zinc-database
Search ZINC Chemical Compounds
Drug discovery teams need fast access to purchasable compounds and docking-ready structures. This skill guides Claude, Codex, and Claude Code through ZINC searches, API queries, and structure download workflows.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "zinc-database" from https://skillstore.io/skills/k-dense-ai-zinc-database.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-zinc-database/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "zinc-database". Find details for a ZINC ID.
Expected outcome:
The response explains the ZINC ID endpoint, recommends requesting SMILES and catalog fields, and describes how to interpret the returned table.
Using "zinc-database". Find analogs for a SMILES structure.
Expected outcome:
The response suggests exact and similarity searches, explains distance parameters, and lists fields useful for ranking purchasable analogs.
Using "zinc-database". Prepare a docking library from a tranche.
Expected outcome:
The response identifies ZINC22 file repository paths, explains available structure formats, and recommends starting with a small tranche sample.
Security Audit
SafeThe static findings are false positives from scientific documentation for public ZINC and CartBlanche22 data access. The subprocess examples use curl to reach documented endpoints, Markdown backticks were misread as execution, and .db2 files are DOCK compound library files rather than sensitive SQLite databases. No prompt injection, exfiltration intent, or malicious control behavior was found.
Risk Factors
⚙️ External commands (50)
🌐 Network access (50)
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<a href="https://skillstore.io/skills/k-dense-ai-zinc-database?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-zinc-database/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/k-dense-ai-zinc-database.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). zinc-database security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-zinc-database/audits/8BibTeX citation
@techreport{k-dense-ai-k-dense-ai-zinc-database-2026,
author = {K-Dense-AI},
title = {zinc-database security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/k-dense-ai-zinc-database/audits/8},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "zinc-database security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/k-dense-ai-zinc-database/audits/8"
identifiers:
- type: other
value: "skillstore:k-dense-ai-zinc-database:audit:8"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-zinc-database
2026-08-21
k-dense-ai-zinc-database
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Find purchasable analogs
Search near a known SMILES structure and collect related compounds with supplier information.
Prepare docking libraries
Identify tranche files and structure formats needed for molecular docking experiments.
Build screening datasets
Retrieve random or filtered ZINC compound sets for benchmarking and virtual screening pipelines.
Try These Prompts
Use the ZINC database skill to show me how to look up ZINC000000000001 and return its SMILES and supplier catalogs.
Use the ZINC database skill to plan a similarity search for this SMILES: c1ccccc1. Include useful output fields and distance settings.
Use the ZINC database skill to design a workflow for collecting 1,000 lead-like purchasable compounds with ZINC IDs, SMILES, tranches, and catalogs.
Use the ZINC database skill to explain how to locate docking-ready 3D structure files for a chosen tranche and prepare them for a DOCK6 workflow.
Best Practices
- Start with exact ZINC ID or SMILES searches before broad similarity or random sampling.
- Request only fields needed for the analysis to reduce response size and processing time.
- Use small test downloads before retrieving large tranche files for docking workflows.
Avoid
- Do not make rapid repeated API calls without delays or retry backoff.
- Do not assume supplier availability is current without checking returned catalog data.
- Do not download full tranche directories before confirming the target format and storage requirements.
Frequently Asked Questions
What is ZINC used for?
Can this skill search by SMILES?
Does this skill provide 3D structures?
Does it require an API key?
Can I use it for supplier checks?
What should I watch for when downloading files?
Developer Details
Author
K-Dense-AILicense
Unknown
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/zinc-databaseRef
1ffa7643651792ccb4bd3b15d924d2c97edff755
Maintenance freshness
7/18/2026
Usage
7 downloads · 202 views
File structure