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Currently accepted at: JMIR Bioinformatics and Biotechnology

Date Submitted: Apr 3, 2019
Date Accepted: Sep 24, 2019

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/14232

The final accepted version (not copyedited yet) is in this tab.

Click by Click Molecular Docking for non-bioinformaticians using Chimera 1.12

  • Sania Safdar Butt; 
  • Yasmeen Badshah; 
  • Maria Shabbir; 
  • Mehak Rafiq; 

ABSTRACT

In the field of drug discovery, many methods of molecular modeling have been employed to study the complex biological and chemical systems. Experimental strategies are integrated with computational approaches in the identification, characterization and development of novel drugs and compounds. Molecular Docking is the approach in the modern drug design that explores the confirmation of ligand within the binding site of the macromolecule. To date many software’s and tools for Docking have been employed. AutoDock Vina (in UCSF Chimera) is one of the computationally fast and accurate software employed in Docking. In this paper, a sequential demonstration of molecular Docking of ligand Fisetin with the target protein Akt has been provided, using AutoDock Vina in UCSF Chimera 1.12. The first step involves the target protein ID retrieval from PDB, the second step is to visualize the structure of protein in UCSF Chimera, the third step is to prepare the target protein for Docking, the fourth step is preparing the ligand for docking, the fifth step is the Docking of ligand and the target protein as Mol.2 files in Chimera using AutoDock Vina and the final step is the interpretation and analysis of Docking results. By following the guidelines and the steps used in this paper, the researchers who have no previous background in bioinformatics research can perform computational Docking in a more user-friendly and easy manner.


 Citation

Please cite as:

Butt SS, Badshah Y, Shabbir M, Rafiq M

Click by Click Molecular Docking for non-bioinformaticians using Chimera 1.12

DOI: 10.2196/14232

URL: https://preprints.jmir.org/preprint/14232


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