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LeonChaoX
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drugbank-database

Extract structured drug records, chemical properties, targets, pathways, and drug-drug interactions from DrugBank XML.

783|65|Updated Feb 27, 2026
Search Tags:#drug discovery#drugbank#drug targets#drug-drug interactions#chemical similarity#xml data
One-click install
npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill drugbank-database-leonchaox
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drugbank-database
Source: https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/drugbank-database
Command: npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill drugbank-database-leonchaox

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires drugbank-downloader, bioversions, lxml, pandas, rdkit, networkx, scikit-learn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

It eliminates the manual effort of collecting consistent drug information, chemical properties, targets, and drug-drug interactions by pulling structured DrugBank data programmatically for analysis and decision support.

Core Features & Use Cases

  • Drug data access & parsing: Download and parse DrugBank XML securely using authenticated access and cached local datasets, supporting reproducible version pinning.
  • Comprehensive drug queries: Retrieve drug identifiers, descriptions/indications, chemical structures (e.g., SMILES/InChI), pharmacology, and external cross-references in a queryable form.
  • Targets, pathways, and interactions: Extract targets (including actions and UniProt-linked polypeptides), map drugs to pathways, and analyze drug-drug interactions for polypharmacy safety or combination assessment.
  • Chemical similarity & property screening: Compute physicochemical descriptors, apply drug-likeness rules (Lipinski/Veber), generate fingerprints, and run structure-similarity workflows using RDKit.

Quick Start

Use the drugbank-database skill to look up DB00001 and return its drug information, targets, interactions, and key chemical properties from DrugBank.

Frequently Asked Questions about drugbank-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve drug-drug interactions and targets from DrugBank XML for pharmacology profiling?▼

Yes, you can compute chemical similarity and apply drug-likeness rules using RDKit within the DrugBank data workflow. It generates molecular fingerprints, calculates physicochemical descriptors, and runs structure-similarity screening against retrieved SMILES or InChI chemical structures.

Do I need authenticated access to download specific DrugBank versions for reproducible research?▼

Yes, you need authenticated access to download specific DrugBank versions for reproducible research. The workflow uses drugbank-downloader for secure access and supports optional local dataset caching to ensure version-pinned consistency during downstream analysis.

What is the best way to parse DrugBank XML namespaces when extracting cross-references and chemical structures?▼

The best way to parse DrugBank XML namespaces when extracting cross-references and chemical structures is using lxml. This approach securely traverses the XML tree to query drug identifiers, descriptions, SMILES, InChI, pharmacology data, and external cross-references in a structured format.

Can I analyze polypharmacy interactions and map drugs to pathways using pandas and networkx?▼

You can analyze polypharmacy interactions and map drugs to pathways by feeding parsed DrugBank records into pandas and networkx. This combination enables structured interaction checks for combination assessment and network-based pathway mapping for comprehensive pharmacological analysis.

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