helmkit 0.6.0

Parse HELM strings into RDKit molecules

helmkit

A Python library for converting HELM (Hierarchical Editing Language for Macromolecules) notation to RDKit molecules.

Table of Contents

• Basic Usage
• Installation
• Quick Example
• Understanding HELM Notation
• Using Custom Monomer Data
• SDF File Structure Requirements
• Parallel Processing of Peptides
• Development Setup
• Running Tests

Basic Usage

from helmkit import Molecule

# Create a molecule from a HELM string
helm_string = "PEPTIDE1{A.R.G}$$$$"
molecule = Molecule(helm_string)

# Access the RDKit molecule object
rdkit_mol = molecule.mol

Installation

To install helmkit, you can use either uv or pip.

With uv

uv pip install helmkit

or if you have added it as a dependency to your pyproject.toml:

uv add helmkit

Without uv

pip install helmkit

Quick Example

from helmkit import Molecule
from rdkit.Chem import AllChem, Draw

# Create a simple tripeptide (Ala-Arg-Gly)
molecule = Molecule("PEPTIDE1{A.R.G}$$$$")

# Generate 2D coordinates for visualization
AllChem.Compute2DCoords(molecule.mol)

# Save the image
img = Draw.MolToImage(molecule.mol)
img.save("tripeptide.png")

Understanding HELM Notation

HELM (Hierarchical Editing Language for Macromolecules) is a notation for representing complex biomolecules. A basic HELM string has the following format:

PEPTIDE1{A.R.G}|PEPTIDE2{S.G.C}$PEPTIDE1,PEPTIDE2,1:R1-3:R3$$$V2.0

Where:

• PEPTIDE1{A.R.G} defines the first chain (a peptide with amino acids A, R, G)
• PEPTIDE2{S.G.C} defines the second chain
• PEPTIDE1,PEPTIDE2,1:R1-3:R3 defines a connection between the chains (R1 of residue 1 in PEPTIDE1 connects to R3 of residue 3 in PEPTIDE2)
• $ characters separate different sections of the HELM string

Using Custom Monomer Data

By default, helmkit uses the monomer data in helmkit/data/monomers.sdf. To use a custom SDF file:

from helmkit import Molecule, load_monomer_library

# Load your custom monomer data
custom_sdf_path = "/path/to/your/custom_monomers.sdf"
custom_monomers = load_monomer_library(custom_sdf_path)

# Create molecule with custom monomer data
molecule = Molecule("PEPTIDE1{A.R.G}$$$$", monomer_df=custom_monomers)

SDF File Structure Requirements

The SDF file containing monomer data must have the following properties for each molecule:

Required Properties:

• symbol: A unique identifier for the monomer (e.g., "A" for alanine)
• m_RgroupIdx: Comma-separated list of R-group atom indices (e.g., "1,2,None,None")

Optional Properties:

• m_Rgroups: Comma-separated list of R-group types (e.g., "H,OH,None,None")
• m_type: Monomer type (e.g., "aa" for amino acid)
• m_subtype: Monomer subtype
• m_abbr: Monomer abbreviation

Example SDF Entry:

Your molecule atom data here...
...

> <symbol>
A

> <m_Rgroups>
H,OH,None,None

> <m_RgroupIdx>
1,2,None,None

> <m_type>
aa

> <m_subtype>
natural

> <m_abbr>
Ala

$$$$

Parallel Processing of Peptides

For workflows involving a large number of peptides, helmkit provides a function to process them in parallel, significantly improving performance.

from helmkit import load_monomer_library
from helmkit import load_in_parallel

# Load your custom monomer data (optional)
custom_sdf_path = "/path/to/your/custom_monomers.sdf"
monomer_db = load_monomer_library(custom_sdf_path)

# A list of HELM strings
helm_strings = ["PEPTIDE1{A.R.G}$$$$", "PEPTIDE1{S.G.T}$$$$"]

# Process peptides in parallel
molecules = load_in_parallel(helm_strings, monomer_db)

Development Setup

To set up a development environment, first clone the repository. Then, from the root of the repository, use uv to sync the environment:

uv sync -U

Running Tests

To run the test suite, execute pytest from the root of the repository:

pytest