Connect with us

Docking

Identifying binding sites in receptors using AutoSite tool

Published

on

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 any 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 as ‘_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. Bioinformatics32(20), 3142-3149.

 

Tariq is founder of Bioinformatics Review and CEO at IQL Technologies. His areas of expertise include algorithm design, phylogenetics, MicroArray, Plant Systematics, and genome data analysis. If you have questions, reach out to him via his homepage.

Docking

What values are considered as good or bad in computational docking?

Published

on

After performing computational docking, a question that comes to mind most is “what docking score is considered good or bad”. In this article, we will discuss this in detail. (more…)

Continue Reading

Bioinformatics Programming

How to sort binding affinities based on a cutoff using vs_analysis.py script?

Published

on

How to sort binding affinities based on a cutoff using vs_analysis.py script?

Previously, we have provided a Python script (vs_analysis.py) to analyze the virtual screening (VS) results of Autodock Vina. Now, we have updated this script to sort binding affinities based on user inputted cutoff value. (more…)

Continue Reading

Docking

Virtual Screening using Autodock Vina: Frequently Asked Questions & Answers for Starters

Published

on

Virtual Screening using Autodock Vina: Virtual Screening: Frequently Asked Questions & Answers for Starters

Virtual Screening (VS) is one of the important techniques in bioinformatics. It can be easily performed using Autodock Vina. We have provided detailed articles on this topic. In this article, we are trying to answer some FAQs for beginners. (more…)

Continue Reading

LATEST ISSUE

ADVERT