Accelerating 3D Protein Structure Similarity Searching on Microsoft Azure Cloud with Local Replicas of Macromolecular Data

摘要

Searching similarities among 3D protein structures deposited in macromolecular data repositories, like Protein Data Bank, is one of the time-consuming processes performed in structural bioinformatics. When performed in one-to-many or many-to-many model, the process requires increased computational resources. Moreover, exponential growth of protein structures in the Protein Data Bank causes the necessity to prepare computer systems to be able to deal with such huge volumes of data. Cloud computing provides both, theoretically infinite computational resources and a great possibility of scaling systems out and up. In this paper, we show how 3D protein structure similarity searching can be scaled out on Microsoft Azure cloud and performed by a loosely coupled, many-task computing system with local replicas of macromolecular data.