Illustrating and homology modeling the proteins of the Zika virus

  • Sean Ekins, John Liebler, Bruno J. Neves, Warren G. Lewis, Megan Coffee, Rachelle Bienstock, Christopher Southan, Carolina H. Andrade
  • F1000Research, March 2016, Faculty of 1000, Ltd.
  • DOI: 10.12688/f1000research.8213.1

Modeling the proteins in the Zika virus

What is it about?

This paper describes the construction of homology models for all the proteins in the Zika virus. Public software was used to generate these models which were evaluated with commercial and other tools. The Glycoprotein E model was used to generate a model of the complete virus. These various models are now publically accessible and can be used for docking etc.

Why is it important?

This is the first paper describing models for all the proteins in the Zika virus. 11 out of 15 appeared to be useful based on the model criteria described. This represents the starting point for future structure-based work to discover molecules that could bind to these proteins.

Perspectives

Dr Sean Ekins
Collaborations in Chemistry

This work was inspired by John who wanted to illustrate the virus. This triggered me to model all the proteins and pull a team of other scientists together to get their comments and insights. Carolina's group did further analysis and work to ensure the protein models looked good. The work transpired over a couple of weeks in February 2016. All the models were also initially deposited in Figshare.

Dr Christopher Southan

I came to the party a little late on this one but I had been both collating some anti-Dengue chemistry and doing some sequence analysis on my blog which I was able to adapt to fit the publication. The amino acid similarity statistics are important for judging the plausibility of getting target models that have real utility for VS work and docking. In addition they can suggest a priority triage for experimental screening (i.e. in this case we can preict that target-based anti-Dengue cpds shoud cross-inhibit more than HCV inhibitors). I hope to expand on these aspects when we revise the submission.

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http://dx.doi.org/10.12688/f1000research.8213.1

The following have contributed to this page: Dr Sean Ekins, Dr Rachelle J Bienstock, Dr Carolina Horta Andrade, and Dr Christopher Southan