pkasso 0.5.2

Prediction of protonation states for small molecules

pKasso

Developed by Bind Research

Protonation state prediction for small molecules

pKasso determines protonation states for small molecules from SMILES strings or RDKit molecule objects. pKasso is open-source and free to use (MIT Licence).

Protonation microstates describe the unique charge patterns on protonable sites of molecules. The acid/base equilibria (micro-pKa values) of individual protonable sites are coupled, leading to a graph of free energy difference between protonation microstates. pKasso computes this graph based on micro-pKa predictions from MolGpKa. pKasso then converts the results into pH-dependent absolute microstate probabilities and predicts net acid/base equilibria (macro-pKa values) of the molecule.

pKasso is under active development. Features, prediction models, and results may change in future releases.

Run pKasso

The easiest way to run pKasso is via the webserver.

Local 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

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.

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 (main).