Showing posts with label molecular docking. Show all posts
Showing posts with label molecular docking. Show all posts

Tuesday, June 30, 2020

Two steps for virtual screening in the pocket of SARS-CoV-2 Mpro

1. Introduction
In this tutorial, we introduce the fast way for drug virtual screening of SARS-CoV-2 Mpro based on the known database such as ZINC database. The premise for this tutorial is that you can deal with protein structure for Autodock Vina. If you are not familiar with it, you can learn from the previous tutorial https://github.com/MolAICal/documents/tree/master/tutorials/002-AIVS. Here, MolAICal (https://doi.org/10.1093/bib/bbaa161) is employed for this tutorial.

2. Materials
2.1. Software requirement
1) MolAICal: https://molaical.github.io

2.2. Example files
1) All the necessary tutorial files are downloaded from:
https://github.com/MolAICal/tutorials/tree/master/003-VS
2) The file named “ligandSet.mol2” which contains 16 ligands obtained from ZINC database is chosen for demo. You can select your ligand database.
3) The protein file named “pro.pdbqt” that is PDBQT format structure of SARS-CoV-2 Mpro is used for molecular docking.


For more detailed procedures, please go to https://molaical.github.io, and click the section named "Tutorials" in the left part of webpage. Once "Tutorials" open, you can freely find pdf file about this tutorial (see Figure 1):
                                                            Figure 1

You can repeat this tutorial according to the content of pdf file.


Tutorials of 3D drug design by AI and virtual screening method

1. Introduction
A new drug development may cost about 2.6 billion USD. However, about 90% of drugs are failure in the process of clinical trial and approval for marketing even though a lot of capital is used to drug development1. In this tutorial, the standard protocol of MolAICal (https://doi.org/10.1093/bib/bbaa161) is introduced for the drug design of SARS-CoV-2 Mpro by artificial intelligence and molecular docking method. It will help the pharmacologist, chemists and other scientists design rational drugs according to the three-dimensional active pocket of proteins.

2. Materials
2.1. Software requirement
1)    MolAICal (win64 or linux64): https://molaical.github.io
2)    UCSF Chimera: https://www.cgl.ucsf.edu/chimera/
3)    MGLTools: https://ccsb.scripps.edu/mgltools/downloads/
4)    Python: https://www.python.org/
5)    Pymol: http://www.lfd.uci.edu/~gohlke/pythonlibs

It is easily to install the first four software. They can be easily installed by following step tips. For pymol install, it needs modules numpy, pmw, pymol_launcher and pymol. The numpy, pmw, pymol_launcher and pymol should choose the same version and correspond to your installed version of Python in your operating system. They can be downloaded from the below website:
 

https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
https://www.lfd.uci.edu/~gohlke/pythonlibs/#pymol-open-source
 

Then install Pymol by following command:
#> pip install --no-index --find-links="%CD%" pymol_launcher

The Pymol named “pymol.exe” will be installed in the directory “Scripts” in your installed directory of Python. You can make a shortcut on your desktop of operating system.
Make sure all software is installed rightly.

2.2. Example files
All the necessary tutorial files are downloaded from:
https://github.com/MolAICal/tutorials/tree/master/002-AIVS


For more detailed procedures, please go to https://molaical.github.io, and click the section named "Tutorials" in the left part of webpage. Once "Tutorials" open, you can freely find pdf file about this tutorial (see Figure 1):
                                                             Figure 1

You can repeat this tutorial according to the content of pdf file.