FastROCS: Difference between revisions

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  $ ShapeDatabaseClientHistogram.py <server:port> <query> <results> [num_hits = 100]
  $ ShapeDatabaseClientHistogram.py <server:port> <query> <results> [num_hits = 100]


===Running FastROCS on command line on a small database===




[[Category:Tutorials]]
[[Category:Tutorials]]

Revision as of 00:25, 20 April 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

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-9-34.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