Velocity

a Python package for running kinetic simulations

Introduction

Velocity lets you define chemical reaction networks and simulates their timecourses by numerically integrating the underlying differential equations. Support for multiple reagent doses is provided.

Installation

Add this folder to the PYTHONPATH. You will need these packages:

• numpy
• scipy
• pandas
• pytest
• pdoc

Quick Start

Here's how to setup a simple A --> B reaction network:

species_A = Species("A")
species_B = Species("B")
    
reaction1 = Reaction(species_A, species_B)

reactions_dict = {
    reaction1 : 0.05,  # rate constant
}

network = Network(reactions_dict, fixed_concentrations=None)

In this case, the abbreviation for species_A is just "A." You can define longer names this way:

Species("MeOH", "methanol")

(Keep in mind abbreviations must no more than 5 characters long.)

Now, we'll tell velocity to simulate 100 seconds of data and that we want to start with a concentration of 1.0 for A.

t_span = (0.0, 100.0)
t_eval = np.linspace(0,100,101)
initial_concentrations_dict = { species_A : 1.0 }
concentrations_df = network.simulate_timecourse(initial_concentrations_dict, t_span, t_eval)

concentrations_df will contain the abbreviations for Species as the column headings and t_eval as the index:

              A         B
time
0.0    1.000000  0.000000
1.0    0.951229  0.048771
2.0    0.904837  0.095163
3.0    0.860704  0.139296
...         ...       ...
100.0  0.006756  0.993244

Multiple Dosing

You can add reagents after the start of the experiment, but you'll have to specify volumes. Using the same setup as above:

# your friendly helper, the ExperimentBuilder
builder = ExperimentBuilder(network)

# what concentrations to start with
builder.schedule_start(initial_concentrations_dict, volume=1.0)

# add more A at t=100
builder.schedule_addition({species_A:2.0}, volume=0.5, time=100.0)

# stop simulating here
builder.schedule_end(time=200.0)

# as before
builder.add_eval_times(eval_times)
experiment = builder.build()
experiment.simulate()

Here's the result in experiment.df:

             A         B
time
0     1.000000  0.000000
10    0.606492  0.393508
20    0.367789  0.632211
...
90    0.011137  0.988863
100   0.671170  0.662163
110   0.406818  0.926516
...
200   0.004539  1.328795

You can also specify dosing in segments of defined lengths. See tests/test_chemistry_experiment.py:test_two_additions() for an example.

Sugar Analysis

This package was developed to analyze the kinetics of interconverting hexoses. Notebooks and data are provided in the sugar/ folder:

• catalyst_deactivation: assessment of the lifetime of the amine/thiol catalyst system using a multiple dosing strategy
• sugar_cube: kinetic characterization of the interconverting hexoses using timecourse and deuteration data
• infinite_time: allows one to inspect the sugar_cube model by starting from arbitrary sugar distributions, with and without catalyst deactivation

Tests

To run all the tests, execute these commands in the project root:

export PYTHONPATH=.
pytest

API Documentation

Good API-level documentation is available. These docs can be built with pdoc. In the project root:

pdoc --docformat google velocity/*.py -o docs

License

This project is licensed under the Apache License, Version 2.0. Please see LICENSE for full terms and conditions.

Author

Eugene Kwan, 2023