Drug repurposing is the practice of testing approved drugs for the use against a different target. This strategy is intended to lower costs, reduce development times, and reduce the risk of failure in drug development.

In a recent publication, Shailima Rampogu[1] and coworkers used Discovery Studio to repurpose PARP inhibitors to target SARS-CoV-2 main protease. The authors used CDOCKER and the Grow Scaffold protocol to design compounds with high affinity for SARS-CoV-2 main protease. (Original manuscript)

Computational tools for lead optimization can propose synthetically feasible candidates from a reagent library representing accessible chemistry, focused on the protein target. The Grow Scaffold protocol, used by the authors of the publication, uses a reaction-based in situ enumeration approach to identify and prioritize which reagents are most likely to produce potential active compounds for the receptor binding site.

To understand how we can grow a scaffold in Discovery Studio, I will present an example with step-by-step instructions. The example uses SARS-CoV-2 main protease (PDB ID: 6LU7) and Olaparib (downloaded from pubchem), a known PARP inhibitor. The steps to use the Grow Scaffold… protocol are as follows.

• The protein-ligand complex was obtained by docking Olaparib to SARS-CoV-2 main protease using CDOCKER.
• Select H52 (the hydrogen in position 8 in the isoquinolinone ring) and create a group. To create a group right-click on the Molecule Window and click on Group… If you want to include other growing points, you should select all the growing points (Shift+left-click) before the group creation.

• Open the Grow Scaffold… protocol located in Receptor-Ligand Interactions > Lead Optimization tool panel.
• In the Parameter Explorer make sure the receptor (6lu7) and ligand (Olaparib) are correctly chosen as the Input Receptor and Input Ligand Scaffold, respectively.
• Next specify the Scaffold Growing point. From the drop-down menu select the group created in step 2.

• You may want to adjust the other parameters, but for this example the defaults were used to reduce the computational cost. Two of the most important parameters to obtain a diverse set of ligands, is to modify the Reactions and Reagents parameters. Discovery Studio comes with a set of 8 reactions, but custom reactions and reagents can be added.  
• Click on Run after everything has been set up.

When the protocol finishes, you should see 400 unique ligands generated (this number may vary depending on the parameters used).

Next Steps: You can then use docking to predict which of the generated molecules are going to bind the protein better than the original Olaparib. I used LibDock to dock the output ligands from the Grow Scaffold job and the best predicted ligand had a LibDock Score of 169.8 compared to the original Olaparib’s score of 146.9. Additional scoring of the docked ligands could be performed with CDOCKER or Calculate Binding Energies.

For the full procedure and the results for repurposing PARP inhibitors to target SARS-CoV-2 main protease please refer to the original work done by Keun Woo Lee’s group.[1]

A complete tutorial on how to use the Grow Scaffold protocol can be found in Discovery Studio’s Help (Tutorials > Receptor-Ligand Interactions tools tutorials > Optimizing lead compounds from a scaffold in a protein active site). Also, more information about the protocol and all protocol parameters, as well as the reactions that are available can be found in Discovery Studio’s Help (Receptor-Ligand Interactions tools > Receptor-Ligand Interactions tool panels > Lead Optimization tools > Grow Scaffold).

1. Rampogu, S., Jung, T.S., Ha, M.W. et al. Repurposing and computational design of PARP inhibitors as SARS-CoV-2 inhibitors. Sci Rep 13, 10583 (2023). DOI: 10.1038/s41598-023-36342-7