Identifying binding sites in receptors using AutoSite tool

AutoSite is a computational method and tool that is used for the identification of binding sites of small molecules in target proteins [1]. It comes with the MGLTools2 package along with ADFR and AGFR. In this article, we will predict the binding sites in a receptor using the Autosite tool.

The potential binding sites in the receptor are computed and ranked as:

(No. of fill points X buriedness^2 )/(Radius of gyration)

We are using human serum albumin in this tutorial for binding site prediction.

Preparing receptor

1. Download the structure from PDB (here, 2BXA).
2. Remove extra chains and hetatoms.
3. Prepare the PDBQT file of the receptor following the same procedure as used in the preparation of the receptor for docking. You can find a detailed procedure in this article. As you don’t need grid file for this tutorial. Therefore, you can skip the grid box defining part for now.

Executing AutoSite

Open a terminal (Ctrl+Alt+T), change to the directory where you have saved your receptor PDBQT file, and type the following commands:

$ cd Downloads/

$ /home/user/Downloads/mgltools2_x86_64Linux2_1.0/bin/pythonsh /home/user/Downloads/mgltools2_x86_64Linux2_1.0/MGLToolsPckgs/AutoSite/bin/AS.py -r 2BXA.pdbqt

Don’t forget to replace the ‘user’ in the above command with your username.

As a result, it will output rank-based receptor files named ‘_cl_<rank>.pdb‘ for the predicted pockets and ‘_fp_<rank>.pdb‘ for the predicted ligand.

References

1. Ravindranath, P. A., & Sanner, M. F. (2016). AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms. Bioinformatics, 32(20), 3142-3149.