Quantum Computing Exploration for Drug Discovery on Amazon Web Services

An open-source solution for exploring quantum computing in the drug discovery field

Quantum Computing Exploration for Drug Discovery on Amazon Web Services is an open-source solution that allows researchers or quantum computing advocates to design and run computational studies in the field of drug discovery. With the solution, you can access quantum computers via Amazon Braket service, use Amazon Batch for job management, and leverage Amazon Step Functions to orchestrate different workflows. The solution helps you to use classical computing and quantum computing resources to evaluate experiment values such as cost, time, performance, and so on. Evaluation results are visualized in Amazon QuickSight. The solution comes with built-in code for certain drug discovery problems, such as molecular docking and protein folding, for you to get started with quantum computing in the field. 

Benefits

Hybrid architecture

The solution provides a hybrid architecture that offers flexibility for you to use either quantum computing or classical computing resources, or both. You can evaluate and compare experimental values by testing the same problem with these resources.

Drug discovery use cases

The solution includes code for certain drug discovery use cases. You can learn and customize the code step-by-step in Jupyter Notebook.

Visualization

The batch run results are stored in Amazon S3 and visualized with Amazon QuickSight. You can build the customized QuickSight dashboards or use the built-in dashboards.

Solution overview

The diagram below presents the architecture you can automatically deploy using the solution's implementation guide and accompanying Amazon CloudFormation template.

Quantum Computing Exploration for Drug Discovery on Amazon Web Services

This solution deploys the Amazon CloudFormation template in your Amazon Cloud account and provides three parts:

Notebook experimentation    

1.  An Amazon SageMaker Notebook instance, which allows notebook experimentation for drug discovery.

2.  The notebook comes with built-in code for different problems in drug discovery, such as molecular unfolding.

3.  The solution creates Network Address Translation (NAT) gateways in public subnets, which connect to the internet using an internet gateway. The notebook instance is deployed in private subnets, and can access internet using NAT gateways.

Batch evaluation

4.  Amazon Step Functions workflows for batch evaluation.

5.  The Amazon Step Functions workflows launch various computing tasks in parallel through Amazon Batch jobs based on different model parameters and resources for classical computing or quantum computing.

6.  Each Amazon Batch job uses pre-built container images and attempts to evaluate a particular drug discovery problem based on specific model parameters.

7.  All the pre-built container images are stored in Amazon ECR.

8.  Amazon Batch jobs evaluate the problem on Amazon EC2, and save results in Amazon S3.

9.  Amazon Batch jobs asynchronously submit Amazon Braket tasks.

10.   When an Amazon Braket task is completed, it saves output as a file in an Amazon S3 bucket, and an event is dispatched via Amazon EventBridge.

11.  An Amazon Lambda function is triggered by events from EventBridge, parses the output file of the Braket task in S3, saves the evaluation result to the S3 bucket, and sends a callback to the Amazon Step Functions workflow.

Visualization

12.  When the whole batch evaluation is done, the workflow sends a notification to an Amazon SNS topic. All subscribers will be notified for the batch evaluation results.

13.  An Amazon Athena table is created for querying the metrics of batch evaluation.

14.  Amazon QuickSight to view the batch evaluation results. By default, the solution provides metrics for the running time of different resources.

Quantum Computing Exploration for Drug Discovery on Amazon Web Services

Version 1.0.1
Last updated: 06/2022
Author: Amazon Web Services 

Estimated deployment time: 10 min

Source code 
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