For very large virtual-screening tasks, we provide the GOLD Cloud tool. For smaller-scale parallelization, e.g. on a computational chemist's workstation or a local compute server, we do not have a specific product, but options are available.
This tool runs GOLD on a Kubernetes cluster using Docker containers and is intended be used with commercial cloud platforms. Our experience is with Azure, but we are aware of customers who have used AWS and GCP. Further details are available in the GOLD Cloud User Guide and the tooling is available for download via your normal mechanism. A White Paper describing a practical application of the GOLD Cloud is also available.
GOLD Cloud can also be run locally using MiniKube or Docker Desktop. Thus, in principle, this tool may be used to parallelize GOLD docking. However, the setup involved isn't trivial and might not be straightforward on all platforms. A simpler solution for this use-case is thus provided below.
The linked archive contains scripts which illustrate the use the CSD Docking API and the Python standard-library multiprocessing module to parallelize GOLD docking. This approach should be suitable for docking some hundreds or perhaps thousands of ligands, depending on the compute resource available. Further information is available in the ReadMe.txt in the archive.
Platforms no longer supported
We no longer support using GOLD with Parallel Virtual Machine (PVM). We also do not currently provide tooling or support for running GOLD on Grid Engines, although there is nothing in principle that should prevent this being done.