Large-Scale Docking in the Cloud

Abstract

Molecular docking is a pragmatic approach to exploit protein structures for new ligand discovery, but the growing size of available chemical space is increasingly challenging to screen on in-house computer clusters. We have therefore developed AWS-DOCK, a protocol for running UCSF DOCK in the AWS cloud. Our approach leverages the low cost and scalability of cloud resources combined with a low-molecule-cost docking engine to screen billions of molecules efficiently. We benchmarked our system by screening 50 million HAC 22 molecules against the DRD4 receptor with an average CPU time of around 1 s per molecule. We saw up to 3-fold variations in cost between AWS availability zones. Docking 4.5 billion lead-like molecules, a 7 week calculation on our 1000-core lab cluster, runs in about a week depending on accessible CPUs, in AWS for around $25,000, less than the cost of two new nodes. The cloud docking protocol is described in easy-to-follow steps and may be sufficiently general to be used for other docking programs. All the tools to enable AWS-DOCK are available free to everyone, while DOCK 3.8 is free for academic research.

Figure 1

Docking in the cloud. Though conceptually simple, cloud docking presents operational complexities that must be overcome. (A) Upload receptor model and software. The dockable database is preloaded. (B) LSD jobs are run, potentially at an immense scale, and the results are merged to top-hit collections (T.H.C.) within cloud storage. (C) The T.H.C. results are downloaded for prioritization and purchase.