antivirals 0.0.1

Finding antivirals for the novel coronavirus.

Coronavirus Antivirals

This project hopes to discover an antiviral that can treat the novel coronavirus disease. This project will use newer approaches in machine learning to model and optimize for the properties needed in candidate therapeutics.

In therapeutic drug development the properties we minimize are toxicity and side-effects (also called “off-target effects”). Properties we maximize are bioactivity on target (also called “on-target effects”), absorption, synthesizability, and large-scale manufacturability.

We aim to search the molecular space (both drug-like molecules, and already approved drugs) for drug candidates maximizing these properties.

How to Contribute

We need your help if you have one of the following skills:

• Software development in Python

• Machine learning

• Web development (for the UI)

• DevOps – especially with Kubernetes and Helm

Fork the project and create a new branch:

git checkout -b feature/my_new_feature

Push your changes and use GitHub to submit a pull request.

Any contributions are helpful. Look at the open issues for inspiration on what to work on.

License

Apache 2. See LICENSE file for details.

Installation

Using the system through Docker is highly recommended:

docker run -v my_host_data_directory:/app/data -it inqtel/antivirals up sqlite:////app/data/antivirals.db

Alternatively, a package is also available:

pip install antivirals

Archiecture

The system is structured in a quazi Model-View-Controller archiecture.

• __init__.py: Executes operations like training and inference. The “controller” layer in MVC archiecture.

• schema.py: Contains all the code for adding to and querying the molecular database. The “model” layer in MVC archiecture.

• __main__.py: A command-line user interface. The “view” layer in MVC archiecture.

• data.py: Maps from public datasets (eg. ZINC Clean Leads, Tox21) to the molecular database schema.

• chem.py: The actual cheminformatics machine learning algorithms.

There is also work to make it function as part of Docker and Kubernetes. Help is needed!

Usage

The Coronavirus Antivirals project comes bundled with a command line tool.

You must have a SQLAlchemy compatible database running. Otherwise everything gets stored in volitile memory. Any database string can be used in theory, but it has only been tested with SQLite.

To completely set up the project and run an agent that runs indefinitely doing antivirals experiments, simply run:

antivirals up sqlite:///path/to/your/db

This command sets up the whole Coronavirus Antivirals system de novo (downloading data, training models, etc).

Any models generated will be dumped in the current working directory in “data”. When you use Docker or Kubernetes you want to mount the /app/data folder in the container to a volume.

There is some more advanced usage. Inline documentation about other actions is available:

antivirals -h

Acknowledgment

A project of B.Next.