Search and retrieve chemical compound data from the ZINC database via the CartBlanche22 API.
npx skills add https://github.com/yf8578/clawomics --skill zinc-database-yf8578
Please help me install this Agent Skill. Skill: zinc-database Source: https://github.com/yf8578/clawomics/tree/main/skills/zinc-database Command: npx skills add https://github.com/yf8578/clawomics --skill zinc-database-yf8578
This Skill provides programmatic access to the ZINC database, enabling users to search for and retrieve information on over 230 million purchasable chemical compounds, facilitating drug discovery and virtual screening efforts.
Use the zinc-database skill to find 100 lead-like compounds.
High-intent search queries and answers about installing and using this skill.
You can search the ZINC database by providing a SMILES string to find purchasable compounds and retrieve their ZINC IDs and supplier information. This enables you to identify commercially available analogs of a target molecule for drug discovery.
Yes, you can retrieve 3D-ready molecular structures from ZINC for virtual screening. The Skill provides access to 3D conformers suitable for docking studies, helping you evaluate molecular interactions during drug discovery.
You can obtain a random sample of drug-like compounds from the chemical database by using property filters. The Skill supports random sampling with filters like 'lead-like' or 'drug-like' to retrieve customized compound sets for screening.
The best way to find structurally similar compounds is to perform a similarity search using a query molecule. This Skill queries the ZINC database to find and retrieve compounds structurally similar to your input, facilitating analog identification.
Yes, ZINC database searching supports both supplier codes and ZINC IDs. You can use these specific identifiers to directly query and retrieve detailed information on over 230 million purchasable chemical compounds.
Accessing 230 million compounds requires utilizing the CartBlanche22 API for ZINC22 data. Users should be aware that complex similarity searches and large random sampling queries may be constrained by API rate limits and data retrieval processing times.
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