OCEAN is a web-tool for target-prediction of chemical structures which uses ChEMBL as datasource. For more details please feel free to read the paper.
We recommend to use myChembl20-VM which has almost everything you need to run OCEAN.
Nevertheless here are the core-depencies:
RDKit (2015.03.1)http://www.rdkit.org/Django (1.7.1)numpy (1.9.0)sciPy (0.15.1)your preferred database-server (Oracle or PostgreSQL, we didn't test MySQL or sqlite but they are supported by Django as well)python module for your database-server (cx_oracle for Oracle, psycopg2 for PostgreSQL)
matplotlib (1.3.0)pillow (2.6.1)images2gif (1.0.1)
Prepare and activate a virtual environment for OCEAN:
# create a virtualEnv for OCEAN
virtualenv --system-site-packages ocean_env
# activate ocean_env
source ocean_env/bin/activate
# install Django 1.7.1
pip install Django==1.7.1
Get a clone of OCEAN from the Repo:
git clone https://www.github.com/rdkit/OCEAN.git
cd OCEAN
Create a PostgreSQL-User, the database for OCEAN and fill the OCEAN-DB:
# create PostgreSQL-User for OCEAN
# password 'ocean_pw' should be used when asked,
# according to database-entry in settings.py
createuser -P -s -d -r -e ocean_user
# create PostgreSQL-Database for OCEAN
createdb --owner=ocean_user ocean
If you want to use ChEMBL17-data for OCEAN you should:
change line
CHEMBL_VERSION = "chembl_%d" % (20)in fileocean/settings.pytoCHEMBL_VERSION = "chembl_%d" % (17)
createdb --owner=ocean_user chembl_17
# create and populate OCEAN-DB (duration <2 min)
psql chembl_17 < postgres_createOceanDB.sql
./importOcean17DB.sh
# Chembl17 is not a part of myChembl20-VM, so we need to create and populate
# a few tables (duration <10 sec)
psql chembl_17 < postgres_createChembl17Tables.sql
./importChembl17Tables.sh
For ChEMBL20-data you should:
psql chembl_20 < postgres_createOceanDB.sql
./importOcean20DB.sh
It's time to start OCEAN:
# On first start, you have to sync the django-server to create all missing tables.
# When asked, you should create a superuser and set a password.
# This is necessary to have access to the django-admin portal of OCEAN.
python manage.py syncdb
# Start OCEAN
python manage.py runserver 0.0.0.0:8080
The next steps are necessary to create the fingerprints for all structures:
-
Login to ocean-admin portal http://0.0.0.0:8080/admin
-
Select CHEMBL and 6 (section a), press createFPs to create Morgan-Fingerprints for all entries. This may take a few minutes. You should see a message at the bottom of the site when the process is done.
The last step is calculating the statistical parameters for OCEAN's scoring-function:
- In the Django-Admin portal select CHEMBL, 6 and activate Checkbox rebuild Pairs (section b), press recalc Statistics for Fingerprint and Datasource to calculate statistic-parameters for the scoring-function. This will also take a few minutes. Wait until you see a new message at the bottom of the site.
If you have a MarvinJS licence, you can copy the MarvinJS-folder to ocean/media/MarvinJS and change the line url(r'^$', main_smiles, name='home') in ocean/urls.py to url(r'^$', main_marvin, name='home') to use MarvinJS as sketcher.
Now lets try it:
-
Open ocean-website http://0.0.0.0:8080
-
Write a smiles-string into the smiles-field or sketch a molecule (if you have MarvinJS) and press Button Start OCEAN-Search. You should see the results after a few seconds.
If you have any questions or problems with OCEAN please do not hesitate to contact Paul Czodrowski or Wolf-Guido Bolick.