Improving ALS research with Google Cloud, Schrödinger, and Cycle Computing

Today we published a case study describing how the use of Google Cloud enabled one professor to do work she never thought possible. May Khanna, Assistant Professor of Pharmacology at the University of Arizona, studies pharmacological treatments for pain. Her specific area of expertise focuses on research that uses protein binding to develop possible treatments.

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Using our CycleCloud™ software to manage a 5,000 core Google Cloud Preemptible VM cluster running Schrödinger® Glide™ has enabled research she never thought possible. This cluster was used to run 20,000 hours of docking computations in four hours for $192, thanks to the simple, consistent pricing of GCP’s Preemptible VMs. The n1-highcpu-16 instances she used have 16 virtual cores and 60 gigabyte of RAM, so they’re well-suited for this kind of compute-heavy workload.

For this project, Professor Khanna wanted to analyze a protein associated with amyotrophic lateral sclerosis, also known as “ALS” or “Lou Gerhig’s disease”. ALS has no known cure and causes pain and eventual death for some 20,000 people in the United States every year.

Protein binding simulation is compute-intensive, even under the constraints researchers often apply to achieve their results in a reasonable time. For example, proteins are often simulated in isolation and the binding sites are restricted to a set of known-or-expected active locations on the protein. With those constraints, Professor Khanna was only able to simulate 50,000 compounds, which yielded a grand total of four possible hits.

She was about to give up on the project when she approached Cycle Computing. Using her Google Cloud cluster, she was able to simulate binding of a million compounds in just a few hours. From that million, 600 were hits.

And the benefits aren’t just from the research on this specific protein. By shortening the time-to-results for simulations, Professor Khanna can incorporate this kind of real-world work into her seminars as well. After working with the protein docking simulations, one undergraduate researcher wrote “a pharmacology neophyte such as myself had so much to gain from attending these cutting edge Virtual Docking experiments. This experience was as educationally enriching as it was riveting.”

Being able to complete 20,000 core-hours of simulation in a few hours for less than $200 is a great deal for research and academic work alike.

For the full details, see our case study.

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