/quantum-computing-exploration-for-drug-discovery-on-aws

Deploy a solution to research on drug discovery problems using quantum computing and classical computing resources.

Primary LanguagePythonApache License 2.0Apache-2.0

Quantum Computing Exploration for Drug Discovery on AWS

Overview

Quantum Computing Exploration for Drug Discovery on AWS is an open-source solution that allows researchers and quantum computing advocates to design and run computational studies in the field of drug discovery. With this solution, you can access quantum computers via the Amazon Braket service. The Amazon Braket Hybrid Job feature allows you to use classical computing and quantum computing resources to evaluate experiment values such as cost, time, and performance. The solution comes with built-in sample code for certain drug discovery problems, such as molecular docking, protein folding, RNA folding, and retrosynthetic planning, to help you get started with quantum computing in the field.

The overall architecture is shown as below:

architecture

For detailed description of architecture, please refer to the Architecture Page

This solution deploys the Amazon CloudFormation template in your AWS Cloud account and provides the URL for Notebook Experiment about drug discovery problems.

Pre-built Examples for Drug Discovery1,2

Problem Name Method Reference
Molecular Unfolding QUBO Quantum Molecular Unfolding(2021)
RNA folding QUBO RNA folding using quantum computers(2022)
QHack 2022 winner
Protein folding Quantum Walk QFold: quantum walk and deep learning to solve protein folding(2022)
Roberto Campos's Implementation
VQE --
Grover's Algorithm Quantum Speedup for Protein Structure Prediction(2022)
Renata Wong's Implementation
Retrosynthetic Planning Quantum Reinforcement Learning Learning Retrosynthetic Planning through Simulated Experience(2019)
1.More examples to be added with continuous update

File Structure

Upon successfully cloning the repository into your local development environment, you will see the following file structure in your editor:

├── CHANGELOG.md                  [Change log file]
├── CODE_OF_CONDUCT.md            [Code of conduct file]
├── CONTRIBUTING.md               [Contribution guide]
├── LICENSE                       [LICENSE for this solution]
├── NOTICE                        [Notice for 3rd-party libraries]
├── README.md                     [Read me file]
├── docs                          [Solution's document]
│   ├── en
│   ├── index.html
│   ├── mkdocs.base.yml
│   ├── mkdocs.en.yml
│   ├── mkdocs.zh.yml
│   └── zh
└── source                        [Solution's source and test code]
    ├── README.md
    ├── cdk.json
    ├── package-lock.json
    ├── package.json
    ├── src                       [Solution's source code]
    │   ├── cdk
    │   ├── notebook
    │   │   └── healthcare-and-life-sciences
    │   │       ├── a-1-molecular-unfolding-quadratic-unconstrained-binary-optimization
    │   │       ├── b-1-folding-quadratic-unconstrained-binary-optimization
    │   │       ├── c-1-rna-folding-quadratic-unconstrained-binary-optimization
    │   │       ├── c-2-protein-folding-variational-quantum-eigensolver
    │   │       ├── c-3-protein-folding-grover-search
    │   │       └── d-1-retrosynthetic-planning-quantum-reinforcement-learning 
    │   └── stack.ts
    ├── test                      [Solution's unit test code]
    ├── tsconfig.jest.json
    ├── tsconfig.json
    └── version.json

Deploy From Source

Refer to prerequisites and deployment

Running Unit Tests

The /source/run-all-tests.sh script is the centralized script for running all unit, integration, and snapshot tests for both the CDK project as well as any associated Lambda functions or other source code packages.


cd ./source
chmod +x ./run-all-tests.sh
./run-all-tests.sh

Documents