PTM-Psi on the Cloud
Suman Samantray, Margot Lockwood, Amity Andersen, Hoshin Kim, Paul Rigor, Margaret S. Cheung, Daniel Mejia-Rodriguez

TL;DR
This paper presents PTM-Psi on the Cloud, a cloud-based computational framework that accelerates the study of post-translational modifications on proteins by leveraging asynchronous workflows and cloud resources, enabling high-throughput analysis.
Contribution
It introduces a cloud-compatible version of PTM-Psi with a workflow of workflows approach, optimizing resource use for complex PTM analysis on Azure Quantum Elements Cloud.
Findings
Enabled high-throughput PTM analysis on cloud
Reduced operational complexity for structural modeling
Demonstrated scalability with protein megacomplex study
Abstract
We developed an advanced computational framework to accelerate the study of the impact of post-translational modifications on protein structures and interactions (PTM-Psi) using asynchronous, loosely coupled workflows on the Azure Quantum Elements Cloud platform. We seamlessly integrate emerging cloud computing assets that further expand the scope and capability of PTM-Psi Python package by refactoring it into a cloud-compatible library. We employed a "workflow of workflows" approach wherein a parent workflow spawns one or more child workflows, managing them, and acting on their results. This approach enabled us to optimize resource allocation according to each workflow's needs, and allowed us to use the cloud heterogeneous architecture for the computational investigation of a combinatorial explosion of thiol protein PTMs on an exemplary protein megacomplex critical to the Calvin-Benson…
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