Webinar: PRODIGY, a web server to predict binding affinities in protein-protein complexes (12 October 2016)


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studiare il trading on line opzioni binarie The 7th webinar in BioExcel’s webinar series on computational methods and applications for biomolecular research took place on Wednesday 12th October.

http://vietmoz.com/?syrcis=trading-on-line-forex trading on line forex Anna Vangone introduced PRODIGY, a web server to predict binding affinities in protein-protein complexes.

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buy Finpecia 1mg india The series cover broad topics related to the latest development of major software packages; their application to modelling and simulation; best practices for performance tuning and efficient usage on HPC and novel architectures; introductory tutorials for novel users and much more.

buy tastylia online The webinars include an audience Q&A session during which attendees can ask questions and make suggestions. They are a great opportunity to interact with the main code developers.

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PRODIGY, a web server to predict of binding affinities in protein-protein complexes

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http://jaholtom.com/?binarit=pdf-opzioni-binarie-guide&95b=c1 pdf opzioni binarie guide anna-vangoneAnna Vangone

http://maxbaillie.com/wp-cron.php?doing_wp_cron=1468965424.4381299018859863281250 vincite con opzioni binarie Bijvoet Center for Biomolecular Research
Science Faculty/Chemistry, Utrecht University
Padualaan 8, 3584CH Utrecht, the Netherlands

http://www.uu.nl/medewerkers/AVangone

Abstract: PRODIGY (PROtein binDIng enerGY prediction) web server predicts of the binding affinities in protein-protein complexes. PRODIGY implements a simple but robust descriptor of binding affinity based only on structural properties of protein-protein complexes, that are introduced in Vangone & Bonvin, eLife (2015). Using the protein-protein binding affinity benchmark of Kastritis et al. 2011 we showed that the number of interfacial contacts (ICs) correlates with the experimental binding affinity. This information, combined with properties of the non-interacting surface (NIS) which have been shown to influence binding affinity (Kastritis at el. (2014)), has led to one of the best performing predictor so far reported on such a large and heterogeneous set of data.

References

Vangone A. and Bonvin A.M.J.J. “Contact-based prediction of binding affinity in protein-protein complexes”eLife, 4, e07454 (2015).

Xue L., Rodrigues J., Kastritis P., Bonvin A.M.J.J.*, Vangone A.*, “PRODIGY: a web-server for predicting the binding affinity in protein-protein complexes”. Bioinformatics, doi:10.1093/bioinformatics/btw514.

Follow up questions

If you have any questions following this webinar, or if you would like to discuss any of the points raised, you can join the discussion at:

http://ask.bioexcel.eu/t/bioexcel-webinar-prodigy-a-web-server-to-predict-binding-affinities-in-protein-protein-complexes/214

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