Difference between revisions of "FastROCS"

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(2. Run search)
(1. Set up virtual environment)
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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/ex9/work/khtang/openeye/FastROCS/source_venv
To deactivate conda environment
To deactivate conda environment

Latest revision as of 10:47, 16 April 2020


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.


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/ex9/work/khtang/openeye/FastROCS/source_venv

To deactivate conda environment

$ conda deactivate

2. Run search

$ ShapeDatabaseClient.py [-h] [--tversky] [--shapeOnly]
                             [--alternativeStarts {random,subrocs,inertialAtHeavyAtoms,inertialAtColorAtoms}]
                             server:port query results [nHits]
example: ShapeDatabaseClient.py n-1-141.cluster.ucsf.bkslab.org:8080 ZINC000000002837.sdf result.sdf 3000

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]

Running FastROCS on command line on a small database