Meeko — Python interface for AutoDock molecular docking preparation. Parameterizes small-molecule ligands and macromolecular receptors into PDBQT format for AutoDock-GPU and AutoDock-Vina. Handles fle
Use with AI
Install the MCP server or CLI to instantly fetch Meeko documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/meeko
AutoDock Vina — fast open-source molecular docking engine for predicting protein-ligand binding poses and affinities. Uses gradient-optimization conformational search with Vina, Vinardo, or AutoDock4
1 shared topic • 2 shared operations
DiffDock — diffusion generative model for molecular docking that predicts protein-ligand binding poses. Uses a diffusion process over translations, rotations, and torsion angles to generate and rank d
1 shared topic • 2 shared operations
Gnina — deep learning molecular docking program built on AutoDock Vina. Uses convolutional neural networks (CNNs) to rescore protein-ligand poses for improved binding pose prediction and virtual scree
1 shared topic • 2 shared operations
MDAnalysis — Python library for analyzing molecular dynamics trajectories and atomic coordinate data. Supports 40+ file formats (DCD, XTC, TRR, PDB, GRO, AMBER, LAMMPS). Provides RMSD, RMSF, hydrogen
3 shared operations
MDTraj — Python library for reading, writing, and analyzing molecular dynamics trajectories. Supports 20+ formats (DCD, XTC, TRR, PDB, HDF5, NetCDF, etc.) with NumPy-native arrays. Provides RMSD, RMSF
3 shared operations