models are effective for protein-ligand structure prediction with equivariant transformers. Our method NeuralPLexer accurately inpaints binding site while using doesn't. https://t.co/Yz1Wi2hTUs

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Packaged our algorithm to design binding peptides into a simple colab. Enter a protein sequence, indicate where you want the peptide to bind, and in a few minutes you'll have a peptide predicted to tightly bind via AlphaFold + Bayesian Optimization. 1/2

https://t.co/MvoXmnUHvK

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AI methods can help scientists analyse data.

Find out how researchers from developed a new method to automatically interpret cryo-EM data using open source software including

https://t.co/gmuPFFkLhT

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ColabFold makes folding with & accessible to everyone. Our MSA server processed >1.6 million requests to date. We thank the community for all the help to improve Colabfold.

Now published
📄 https://t.co/lzN4heMaaX

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A new era for structural biology

"The AI revolution allows us to peer inside something that is not visible to us from the outset"

A. Ramanathan




⏯️Researchers turn to to decode protein structures
https://t.co/o8gmPsbXbq

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ColabFold now uses a faster MMseqs2 backend server. We switched from BFD/Mgnify to ColabFoldDB, a larger metagenomic database, and reduced rate limits a lot, so batch AlphaFold2 runs should be faster.
💻 https://t.co/q4y3N7bxGS

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Finally got round to drawing ‘s proteins folding predictor as a man.

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- Improved per-object clipping
- Quality Assessment score support for AlphaFold & Model Archive files
- Improved surface coloring/transparency
- Drag'n'drop for any support file type (including multi-model zip files)

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A computational biologist called Colby Ford used DeepMind's AlphaFold software to predict the shape of Omicron's spike in November, based on its genome sequence, long before the structure was determined physically. The prediction was extremely accurate

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for protein structure prediction is the breakthrough and a top pick of the year 🎉

Thousands of protein structure predictions powered by 's revolutionary AI are available in the AlphaFoldDB

https://t.co/yV1ebwvnlV

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Interesting... I suspect, by reducing the # of seqs in the MSA, this reduced the strength/certainty of restraints derived from coevolution, allowing AlphaFold to generate multiple hypotheses (conformations) with randomseed, model param, or msa pertubations https://t.co/3JPM8Ysgox

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ColabFold now uses the AlphaFold-multimer models paired with MMseqs2 searches for prediction of protein complexes. Just provide chains separated by : and press "Run all" (provide the same sequence multiple times for homooligmers). Check it out at https://t.co/q4y3N7bxGS

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Recording of 'FEBS Junior Sections – AlphaFold Database webinar' by team leaders - Gerard Kleywegt and Sameer Velankar is now available. Find it here https://t.co/2yCepK5YsD

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The source code has been updated and now accounts for multi-chain protein complexes - providing a significant improvement in accuracy for predicting protein interactions: https://t.co/4gyZ0loLrd

Generate predictions from your browser via: https://t.co/2Vd4itjElu

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A paper on "AlphaFold-multimer", a version of AlphaFold that works on protein complexes, was released by .

Accurately predicted structures can lead to better understand the function of such protein complexes that underpin many biological processes!

1/4

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Our structural aligner Foldseek can now automatically download databases in a single command. We provide the PDB (#PDB50) and Alphafold DB. You can download Foldseek here: https://t.co/HVRSi3ycX3

foldseek databases PDB pdb tmp
foldseek easy-search query.pdb pdb aln.m8 tmp

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Many single protein chains can be accurately predicted using AlphaFold, but multi-chain protein complexes remain challenging. Introducing AlphaFold-Multimer, a model that can predict the structure of multi-chain protein complexes with increased accuracy https://t.co/KMyN87wgDE 1/

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Spot the difference: can you find all 49359 differences between these two galleries?
It takes only seconds to model glycans with GlycoSHIELD https://t.co/U87xBZMGiF.
It is indeed

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Glad to see this out! Minor contribution from my side. We tested to see how well AlphaFold can predict homo-oligomers and their oligomeric state. Here I'm plotting the min(pTMscore) across 5 models, splitting success (top row) and failures (bottom row). https://t.co/fhdMtC3f4L

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A method, AlphaFold2, "predicts protein structures with near-experimental accuracy."

I read again with pleasure about this breakthrough!





⏯️Protein-structure prediction revolutionized
1-https://t.co/4r1fmqRXRc
2-https://t.co/LKXDQpJOGf

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