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

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http://vietmoz.com/?syrcis=trading-on-line-forex trading on line forex The 7th webinar in BioExcel’s webinar series on computational methods and applications for biomolecular research took place on Wednesday 12th October.

http://mksplumbing.com.au/?sese=le-vincite-che-vengono-fatte-sulle-opzioni-binarie-sono-tassate&ded=f8 le vincite che vengono fatte sulle opzioni binarie sono tassate Anna Vangone introduced PRODIGY, a web server to predict binding affinities in protein-protein complexes.

buy Finpecia 1mg india Discuss this webinar View slides on SlideShare  Join Interest Group

buy tastylia online 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.

generic maxalt fedex 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://maxbaillie.com/wp-cron.php?doing_wp_cron=1468965424.4381299018859863281250 vincite con opzioni binarie anna-vangoneAnna Vangone

Bijvoet Center for Biomolecular Research
Science Faculty/Chemistry, Utrecht University
Padualaan 8, 3584CH Utrecht, the Netherlands


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.


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.

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