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CompChem Tools
Whilst there are number of Open Source computational toolkits and command-line tools they often present a step learning curve for new users. In an effort to provide a simpler environment to access these tools this page will highlight a series of Jupyter notebooks that users can use to run key computational studies that might be undertaken in a drug discovery project.
This notebook implements a typical protocol for docking ligands to a target protein. It uses RDKit (http://www.rdkit.org) to generate a number of reasonable conformations for each ligand and then uses SMINA (https://sourceforge.net/projects/smina/) to do the docking. Two methods of docking are implemented, the first docks into a rigid receptor, the second sets the protein side-chains around the active site to be flexible. Bear in mind flexible docking will be much, much slower. In the optional final step the resulting docked poses are rescored using a random forest model described in https://www.nature.com/articles/srep46710. You can read more details of the notebook here and you can down load a folder containing the notebook and the [necessary files here] (https://opensourceantibiotics.github.io/murligase/CompChemTools/UsingSmina.zip).