBL_get_drug_mechanisms / ChEMBL_search_drugs - Drug data Step 5: Clinical Evidence & Safety Tools : FDA_get_adverse_reactions_by_drug_name - Safety data FDA_get_active_ingredient_info_by_drug_name - Drug composition OpenTargets_get_drug_warnings_by_chemblId - Drug warnings Step 6: Repurposing Opportunities Match drug targets to new disease genes, assess mechanistic fit, check contraindications, estimate repurposing probability. Quick Start from tooluniverse import ToolUniverse tu = ToolUniverse ( use_cache = True ) tu . load_tools ( )

Step 1: Get GWAS associations

associations

tu . tools . gwas_get_associations_for_trait ( trait = "type 2 diabetes" )

Step 2: Assess druggability

tractability

tu . tools . OpenTargets_get_target_tractability_by_ensemblID ( ensemblID = "ENSG00000148737" )

Step 3: Find existing drugs

drugs

tu
.
tools
.
OpenTargets_get_associated_drugs_by_disease_efoId
(
efoId
=
"EFO_0001360"
)
All Tools by Category
GWAS & Genetics
:
gwas_get_associations_for_trait
/
gwas_search_associations
/
gwas_get_associations_for_snp
OpenTargets_search_gwas_studies_by_disease
/
OpenTargets_get_variant_credible_sets
Target Assessment
:
OpenTargets_get_target_tractability_by_ensemblID
/
OpenTargets_get_target_classes_by_ensemblID
OpenTargets_get_target_safety_profile_by_ensemblID
/
OpenTargets_get_target_genomic_location_by_ensemblID
Drug Discovery
:
OpenTargets_get_associated_drugs_by_disease_efoId
/
OpenTargets_get_drug_mechanisms_of_action_by_chemblId
ChEMBL_get_target_activities
/
ChEMBL_get_drug_mechanisms
/
ChEMBL_search_drugs
Safety & Clinical
:
FDA_get_adverse_reactions_by_drug_name
/
FDA_get_active_ingredient_info_by_drug_name
OpenTargets_get_drug_warnings_by_chemblId
Literature
:
PubMed_search_articles
/
EuropePMC_search_articles
/
ClinicalTrials_search
Best Practices
Multi-ancestry GWAS
Include trans-ethnic meta-analyses for robust signals
Functional validation
Confirm with eQTL, pQTL, colocalization analysis
Network analysis
Group GWAS hits by pathway (KEGG, Reactome)
Safety assessment
Check gnomAD pLI, GTEx expression, PharmaGKB
Batch operations
Use tu.run_batch() for parallel queries across targets Troubleshooting Problem Solution No GWAS hits for disease Try broader trait name, check synonyms, use OpenTargets Gene not in druggable class Consider antibody/antisense modalities, check pathway neighbors No existing drugs for target Target may be novel - check tool compounds in ChEMBL Low L2G score Variants may be regulatory - check eQTL/pQTL evidence Reference Files REFERENCE.md - Detailed concepts, druggability tiers, clinical translation, limitations, ethics EXAMPLES.md - Use cases (Huntington's, Alzheimer's, diabetes) with success stories REPORT_TEMPLATE.md - Output report template with scoring criteria PROCEDURES.md - Step-by-step implementation procedures QUICK_START.md - Quick start guide
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