zinc-database

Locates purchasable small-molecule candidates from ZINC via ID, SMILES, or supplier code searches.

21|2|Updated Dec 8, 2025
One-click install
npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill zinc-database-silverstein
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: zinc-database
Source: https://github.com/silverstein/claude-scientific-skills-desktop/tree/main/corpus/zinc-database
Command: npx skills add https://github.com/silverstein/claude-scientific-skills-desktop --skill zinc-database-silverstein

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

ZINC selection is hard because researchers need fast ways to locate purchasable compounds by identifier, structure, or similarity and obtain the right data for downstream virtual screening.

Core Features & Use Cases

  • Find compounds by ZINC ID or SMILES: Look up specific molecules or search by chemical structure for screening libraries.
  • Run similarity and analog discovery: Use distance thresholds for Tanimoto-style similarity to expand hit lists into purchasable analogs.
  • Retrieve docking-ready 3D structures: Download structures organized by tranches suitable for virtual screening and docking workflows.
  • Support chemical space sampling: Generate random compound sets (e.g., fragment/lead-like/drug-like) for benchmarking and library building.

Quick Start

Use the skill to search ZINC22 by SMILES for similarity matches and return ZINC IDs plus SMILES for virtual screening.

Frequently Asked Questions about zinc-database

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

FAQPage Schema
How do I search ZINC by SMILES to find purchasable compounds for virtual screening?

Search ZINC by SMILES to locate purchasable small-molecule candidates using similarity and analog discovery. The skill queries ZINC22 via CartBlanche22 endpoints, applying distance thresholds to return matching ZINC IDs and SMILES for screening libraries.

Can I retrieve docking-ready 3D structures from ZINC22 for molecular docking workflows?

Retrieve docking-ready 3D structures from ZINC22 by searching for compounds and downloading structures organized by tranches. These tranche metadata entries support property-driven filtering for virtual screening and docking library preparation.

What is the best way to find purchasable analogs from a known ZINC ID for hit expansion?

Find purchasable analogs from a known ZINC ID by running a similarity search with Tanimoto-style distance thresholds. The skill uses CartBlanche22 endpoints to expand hit lists into purchasable analogs and returns selectable output fields for screening.

Does the ZINC database skill support random chemical space sampling for benchmarking?

Random chemical space sampling is supported to generate random compound sets for benchmarking and library building. You can sample fragment, lead-like, and drug-like subsets from ZINC22 to prepare diverse screening libraries.

How do I filter ZINC compound search results by physicochemical properties?

Filter ZINC compound search results by physicochemical properties using tranche metadata and subset filtering parameters. The skill applies parameterized search logic via CartBlanche22 endpoints to return compounds matching specific property-driven criteria.

Why use ZINC22 for virtual screening instead of searching other chemoinformatics databases?

ZINC22 provides direct access to purchasable small-molecule candidates with docking-ready 3D structures organized by tranches. It supports SMILES queries, ZINC ID lookups, and supplier code searches with similarity thresholds for targeted analog discovery.