tooluniverse-drug-target-validation by mims-harvard/tooluniverse
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-drug-target-validation在投入湿实验工作前,使用多维度的计算证据验证药物靶点假设。生成量化的靶点验证分数(0-100),附带优先级分类和 GO/NO-GO 建议。
当用户询问以下问题时应用:
不适用于(请使用其他技能):一般靶点生物学研究 (tooluniverse-target-research)、药物化合物分析 (tooluniverse-drug-research)、变异解释 ()、疾病研究 ()。
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tooluniverse-variant-interpretationtooluniverse-disease-research| 参数 | 必需 | 描述 | 示例 |
|---|---|---|---|
| target | 是 | 基因符号、蛋白质名称或 UniProt ID | EGFR, P00533 |
| disease | 否 | 疾病/适应症背景 | Non-small cell lung cancer |
| modality | 否 | 首选治疗模式 | small molecule, antibody, PROTAC |
总分:0-100 分,涵盖 5 个维度(详情见 SCORING_CRITERIA.md):
| 维度 | 最高分 | 子维度 |
|---|---|---|
| 疾病关联性 | 30 | 遗传学 (10) + 文献 (10) + 通路 (10) |
| 成药性 | 25 | 结构 (10) + 化学物质 (10) + 靶点类别 (5) |
| 安全性特征 | 20 | 表达 (5) + 遗传学验证 (10) + 不良反应 (5) |
| 临床先例 | 15 | 基于达到的最高临床阶段 |
| 验证证据 | 10 | 功能研究 (5) + 疾病模型 (5) |
优先级分类 : 80-100 = 第 1 级 (GO) | 60-79 = 第 2 级 (有条件 GO) | 40-59 = 第 3 级 (谨慎) | 0-39 = 第 4 级 (NO-GO)
证据等级 : T1 (临床证明) > T2 (功能研究) > T3 (关联性) > T4 (预测)
在任何分析之前,将靶点解析为所有标识符。
步骤 :
MyGene_query_genes - 获取初始 ID(Ensembl、UniProt、Entrez)ensembl_lookup_gene - 获取带版本的 Ensembl ID(必需参数:species="homo_sapiens")ensembl_get_xrefs - 交叉引用(HGNC 等)OpenTargets_get_target_id_description_by_name - 验证 OT 靶点ChEMBL_search_targets - 获取 ChEMBL 靶点 IDUniProt_get_function_by_accession - 功能摘要(返回字符串列表)UniProt_get_alternative_names_by_accession - 冲突检测输出 : 已验证标识符表(基因符号、Ensembl、UniProt、Entrez、ChEMBL、HGNC)以及蛋白质功能和靶点类别。
从遗传学、文献和通路证据量化靶点-疾病关联性。
关键工具 :
OpenTargets_get_diseases_phenotypes_by_target_ensembl - 疾病关联OpenTargets_target_disease_evidence - 详细证据(需要 efoId 和 ensemblId)OpenTargets_get_evidence_by_datasource - 按数据源分类的证据gwas_get_snps_for_gene / gwas_search_studies - GWAS 证据gnomad_get_gene_constraints - 遗传约束(pLI, LOEUF)PubMed_search_articles - 文献(返回字典的普通列表)OpenTargets_get_publications_by_target_ensemblID - OT 出版物(使用 entityId)评估靶点是否适合进行治疗干预。
关键工具 :
OpenTargets_get_target_tractability_by_ensemblID - 成药性(SM, AB, PR, OC)OpenTargets_get_target_classes_by_ensemblID - 靶点分类Pharos_get_target - TDL: Tclin > Tchem > Tbio > TdarkDGIdb_get_gene_druggability - 成药性类别alphafold_get_prediction (参数:qualifier) / alphafold_get_summaryProteinsPlus_predict_binding_sites - 结合口袋检测OpenTargets_get_chemical_probes_by_target_ensemblID - 化学探针OpenTargets_get_target_enabling_packages_by_ensemblID - TEPsTCDB_get_transporter - 对于 SLC/ABC 转运蛋白靶点:TC 分类、家族、PDB 结构(参数:uniprot_accession)TCDB_search_by_substrate - 通过底物查找转运蛋白(参数:substrate_name)识别用于靶点验证的现有化学起点。
关键工具 :
ChEMBL_search_targets + ChEMBL_get_target_activities - 生物活性数据(注意:target_chembl_id__exact 带有双下划线)BindingDB_get_ligands_by_uniprot - 结合数据(亲和力,单位 nM)PubChem_search_assays_by_target_gene + PubChem_get_assay_active_compounds - HTS 数据OpenTargets_get_associated_drugs_by_target_ensemblID - 已知药物(必需参数:size)ChEMBL_search_mechanisms - 药物作用机制DGIdb_get_gene_info - 药物-基因相互作用评估来自已批准药物和临床试验的临床验证情况。
关键工具 :
FDA_get_mechanism_of_action_by_drug_name / FDA_get_indications_by_drug_namedrugbank_get_targets_by_drug_name_or_drugbank_id (所有参数必需:query, case_sensitive, exact_match, limit)search_clinical_trials (必需参数:query_term)OpenTargets_get_drug_warnings_by_chemblId / OpenTargets_get_drug_adverse_events_by_chemblId从表达、遗传学和已知不良反应中识别安全风险。
关键工具 :
OpenTargets_get_target_safety_profile_by_ensemblID - 安全风险GTEx_get_median_gene_expression - 组织表达(必需参数:operation="median")HPA_search_genes_by_query / HPA_get_comprehensive_gene_details_by_ensembl_idOpenTargets_get_biological_mouse_models_by_ensemblID - KO 表型FDA_get_adverse_reactions_by_drug_name / FDA_get_boxed_warning_info_by_drug_nameOpenTargets_get_target_homologues_by_ensemblID - 旁系同源物风险需要检查的关键组织 : 心脏、肝脏、肾脏、大脑、骨髓。
理解靶点在生物网络和疾病通路中的作用。
关键工具 :
Reactome_map_uniprot_to_pathways (参数:id,不是 uniprot_id)STRING_get_protein_interactions (参数:protein_ids 作为数组,species=9606)intact_get_interactions - 实验性 PPIOpenTargets_get_target_gene_ontology_by_ensemblID - GO 术语STRING_functional_enrichment - 富集分析评估 : 通路冗余性、补偿风险、反馈回路。
评估现有的功能验证数据。
关键工具 :
DepMap_get_gene_dependencies - 必需性(分数 < -0.5 = 必需)PubMed_search_articles - 搜索 CRISPR/siRNA/敲除研究CTD_get_gene_diseases - 基因-疾病关联利用结构生物学理解成药性和作用机制。
关键工具 :
UniProt_get_entry_by_accession - 提取 PDB 交叉引用get_protein_metadata_by_pdb_id / pdbe_get_entry_summary / pdbe_get_entry_qualityalphafold_get_prediction / alphafold_get_summary - pLDDT 置信度ProteinsPlus_predict_binding_sites - 可成药口袋InterPro_get_protein_domains / InterPro_get_domain_details - 结构域架构全面的冲突感知文献分析。
步骤 :
"{gene_symbol}"[Title];如果 >20% 不相关,则添加过滤器(AND protein OR gene OR receptor)review[pt] 过滤器openalex_search_works 获取影响力数据EuropePMC_search_articles将所有阶段综合为可操作的输出:
创建文件:[TARGET]_[DISEASE]_validation_report.md
使用 REPORT_TEMPLATE.md 中的完整模板。关键部分:
在最终确定前完成 Completeness Checklist(位于 REPORT_TEMPLATE.md 中),以验证所有阶段都已涵盖、所有分数都有理由、阴性结果已记录。
每周安装次数
127
代码库
GitHub 星标数
1.2K
首次出现
2026年2月19日
安全审计
安装于
codex124
gemini-cli123
opencode123
github-copilot122
cursor120
amp119
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.
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, |
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)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 probesIdentify 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 mechanismsAssess 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 / Identify 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.
Weekly Installs
127
Repository
GitHub Stars
1.2K
First Seen
Feb 19, 2026
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Installed on
codex124
gemini-cli123
opencode123
github-copilot122
cursor120
amp119
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PROTACOpenTargets_get_publications_by_target_ensemblID - OT publications (uses entityId)OpenTargets_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)DGIdb_get_gene_infoOpenTargets_get_drug_adverse_events_by_chemblId