Identify and rank ligandable pockets on a protein structure or model using geometry (fpocket) or an ML predictor (P2Rank). Returns ranked pockets with lining residues, geometric center, volume, and a druggability score per pocket. Excludes docking; pair with drug-binding-site-definition or drug-docking-vina downstream. Use whenever the user has a protein but no binding-site information, asks about cryptic / allosteric / orphan pockets, needs to assess druggability, or wants to choose where to dock.
How to install drug-pocket-detection?
learningmatter-mit/atomisticskills/drug-pocket-detection
$npx -y skills add learningmatter-mit/atomisticskills --skill drug-pocket-detectionInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/learningmatter-mit/atomisticskills" --skill "learningmatter-mit/atomisticskills/drug-pocket-detection"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/learningmatter-mit/atomisticskills" that are relevant to the current task. Run `npx skills add "https://github.com/learningmatter-mit/atomisticskills"` and select the relevant skills, then follow their instructions.
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