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(Tue, 03/03/2020 - 23:02  |  3 comments)

Foldit Lab Report #6: Coronavirus puzzle

Check out Foldit Lab Report #6 on YouTube now!

We've got a bunch of new puzzles this month — and some exciting tools coming soon!

NEWS
• Looking at electron density in Foldit is about to get a whooole lot easier (0:31)
• With the new BUNS tool, your solutions should be better behaved in the lab (2:18)

PUZZLE UPDATES
• More poly-proline helix design (3:50)
• CRISPR/Cas transposase (4:02)
• Aflatoxin prediction (4:28)
• Coronavirus spike-binder design (5:20)
• Return of sketchbooks — this time symmetric (6:10)

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(Sun, 03/01/2020 - 17:09  |  4 comments)

New coronavirus puzzle!

The Baker Lab is trying to design proteins that could be used as antiviral agents against the 2019 coronavirus! Check out Puzzle 1805b and design a protein that can bind the coronavirus spike protein!

(Fri, 02/28/2020 - 20:37  |  2 comments)

Foldit Lab Report #5: New software dev

Check out Foldit Lab Report #5 on YouTube now!

NEWS
- This month we welcome Henry! (aka milkshake)
- Check the Foldit blog for an update on DeepMind's AlphaFold

PUZZLE UPDATES
- New poly-proline helix tools are on the way
- Introducing a CRISPR puzzle
- Ever more symmetric designs
- Can you make the next top TIM?

DESIGN OF THE MONTH
- silent gene created another great symmetric design

(Sat, 02/01/2020 - 20:31  |  5 comments)

New AlphaFold blog post!

Check out the blog for a look at AlphaFold, a new method for protein structure prediction!

AlphaFold, which was developed by DeepMind in 2018, uses a sophisticated machine-learning algorithm to derive structural information from a protein's sequence. In the last CASP competition, it out-performed every other method for protein structure prediction! In this latest blog post, we take a look at the AlphaFold method and its impact on protein research!

(Fri, 01/31/2020 - 00:57  |  3 comments)
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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons