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k-dense-ai/drug-discovery-agent-skills

v1.3.0MIT

Agent Skills for small-molecule and protein therapeutics: target validation and human genetics, bioactivity and chemical space, generative design and retrosynthesis, docking, free energy and dynamics, ADMET and PK translation, protein, antibody, degrader and oligonucleotide design, and the clinical and regulatory record.

autodock-vina

Structure-based docking with AutoDock Vina, Vinardo, and AutoDock4 through the Meeko toolchain. Use this skill to define a docking box, prepare receptors and ligands as PDBQT, run single or batch docking, rescore, and interpret affinities, poses, and ligand efficiency. Covers box definition from a reference ligand or pocket residues, protonation and tautomer decisions, flexible side chains, exhaustiveness and seeds, redocking validation, and virtual screening over compound libraries. Also trigger on vina, smina, gnina, mk_prepare_ligand, mk_prepare_receptor, mk_export, scrub.py, PDBQT, autogrid4, docking box, or binding-pose prediction.

Version
1.0
License
MIT
Compatibility
The bundled scripts need only Python 3.10+ and the standard library. Running a docking calculation additionally needs the AutoDock Vina binary (conda install -c conda-forge vina, or pip install vina 1.2.7) and Meeko 0.7+ (pip install meeko) on PATH; SMILES input also needs molscrub. CPU only; no GPU or API key required.
Read SKILL.md at the source

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Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

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