A recent preprint from @Lauren_L_Porter shows that it's sometimes possible to sample the alternative conformation of metamorphic proteins by removing the MSA. Though I think this is a very interesting observation, I disagree that coevolution is not used when it is provided. (1/9) We believe AlphaFold has learned some approximation of an "energy function" and a limited ability to explore. But this is often not enough to find the correct conformation, and often an MSA is required to reduce the search space. (2/9)

Puzzle: The residue index encodes the position embedding for models like AlphaFold. This residue index is converted into an offset matrix. (1/3) What do you think will happen if this offset matrix is used instead? [answer will be posted later] (2/3)

AlphaFold inverted to hallucinate denovo proteins of up to 600 amino acids in length🤯

(animation below shows the designed protein docked into CryoEM density)

Exciting work with:
@chrisfrank662, @AKhoshouei, Yosta de Stigter, Dominik Schiewitz, @ShihaoFeng18, @hendrik_dietz

https://twitter.com/hendrik_dietz/status/1629749217399808001

We've been working on adding AlphaFold v2.3.1 support to ColabFold. 😎 Here is the notebook for those interested in testing: colab.research.google.com/github/sokrypt… (1/5) The major update is AlphaFold_multimer_v3. This is an updated multimer model from @DeepMind. Initial tests from @milot_mirdita show an improvement over v2. Though, it's unclear whether improvements are due to new params or protocol (run for more recycles, with early stop). (2/5)

Some exciting results from CASP15! (1/6)

https://twitter.com/MartinPacesa/status/1601511762356228096

Though Zscores can be a little misleading. If everyone is the same on average, and one group does really well on a particular target compared to everyone else, they HUGE boost. Here are the same data (same order, but plotting average GDT_TS). (2/6)

inspired by some of our work on AF2Rank (showing AF can be used to denoise template inputs) and RFdiffusion, I tried hacking AlphaFold to be a diffusion model for generating backbones. 😎 Only 15 lines of code to implement in ColabDesign 🤓
colab.research.google.com/github/sokrypt…

Job-application-procrastination-project:
ProteinMPNN in jax! 😅

GPU=A6000, length=2382, seqs=32
pytorch=3m22s
jax=17.9s
jax=4.46s (vmap)

length=100, seqs=5000
jax=2s

Special thanks to Shihao Feng, @JustasDauparas and @sim0nsays

colab.research.google.com/github/sokrypt…

(1/3) With 10 lines of code you can now design sequences with ProteinMPNN and "evaluate" them with AlphaFold/AF2Rank ( from @jamesproney )
github.com/sokrypton/Cola…
(2/3)

Found an example from @Alexis_Verger that OmegaFold fails on (and has low confidence). But if you hack OmegaFold to use an MSA input, it gets it right (and has high confidence)!

https://twitter.com/Alexis_Verger/status/1555134615328899072

@Alexis_Verger

Seems to be working 😅
Now to test the limits on Colab!
colab.research.google.com/github/sokrypt…

https://twitter.com/peng_illinois/status/1554831291794657282

In the spirit of hacking methods for what they were not trained to do. I added support for chain breaks using the residue index offset trick! 😇

We've (including @thesteinegger @milot_mirdita ) updated ColabFold to use the latest optimized AlphaFold implementation that reduces compile time from ~4.5mins to ~30 seconds! We've confirmed the results are identical for both monomer and multimer predictions. Try it out! (1/2) Here is the Pseudo-code of the changes we made and the effects on compile time. (2/2)

For my latest attempt at introducing proteins to students, I made a Google Colab Notebook that predicts proteins from a single sequence. I asked the students to tweak the sequence to get a helix or two helices or... (1/5)
colab.research.google.com/github/sokrypt… I gave them the following cheat sheet: 😅 (2/5)

End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman
biorxiv.org/content/10.110…
A fun collaboration with Samantha Petti, Nicholas Bhattacharya, @proteinrosh, @JustasDauparas, @countablyfinite, @keitokiddo, @srush_nlp & @pkoo562 (1/8) Many methods like GREMLIN, MSA_transformer, RosetTTAFold and AlphaFold rely on input MSA generated by non-differentiable methods. (2/8)