Discover and read the best of Twitter Threads about #proteindesign
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Roughly one year ago we started out venturing in the world of #proteindesign. Today I am very happy to share our first preprint ‘Efficient and scaleable de-novo protein design using a relaxed sequence space’ (biorxiv.org/content/10.110…) with @sokrypton & @hendrik_dietz 1/x
Here we propose and experimentally verify a new way to design protein backbones. We use a relaxed sequence representation allowing the free following of gradients during hallucination. This enables a very efficient search for backbones that minimize the loss function. 2/x 
By using ProteinMPNN we can create sequences for this backbones and our approach achieves SOTA backbone recovery both for ESM-Fold and AF2 single sequence, with median sub 4 A accuracy for 600AA proteins. Standing in line with recently published diffusion models! 3/x
Today's an exciting day!
After many years of work, we're thrilled to report our latest advance in citizen science: nature.com/articles/s4158…
@Foldit @UWBiochemistry @uwcse @RutgersU @dartmouth @Northeastern @HHMINEWS #citizenscience #proteindesign @nature
After many years of work, we're thrilled to report our latest advance in citizen science: nature.com/articles/s4158…
@Foldit @UWBiochemistry @uwcse @RutgersU @dartmouth @Northeastern @HHMINEWS #citizenscience #proteindesign @nature
Online citizen science projects have largely harnessed human pattern-recognition skills rather than human creativity. We wanted to go much further.
We posed the challenge of de novo protein design in the online protein-folding game @Foldit.
We posed the challenge of de novo protein design in the online protein-folding game @Foldit.
After many iterations of player design, analysis of the top-scoring solutions and subsequent game improvement, Foldit players can now—starting from an extended polypeptide chain—generate a diversity of protein structures and sequences that encode them in silico.
