learningmatter-mit/AtomisticSkills

Intergrating Atomistic Skills into Agentic IDEs (Cursor, Claude Code, Google Antigravity, OpenClaw, etc)

158Stars on the repository
134Mods indexed here, across every type
todayLast push, which is what freshness is scored on
MITLicence, which decides whether bodies are shown

chem-vibration

25

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Calculate vibrational frequencies, normal modes, zero-point energy, and IR spectra of molecules and clusters using MLIPs.

not rated 158 today A 27 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Define a docking search box (center coordinates + box dimensions in Angstroms) from a co-crystal ligand, binding-site residues, or a saved JSON specification. Use this skill whenever the user mentions binding site, docking box, search box, grid box, active site definition, or pocket definition, or needs to specify…

not rated 158 today A 101 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Build a solvated, charge-neutralized protein-ligand complex for OpenMM molecular dynamics simulation. Combines a prepared receptor PDB and ligand SDF, parameterizes the ligand with OpenFF Sage or GAFF (AM1-BCC charges), applies Amber ff14SB to the protein, solvates with explicit water, and adds counterions. Use this…

not rated 158 today A 118 tokens original MIT

drug-db-chembl

30

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Query ChEMBL web services for targets, molecules, and curated bioactivity measurements (IC50, Ki, EC50, etc.).

not rated 158 today A 33 tokens original MIT

drug-db-pdb

31

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Search, filter, and retrieve macromolecular structures from the RCSB Protein Data Bank (PDB), including metadata, bound ligands, and optional coordinate/validation downloads.

not rated 158 today A 41 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Post-docking analysis of virtual screening results including score distributions, enrichment metrics (ROC AUC, enrichment factors), and ligand efficiency calculations.

not rated 158 today A 32 tokens original MIT

drug-docking-vina

34

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Dock small-molecule ligands into a protein receptor using AutoDock Vina (Python API) and save ranked poses + docking metadata for reproducible virtual screening.

not rated 158 today A 38 tokens original MIT

drug-ligand-prep

35

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Prepare small-molecule ligands for docking and analysis via optional state enumeration, 3D conformer generation, MMFF/UFF minimization, and export to SDF + AutoDock PDBQT.

not rated 158 today A 48 tokens original MIT

drug-mmpbsa-gbsa

36

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Compute single-trajectory MM-GBSA and / or MM-PBSA binding free energy estimates from a protein-ligand MD trajectory. Two backends: a fast OpenMM GBn2 path (no extra dependencies) and an AmberTools MMPBSA.py path that supports both GB (multiple igb models) and Poisson-Boltzmann PB on the same trajectory.

not rated 158 today A 86 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

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…

not rated 158 today A 111 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Validate docked or generated ligand poses for physical plausibility using PoseBusters, filtering out chemically invalid or clashing poses before downstream refinement.

not rated 158 today A 33 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Run a protein-ligand MD simulation in OpenMM with energy minimization, restrained equilibration, and production NPT, producing trajectory and checkpoint files for downstream analysis.

not rated 158 today A 42 tokens original MIT

drug-protein-prep

41

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Prepare macromolecular receptor structures (PDB/mmCIF or RCSB PDB ID) for docking or simulation by fixing common structure issues and adding hydrogens.

not rated 158 today A 41 tokens original MIT

drug-redocking-rmsd

42

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Compute symmetry-corrected heavy-atom RMSD between docked poses and a reference crystal ligand to validate docking protocols.

not rated 158 today A 31 tokens original MIT

learningmatter-mit/AtomisticSkills

Skill Claude CodeCodex

Analyze a protein-ligand MD trajectory to compute ligand RMSD, pocket RMSF, hydrogen bonds, contact occupancy, and protein-ligand interaction fingerprints over time.

not rated 158 today A 39 tokens original MIT

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