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alterlab-drugbank

Retrieve DrugBank drug information, interactions, targets, and pathways via Python.

58|9|Updated Mar 16, 2026
Search Tags:#bioinformatics#pathways#targets#pharmacology#drugbank#drug-interactions#xml-parse
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-drugbank
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alterlab-drugbank
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/databases/alterlab-drugbank
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-drugbank

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Enables programmatic access to DrugBank data for automated retrieval of drug information, interactions, targets and pathways to support research workflows.

Core Features & Use Cases

  • Data Access & Queries: Retrieve drug details, calculated/experimental properties, and external references from DrugBank.
  • Interactions & Targets: Analyze DDIs, extract targets, enzymes, transporters, and pathway mappings for pharmacology studies.
  • Reproducible Workflows: Build data pipelines, export to CSV/DataFrames, and document versions for reproducibility.
  • Real-World Use Case: A researcher looks up aspirin's indications, interactions, and target proteins to assess repurposing opportunities.

Quick Start

Run a quick lookup by DB ID using DrugBankHelper to fetch basic information and targets in one call.

Frequently Asked Questions about alterlab-drugbank

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

FAQPage Schema
How do I programmatically access DrugBank data for drug interactions and targets?▼

Programmatic DrugBank data access is enabled through scripted Python queries that parse XML files to retrieve drug information, interactions, targets, and pathways. You use the DrugBankHelper to fetch details and export results as dictionaries or CSV extracts.

What is the best way to parse DrugBank XML for pharmacology research and drug repurposing?▼

Parsing DrugBank XML for pharmacology research involves Python scripts with proper namespace handling to extract calculated properties, experimental properties, and external references. The Skill structures this data into reproducible formats like DataFrames and CSV files for drug repurposing analysis.

Can I analyze drug-drug interactions and map pathways across many drugs using DrugBank data?▼

Yes, analyzing drug-drug interactions and mapping pathways across many drugs is supported by extracting targets, enzymes, and transporters from DrugBank data. Scripted queries process the XML to build DDI analysis pipelines for pharmacology studies and safety analysis.

Do I need the DrugBank downloader and Python to retrieve drug information from XML files?▼

Yes, retrieving drug information requires the DrugBank downloader to acquire the XML data and Python for XML parsing. Proper namespace handling is necessary during extraction to accurately produce dictionaries and CSV extracts for reproducible research workflows.

How do I export DrugBank query results to CSV for reproducible data pipelines?▼

Exporting DrugBank query results to CSV involves running scripted queries to extract drug details and interactions, then converting the resulting dictionaries into DataFrames. This produces reproducible CSV extracts that document versions for pharmacology research and teaching workflows.

Why does my DrugBank XML parsing fail to extract targets and pathways correctly?▼

DrugBank XML parsing fails to extract targets and pathways correctly when proper namespace handling is omitted from the Python scripts. Accurate retrieval of drug information, interactions, and external references requires specifying the correct XML namespaces during the data extraction process.

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