
Amazon SageMaker enables scalable protein folding workflows using AlphaFold2 and OpenFold to accelerate drug discovery by separating computationally intensive MSA generation and structure prediction steps across optimized CPU and GPU instances.


<div><p>This article demonstrates how to build scalable protein folding workflows using Amazon SageMaker to accelerate drug discovery research.</p><ul><li>SageMaker enables interactive protein structure prediction using AlphaFold2 and OpenFold algorithms</li><li>Solution separates MSA generation (CPU) from structure prediction (GPU) for 51-57% cost savings</li><li>FSx for Lustre file system provides high-throughput access to genetic databases without repeated S3 downloads</li><li>SageMaker Pipelines orchestrates multi-step workflows with visual interface and automatic experiment tracking</li><li>Predicted protein structures visualized and compared using RMSD and template modeling score metrics</li><li>Fully managed infrastructure eliminates need for manual compute cluster setup and management</li></ul><p>This solution streamlines protein structure prediction at scale, enabling researchers to rapidly evaluate drug candidates and reduce development timelines and costs.</p></div>


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