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The AlphaFold project of DeepMind (Google) made a dramatic breakthrough in 2020. AlphaFold is often able to predict the structure of a protein from its sequence so well that the difference between the prediction and an X-ray crystallographic structure is as small as the difference between two independent X-ray determinations.
Now, thanks to ColabFold, anyone can submit a sequence and get a free AlphaFold2 structure prediction. Its easy! Here are instructions:
https://proteopedia.org/w/How_to_predict_structures_with_AlphaFold
Reliability is estimated for each amino acid. FirstGlance in Jmol now automatically colors AlphaFold/ColabFold predictions by estimated reliability. Upload your predicted PDB file to
http://bioinformatics.org/firstglance/fgij
Snapshot of Alphafold2 Colab prediction displayed in FirstGlance colored by estimated reliability per residue: https://bioinformatics.org/molvis/images/firstglance-with-alphafold.png
Examples of AlphaFold2 Colab predictions ready to view instantly in FirstGlance: https://bioinformatics.org/firstglance/fgij/versions.htm- ColabFold - Making protein folding accessible to all by M. Mirdita, S. Ovchinnikov, & M. Steinegger: https://www.biorxiv.org/content/10.1101/2021.08.15.456425v1
- More about AlphaFold: https://proteopedia.org/w/Alphafold
- About the 2020 CASP blind competition: https://proteopedia.org/w/Theoretical_models
- AlphaFold Database of several hundred thousand predictions: https://alphafold.ebi.ac.uk
- Official Deepmind AlphaFold blog post: https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology
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