/checking-chembl
Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill checking-chembl --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/checking-chembl
Context preview
The summary Claude sees to decide when to auto-load this skill.
Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data
SKILL.md
checking-chembl.SKILL.mdname: Checking ChEMBL for Structured SAR Data
description: Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data
when_to_use: After finding relevant medicinal chemistry paper. When paper describes SAR data, compound series, or activity measurements. When evaluating papers with IC50, MIC, Ki, or other bioactivity values. Before attempting to parse activity tables from PDFs.
version: 1.0.0
<!-- ╔══════════════════════════════════════════════════════════════╗ ║ 本文件为开源 Skill 原始文档,收录仅供学习与研究参考 ║ ║ CoPaper.AI 收集整理 | https://copaper.ai ║ ╚══════════════════════════════════════════════════════════════╝
来源仓库: https://github.com/kthorn/research-superpower 项目名称: research-superpower 开源协议: MIT License 收录日期: 2026-04-02
声明: 本文件版权归原作者所有。此处收录旨在为社会科学实证研究者 提供 AI Agent Skills 的集中参考。如有侵权,请联系删除。 -->
Checking ChEMBL for Structured SAR Data
Overview
ChEMBL is a manually curated database of ~99,000 medicinal chemistry papers with extracted, standardized bioactivity data. If a paper is in ChEMBL, you can access structured data without parsing PDFs.
**Core principle:** Check ChEMBL first for medicinal chemistry papers. Curated data is more reliable than table parsing.
When to Use
Use this skill when:
- Paper describes medicinal chemistry / drug discovery
- Abstract mentions compound series, SAR, or activity data
- Paper has IC50, MIC, Ki, EC50, or other bioactivity measurements
- Before attempting to extract data from tables/figures
- Paper scored ≥ 7 in relevance evaluation
**When NOT to use:**
- Non-medicinal chemistry papers (cell biology, genomics, etc.)
- Papers without activity measurements
- Reviews without primary data
- Very recent papers (< 6 months, likely not curated yet)
ChEMBL API Basics
**Base URL:** `https://www.ebi.ac.uk/chembl/api/data/`
**No authentication required**
**CRITICAL: ChEMBL can ONLY be queried by DOI, NOT by PMID**
- The API returns PMID in results, but does not accept it as a query parameter
- Always use DOI for lookups: `?doi=10.1234/example`
- PMID queries will return 0 results even if paper exists in ChEMBL
**Two-step process:** 1. Check if paper (by DOI) is in ChEMBL 2. If yes, retrieve bioactivity data
Step 1: Check if Paper in ChEMBL
**Query by DOI (ONLY method that works):**
curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=DOI"
**⚠️ IMPORTANT: Must use DOI, not PMID**
# ✅ CORRECT - Use DOI
doi="10.1021/jm401507s"
curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=$doi"
# ❌ WRONG - PMID won't work (will return 0 results)
pmid="24446688"
curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?pubmed_id=$pmid" # Does NOT work!
**If you only have PMID:** Fetch DOI from PubMed first, then query ChEMBL with the DOI.
**Response structure:**
{
"documents": [
{
"document_chembl_id": "CHEMBL3120156",
"doi": "10.1021/jm401507s",
"title": "Discovery and development of simeprevir (TMC435), a HCV NS3/4A protease inhibitor.",
"abstract": "Hepatitis C virus is a blood-borne infection...",
"pubmed_id": 24446688,
"journal": "J Med Chem",
"year": 2014,
"doc_type": "PUBLICATION"
}
],
"page_meta": {
"total_count": 1
}
}**Key fields:**
- `document_chembl_id` - Use this to retrieve activity data
- `doc_type` - "PUBLICATION" (from literature) or "DATASET" (deposited)
- `pubmed_id` - PMID is in the response, but cannot be used to query ChEMBL
- If `total_count` = 0, paper not in ChEMBL
**Parse response:**
response=$(curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=$doi")
if [ $(echo "$response" | jq -r '.page_meta.total_count') -gt 0 ]; then
chembl_id=$(echo "$response" | jq -r '.documents[0].document_chembl_id')
echo "✓ Found in ChEMBL: $chembl_id"
else
echo "✗ Not in ChEMBL"
fi
Step 2: Get Activity Data Count
**Query activity endpoint:**
curl -s "https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=CHEMBL3120156&limit=1"
**Extract total count:**
activity_url="https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=$chembl_id&limit=1"
activity_count=$(curl -s "$activity_url" | jq -r '.page_meta.total_count')
echo "→ $activity_count bioactivity data points"
Step 3: Report to User and Update Summary
**Report immediately:**
📄 [15/127] Screening: "Discovery and development of simeprevir"
Abstract score: 9 → Fetching full text...
✓ ChEMBL: CHEMBL3120156 (101 activity data points)
→ IC50 data for HCV NS3 protease inhibitors available
**Add to SUMMARY.md:**
### [Discovery and development of simeprevir (TMC435), a HCV NS3/4A protease inhibitor](https://doi.org/10.1021/jm401507s) (Score: 9)
**DOI:** [10.1021/jm401507s](https://doi.org/10.1021/jm401507s)
**PMID:** [24446688](https://pubmed.ncbi.nlm.nih.gov/24446688/)
**ChEMBL:** [CHEMBL3120156](https://www.ebi.ac.uk/chembl/document_report_card/CHEMBL3120156/) (101 data points)
**Key Findings:**
- IC50 data for HCV NS3/4A protease inhibitors (from ChEMBL)
- Lead compound simeprevir (TMC435) approved for HCV treatment
- Structures and full activity data: [ChEMBL API](https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=CHEMBL3120156)
**ChEMBL Activity Summary:**
- IC50 values for HCV NS3/4A protease
- PK parameters (AUC, Cmax, clearance)
- DMPK assays (metabolic stability, permeability)
**Always include ChEMBL status:**
- If found: Add ChEMBL ID with link and data point count
- If not found: Note "Not in ChEMBL" (still valuable information)
Step 4: Update Tracking Files
**Add to papers-reviewed.json:**
{
"10.1021/jm401507s": {
"pmid": "24446688",
"status": "relevant",
"score": 9,
"chembl_id": "CHEMBL3120156",
"chembl_activities": 101,
"has_structured_data": true
}
}Optional: Extract Struc
Read more
name: Checking ChEMBL for Structured SAR Data description: Check if medicinal chemistry papers are in ChEMBL database to access curated bioactivity data when_to_use: After finding relevant medicinal chemistry paper. When paper describes SAR data, compound series, or activity measurements. When evaluating papers with IC50, MIC, Ki, or other bioactivity values. Before attempting to parse activity tables from PDFs. version: 1.0.0
<!-- ╔══════════════════════════════════════════════════════════════╗ ║ 本文件为开源 Skill 原始文档,收录仅供学习与研究参考 ║ ║ CoPaper.AI 收集整理 | https://copaper.ai ║ ╚══════════════════════════════════════════════════════════════╝
来源仓库: https://github.com/kthorn/research-superpower 项目名称: research-superpower 开源协议: MIT License 收录日期: 2026-04-02
声明: 本文件版权归原作者所有。此处收录旨在为社会科学实证研究者 提供 AI Agent Skills 的集中参考。如有侵权,请联系删除。 -->
Checking ChEMBL for Structured SAR Data
Overview
ChEMBL is a manually curated database of ~99,000 medicinal chemistry papers with extracted, standardized bioactivity data. If a paper is in ChEMBL, you can access structured data without parsing PDFs.
**Core principle:** Check ChEMBL first for medicinal chemistry papers. Curated data is more reliable than table parsing.
When to Use
Use this skill when:
- Paper describes medicinal chemistry / drug discovery
- Abstract mentions compound series, SAR, or activity data
- Paper has IC50, MIC, Ki, EC50, or other bioactivity measurements
- Before attempting to extract data from tables/figures
- Paper scored ≥ 7 in relevance evaluation
**When NOT to use:**
- Non-medicinal chemistry papers (cell biology, genomics, etc.)
- Papers without activity measurements
- Reviews without primary data
- Very recent papers (< 6 months, likely not curated yet)
ChEMBL API Basics
**Base URL:** `https://www.ebi.ac.uk/chembl/api/data/`
**No authentication required**
**CRITICAL: ChEMBL can ONLY be queried by DOI, NOT by PMID**
- The API returns PMID in results, but does not accept it as a query parameter
- Always use DOI for lookups: `?doi=10.1234/example`
- PMID queries will return 0 results even if paper exists in ChEMBL
**Two-step process:** 1. Check if paper (by DOI) is in ChEMBL 2. If yes, retrieve bioactivity data
Step 1: Check if Paper in ChEMBL
**Query by DOI (ONLY method that works):**
curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=DOI"
**⚠️ IMPORTANT: Must use DOI, not PMID**
# ✅ CORRECT - Use DOI doi="10.1021/jm401507s" curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=$doi" # ❌ WRONG - PMID won't work (will return 0 results) pmid="24446688" curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?pubmed_id=$pmid" # Does NOT work!
**If you only have PMID:** Fetch DOI from PubMed first, then query ChEMBL with the DOI.
**Response structure:**
{
"documents": [
{
"document_chembl_id": "CHEMBL3120156",
"doi": "10.1021/jm401507s",
"title": "Discovery and development of simeprevir (TMC435), a HCV NS3/4A protease inhibitor.",
"abstract": "Hepatitis C virus is a blood-borne infection...",
"pubmed_id": 24446688,
"journal": "J Med Chem",
"year": 2014,
"doc_type": "PUBLICATION"
}
],
"page_meta": {
"total_count": 1
}
}**Key fields:**
- `document_chembl_id` - Use this to retrieve activity data
- `doc_type` - "PUBLICATION" (from literature) or "DATASET" (deposited)
- `pubmed_id` - PMID is in the response, but cannot be used to query ChEMBL
- If `total_count` = 0, paper not in ChEMBL
**Parse response:**
response=$(curl -s "https://www.ebi.ac.uk/chembl/api/data/document.json?doi=$doi") if [ $(echo "$response" | jq -r '.page_meta.total_count') -gt 0 ]; then chembl_id=$(echo "$response" | jq -r '.documents[0].document_chembl_id') echo "✓ Found in ChEMBL: $chembl_id" else echo "✗ Not in ChEMBL" fi
Step 2: Get Activity Data Count
**Query activity endpoint:**
curl -s "https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=CHEMBL3120156&limit=1"
**Extract total count:**
activity_url="https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=$chembl_id&limit=1" activity_count=$(curl -s "$activity_url" | jq -r '.page_meta.total_count') echo "→ $activity_count bioactivity data points"
Step 3: Report to User and Update Summary
**Report immediately:**
📄 [15/127] Screening: "Discovery and development of simeprevir" Abstract score: 9 → Fetching full text... ✓ ChEMBL: CHEMBL3120156 (101 activity data points) → IC50 data for HCV NS3 protease inhibitors available
**Add to SUMMARY.md:**
### [Discovery and development of simeprevir (TMC435), a HCV NS3/4A protease inhibitor](https://doi.org/10.1021/jm401507s) (Score: 9) **DOI:** [10.1021/jm401507s](https://doi.org/10.1021/jm401507s) **PMID:** [24446688](https://pubmed.ncbi.nlm.nih.gov/24446688/) **ChEMBL:** [CHEMBL3120156](https://www.ebi.ac.uk/chembl/document_report_card/CHEMBL3120156/) (101 data points) **Key Findings:** - IC50 data for HCV NS3/4A protease inhibitors (from ChEMBL) - Lead compound simeprevir (TMC435) approved for HCV treatment - Structures and full activity data: [ChEMBL API](https://www.ebi.ac.uk/chembl/api/data/activity.json?document_chembl_id=CHEMBL3120156) **ChEMBL Activity Summary:** - IC50 values for HCV NS3/4A protease - PK parameters (AUC, Cmax, clearance) - DMPK assays (metabolic stability, permeability)
**Always include ChEMBL status:**
- If found: Add ChEMBL ID with link and data point count
- If not found: Note "Not in ChEMBL" (still valuable information)
Step 4: Update Tracking Files
**Add to papers-reviewed.json:**
{
"10.1021/jm401507s": {
"pmid": "24446688",
"status": "relevant",
"score": 9,
"chembl_id": "CHEMBL3120156",
"chembl_activities": 101,
"has_structured_data": true
}
}Optional: Extract Struc
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Other skills on auto-empirical-research-skills.
- /pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill - /00-Full-empirical-analysis-skill_StatsPAI
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 /
Open skill - /00.1-Full-empirical-analysis-skill_Python
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /00.2-Full-empirical-analysis-skill_Stata
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill

