Using the Cloud to study the impact of post-translational modifications of proteins and their complexes

While the foundation of the structural and functional diversity of a cell’s proteome lies in the gene-encoded primary polypeptide sequences of proteins, this basic framework is vastly enriched by a wide array of post-translational modifications (PTMs). PTMs are covalent, enzymatic, or non-enzymatic attachments of specific chemical groups to amino acid side chains either reversibly or irreversibly. PTMs can affect all aspects of protein function and dynamics, including the assembly of complexes, protein lifespan, protein-protein interactions, and receptor activation.



Given the wide array of proteins, their complexes, and the possible PTMs that can occur on them, the computing power to study the impact of PTMs increases rapidly in a combinatorial way. We have recently developed the PTMPSI Python package to facilitate the introduction and simulation of such modifications' impact on protein structure and dynamics. Cloud services, like Microsoft’s Azure Quantum Elements (AQE), provide an effective computational framework that can be used in both high-performance computing (HPC) and high-throughput computing (HTC) fashion. Here, we will discuss our efforts to port the PTMPSI into the AQE cloud and the advantages and disadvantages of this model versus traditional in-house HPC clusters. We will showcase the capabilities and areas of opportunity of our software by studying a well-known protein complex involved in the regulatory mechanisms of the Calvin-Benson cycle in cyanobacteria.