GCAC can be used as virtual screening platform for drug discovery process. User may create , share and use predictive model that can be used to predict the activity of given compound. The GCAC uses PaDEL for descriptor calculation and R-caret for predictive modelling. “MayaChemTools” used for extracting the potential compounds from large compound library (SDF/Mol). Entire GCAC pipeline is available as galaxy wrapper which ensures reproducibility and sharing of code and data across the globe.
If Toolshed repository is used for installation in galaxy then following prerequisites are need to be address.
- The system package dependencies for GCAC. The following yum packages need to be installed on the Galaxy instance host machine.
- The latex package dependencies for GCAC. The following latex packages need to be installed on the Galaxy instance host machine.
Manual available at demo server. You may download manual from here also. Other important documents are available at demo server “http://ccbb.jnu.ac.in/gcac”.