crimm 2026.2.1

Chemistry with the ReInvented Macromolecular Mechanics

crimm

crimm stands for Chemistry with the ReInvented Macromolecular Mechanics.

This is a Python toolkit for biomolecule structure preparation, designed to unify common modeling routines under one scriptable platform. While many tools exist for tasks like solvation, adding hydrogens, or building missing loops, they often lack the scriptability needed for high-throughput pipelines. crimm aims to fill this gap by providing intuitive Python APIs that integrate seamlessly with pyCHARMM, RDKit, and other computational chemistry tools.

Why crimm?

• Scriptable: All preparation steps are Python functions—no clicking through web interfaces or writing shell scripts
• Integrated: Works natively with pyCHARMM for energy calculations and simulations
• Accurate: Uses mmCIF format to correctly identify chain types, detect missing loops, and handle biological assemblies
• Extensible: Adaptors connect crimm to RDKit, PropKa, OpenMM, and more

Features

• Fetch structures from RCSB PDB or AlphaFold Database
• Organize mmCIF structures into protein, nucleic acid, ligand, solvent, and ion components
• Generate CHARMM36m topology for proteins, canonical DNA/RNA, and protein-containing systems
• Normalize common terminal caps and report unsupported modified chemistry explicitly
• Parameterize small-molecule ligands with CGenFF integration, including lone-pair-aware workflows
• Read, write, and reload native CHARMM PSF and CRD files
• Solvate in cubic or truncated octahedral water boxes
• Add monovalent ions at target concentrations (SPLIT, SLTCAP methods)
• Build missing loops from homology models
• Visualize structures in Jupyter notebooks with NGLView

Installation

pip install crimm

Optional cheminformatics and protonation extras:

pip install "crimm[all]"

Requires Python >= 3.9. For a complete development environment:

conda env create -f env.yaml

Note: pyCHARMM, OpenMM, and the external CGenFF executable must be installed separately when those workflows are needed.

Quick Example

from crimm.Fetchers import fetch_rcsb
from crimm.Modeller import TopologyGenerator
from crimm.Modeller.Solvator import Solvator
from crimm.IO import write_psf, write_crd

# Fetch and prepare structure
model = fetch_rcsb('1LSA', organize=True)
topo_gen = TopologyGenerator()
for chain in model.protein:
    topo_gen.generate(chain)

# Solvate and add 150 mM KCl
solvator = Solvator(model)
solvator.solvate(cutoff=10.0, box_type='octa')
solvator.add_ions(concentration=0.15, cation='POT', anion='CLA')

# Write CHARMM files
write_psf(model, 'system.psf')
write_crd(model, 'system.crd')

Modules

Module	Purpose
Fetchers	Download structures from RCSB PDB or AlphaFold
Modeller	Topology generation, PSF/CRD loading, solvation, loop building
IO	Read/write PDB, mmCIF, PSF, and CRD files
Adaptors	Connect to pyCHARMM, RDKit, PropKa

Documentation

See tutorials/ for Jupyter notebooks on structure preparation, topology generation, PSF/CRD workflows, loop building, and more.

License

GPLv3

Links

• Repository: https://github.com/BrooksResearchGroup-UM/crimm
• Issues: https://github.com/BrooksResearchGroup-UM/crimm/issues