conformer-generation
bygptomics· 59 skills
Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.
How to install conformer-generation?
gptomics/bioskills/conformer-generation
$npx -y skills add gptomics/bioskills --skill conformer-generationInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/gptomics/bioskills" --skill "gptomics/bioskills/conformer-generation"` 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/gptomics/bioskills" that are relevant to the current task. Run `npx skills add "https://github.com/gptomics/bioskills"` and select the relevant skills, then follow their instructions.
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