Serverless Science Gateway Development for Ca2+ binding site prediction on Amazon Web Services: Case Study
TimeWednesday, July 311:30pm - 2pm
DescriptionIn this paper, we discuss the development of a science gateway; Identifying Ca2+ -binding sites in proteins using java application, developed by Dr. Jenny Yang at the Chemistry department, Georgia State University. Starting with a Protein Data Bank (PDB) x-ray or NMR structure file, MUGC application predicts calcium binding sites using a graph theory based algorithm. The project creates a science gateway to provide access to the MUGC algorithm using tools provided by Amazon Web Services. The full-stack solution uses S3 storage, AWS Lambda functions, and API gateway to relay the PDB files to the back-end computing in EC2. Architecture for a full stack serverless processing pipeline is implemented which allows users to access the application. The design is optimized for scalability, reliability, security, performance, and cost.