pkasso 0.5.0

Prediction of protonation states for small molecules

pKasso

pKasso determines protonation states for small molecules based on the pKa predictor MolGpKa (https://github.com/Xundrug/MolGpKa).

One protonation microstate describes a unique charge pattern on the protonable sites of molecules. pKasso enumerates protonation microstates, screens pKa values between connected microstates, and predicts pH-dependent microstate frequencies based on the graph of free energy differences between microstates.

The easiest way to run pKasso is via the webserver: [ADD LINK TO WEBSERVER]

Installation

# Create conda environment
conda create -n pkasso python=3.12
conda activate pkasso

# Install pkasso from PyPI
pip install pkasso

Command line interface

The command line interface is called via pkasso.

1. pkasso single: Calculate single pH-dependent microstate probabilities given a SMILES string
2. pkasso batch: Batch process a .smi file to calculate pH-dependent microstates
3. pkasso scan: Scan a pH range and plot the microstate distributions for all pH values (for a single molecule); calculate macro-pKa values.

pkasso --smiles 'OC(=O)C(c1ccc(O)cc1)CNCCN'
# equivalent to
# pkasso single --smiles 'OC(=O)C(c1ccc(O)cc1)CNCCN'

Get help for different pKasso options (single prediction, batch prediction, pH scan) with

pkasso --help
pkasso single --help
pkasso batch --help
pkasso scan --help

Python interface (e.g. in a notebook)

from pkasso import protonate

name = 'mymolecule'
smiles = r'OC(=O)C(c1ccc(O)cc1)CNCCN'
pH = 7.0

# Include microstates with probability of 20% compared to most probable microstate
# Select cutoff_export = 1. to only output the most likely microstate
cutoff_export = 0.2

# protonate accepts a smiles string or an rdkit Mol as input
smiles_out, mols_out = protonate(smiles, name=name, pH=pH, cutoff_export=cutoff_export)
print(smiles_out)

For more examples, see the jupyter notebook in example/example.ipynb.

Local webserver

A local webserver can be hosted via pip install pkasso[webserver] followed by calling pkasso-web or by downloading and running the docker image [ADD LINK].