PTM-Psi on the Cloud: A Cloud-Compatible Workflow for Scalable, High-Throughput Simulation of Post-Translational Modifications in Protein Complexes

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 cycle of light-dependent sugar production in cyanobacteria. With PTM-Psi on the cloud, we transformed the pipeline for the thiol PTM analysis to achieve high throughput by leveraging the strengths of the cloud service. PTM-Psi on the cloud reduces operational complexity and lowers entry barriers to data interpretation with structural modeling for a redox proteomics mass spectrometry specialist.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-10-03
DOI
https://doi.org/10.1021/acs.jcim.5c01661
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
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article

PTM-Psi on the Cloud: A Cloud-Compatible Workflow for Scalable, High-Throughput Simulation of Post-Translational Modifications in Protein Complexes

Margaret S. Cheung, Michael E. Lockwood, Daniel Mejı́a-Rodrı́guez, Ho Shin Kim et al.
Journal of Chemical Information and Modeling
Scientific Computing and Data Management
article

PTM-Psi on the Cloud: A Cloud-Compatible Workflow for Scalable, High-Throughput Simulation of Post-Translational Modifications in Protein Complexes

Margaret S. Cheung, Michael E. Lockwood, Daniel Mejı́a-Rodrı́guez, Ho Shin Kim, Amity Andersen, Suman Samantray, Paul Rigor
article en

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 cycle of light-dependent sugar production in cyanobacteria. With PTM-Psi on the cloud, we transformed the pipeline for the thiol PTM analysis to achieve high throughput by leveraging the strengths of the cloud service. PTM-Psi on the cloud reduces operational complexity and lowers entry barriers to data interpretation with structural modeling for a redox proteomics mass spectrometry specialist.

Journal of Chemical Information and ModelingVol. 65(20)
Pacific Northwest National Laboratory (US), Environmental Molecular Sciences Laboratory (US), Physical Sciences (United States) (US), Computing Center (RU)
Openalex Percentile: Top 73%
Scientific Computing and Data Management
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