FastROCS: Difference between revisions

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There is also an installation guide on OpenEye website for alternatives. [https://docs.eyesopen.com/toolkits/python/quickstart-python/install.html Click here]
There is also an installation guide on OpenEye website for alternatives. [https://docs.eyesopen.com/toolkits/python/quickstart-python/install.html Click here]
===(Admin-only) Setting up FastROCS server===
===(Admin-only) Setting up FastROCS server===
  '''This needs to take place in a GPU-enabled computer'''
'''This needs to take place in a GPU-enabled computer'''
   View [[FastROCS Server]]
   View [[FastROCS Server]]
===Running query on FastROCS server===
===Running query on FastROCS server===
   View [[FastROCS Usage]]
   View [[FastROCS Usage]]

Revision as of 18:18, 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

 View FastROCS Usage

1. Set up virtual environment

cd /nfs/home/khtang/ex9/openeye/FastROCS
source ./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