FastROCS: Difference between revisions
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====1. Set up virtual environment==== | ====1. Set up virtual environment==== | ||
On bash shell | On bash shell | ||
source /nfs/home/khtang/ex9/openeye/FastROCS/source_venv | $ source /nfs/home/khtang/ex9/openeye/FastROCS/source_venv | ||
====2. Run search==== | ====2. Run search==== |
Revision as of 21:30, 20 March 2019
Overview
FastROCS is an virtual screening tool using shape comparison for potential actives discovery. It is vastly improved of ROCS in term of speed. It could automatically split the search into many parallel searches depending on how many GPU are there.
Tutorials
Install FastROCS
See Openeye python libraries. There is also an installation guide on OpenEye website for alternatives. Click here
(Admin-only) Setting up FastROCS server
This needs to take place in a GPU-enabled computer
View FastROCS Server
Running query on FastROCS server
Any computer
1. Set up virtual environment
On bash shell
$ source /nfs/home/khtang/ex9/openeye/FastROCS/source_venv
2. Run search
$ ShapeDatabaseClient.py [-h] [--tversky] [--shapeOnly] [--alternativeStarts {random,subrocs,inertialAtHeavyAtoms,inertialAtColorAtoms}] server:port query results [nHits] example: ShapeDatabaseClient.py n-9-34.cluster.ucsf.bkslab.org:8080 ZINC000000002837.sdf result.sdf
Send a query to a specified ShapeDatabaseServer and print the histogram of scores for the entire database of molecules
$ ShapeDatabaseClientHistogram.py <server:port> <query> <results> [num_hits = 100]