molecular-docking
De la autor
Molecular docking pipeline using AutoDock Vina for structure-based drug discovery. Triggers on docking, AutoDock Vina, receptor preparation, ligand preparation, PDBQT, grid box, virtual screening, binding affinity, pose prediction, structure-based virtual screening, "redocking RMSD", "Vina score", "docking pose", "prepare receptor", "ligand library screening".
Instalare
npx skills add awslabs/hcls-agent-skills --skill molecular-docking -a claude-code
Se instalează în .claude/skills/molecular-docking/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 82
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Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- autodock-vina-dockingjaechang-hits/SciAgent-SkillsMolecular docking with AutoDock Vina (Python API). Receptor/ligand prep (Meeko + RDKit), grid box, docking, pose and binding energy analysis, and batch virtual screening.Inginerie★ 383
- smina-molecular-dockingjaechang-hits/SciAgent-Skillssmina molecular docking CLI. AutoDock Vina fork with customizable scoring functions, native SDF/MOL2/PDB ligand input, autoboxing, local energy minimization, and per-atom score breakdowns. Pipeline: receptor PDBQT prep -> ligand prep (RDKit/OpenBabel) -> dock via autobox or explicit grid -> rescore/minimize with custom scoring -> rank poses by affinity. Choose smina over Vina when you need custom scoring terms (--custom_scoring), local optimization of an existing pose (--local_only), per-atom contributions (--atom_term_data), or SDF/MOL2 ligands without manual PDBQT conversion. For unknown binding sites use diffdock; for the Python-bindings/Vinardo workflow use autodock-vina-docking.Marketing★ 383
- diffdockaipoch/open-sciencePredict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.Știință★ 5.4K
- structure-based-drug-designawslabs/hcls-agent-skillsReasoning skill for structure-based drug design strategy. Use when the user asks to assess target druggability, choose a docking strategy, select a scoring function, define a binding site, interpret docking results, plan molecular dynamics or free energy perturbation (FEP), design a virtual screening cascade, or decide between fragment-based and HTS screening. Triggers include "drug design", "druggability", "docking strategy", "scoring function", "binding pocket", "molecular dynamics", "FEP", "SAR", "virtual screening", "induced fit", "allosteric site", "fragment-based drug discovery", "lead optimization", "MM-GBSA", "pharmacophore".Design★ 66
- alterlab-diffdockAlterLab-IEU/AlterLab-Academic-SkillsPredicts protein-ligand binding poses with DiffDock diffusion-based molecular docking from PDB structures and SMILES, producing pose confidence scores for virtual screening and structure-based drug design. Use when docking ligands into a protein, generating binding poses, or screening compounds against a target; not for binding affinity prediction. Part of the AlterLab Academic Skills suite.Design★ 78
- diffdock-nimNVIDIA/skillsRun DiffDock molecular docking via NVIDIA NIM to predict small-molecule binding poses against protein targets. Use for DiffDock, molecular docking, ligand docking, blind docking, SMILES or SDF ligands, ranked poses, confidence scores, hosted NVIDIA API, or local Docker deployment.DevOps★ 3.7K
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