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Generating multiple low-energy conformers using Avogadro

Dr. Muniba Faiza
Last updated: October 1, 2021 7:41 pm
Dr. Muniba Faiza
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Generating multiple low-energy conformers using Avogadro
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In our previous article, we generated multiple conformers using OpenBabel. In this article, we are going to generate multiple low-energy conformers of a ligand using Avogadro [1].

Contents
  • References
  • Further Reading

Let’s say, we have a pdb file of a ligand (namely, ligand.pdb) and we want to generate 100 conformers in the same format. Follow the steps given below.

  • Open Avogadro.
  • Go to File --> Open --> ligand.pdb.
  • Go to Extensions --> Optimize Geometry.
  • After optimization, set up a force field. Go to Extensions --> Molecular Mechanics --> Setup Force Field...
  • Select an appropriate force field and number of steps for optimization. MMFF94 is considered a good force field for organic molecules and UFF is also a good option. We are using default values here.
  • Click Ok.
  • Now, let’s search for conformers. Go to Extensions --> Molecular Mechanics --> Conformer Search...
  • Now, select a search method and enter an appropriate number of conformers. We are going to generate 100 conformers only. If you select the ‘Genetic Algorithm’ search method then select a ‘Scoring Method’ as well.
  • Click Ok. It will start the search and soon you will get the conformers.

References

  1. Hanwell, M. D., Curtis, D. E., Lonie, D. C., Vandermeersch, T., Zurek, E., & Hutchison, G. R. (2012). Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. Journal of cheminformatics, 4(1), 1-17.

Further Reading

How to generate multiple conformers of a ligand using OpenBabel?

How to perform virtual screening using Pyrx?

How to install idock on Ubuntu?

TAGGED:avogadrodockingmultiple conformers
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ByDr. Muniba Faiza
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Dr. Muniba is a Bioinformatician based in New Delhi, India. She has completed her PhD in Bioinformatics from South China University of Technology, Guangzhou, China. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba
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