Reacting to Alphafold 2.0

Has protein folding actually been solved?

UPDATE 12/22/2020: Once again, I’d be doing a disservice if I didn’t provide a link to Zach Weiner’s take. This might seem like hyperbole now, but most people that have at a minimum dipped their toes into synthetic biology would agree that the goal is to have enough control for these kinds of petty use-cases.

Explanation of Alphafold-2

While the paper hasn’t been fully released yet, that hasn’t stopped some people from trying their hand at reproducing the algorithm from scratch (such as this repo originally reconstrucing the first Alphafold version)

My takeaway from this is that we have a general solution to folding problems, but not quite a universal one yet. I agree that it’s amazing we can get these results without a quantum computer (I used to think that was a hard-to-get-around prerequisite), but I believe there’s a lot more to go in areas like quaternary protein structures, protein ligand combos, 4D protein structures (such as for the binding sites on viruses), and stable vs. meta-stable proteins (sorely needed in p53 models, prion research, and understanding Alzheimer’s better).

Deepmind still hasn’t solved 4D protein folding yet

Many viruses (most notably bacteriophages) have ligands that change shape when the virus adheres to a cell. This means that after connecting with one


Cited as:

@article{mcateer2020alphafold2,
    title = "How to Train your Energy model",
    author = "McAteer, Matthew",
    journal = "matthewmcateer.me",
    year = "2020",
    url = "https://matthewmcateer.me/blog/reacting-to-alphafold-2/"
}

If you notice mistakes and errors in this post, don’t hesitate to contact me at [contact at matthewmcateer dot me] and I will be very happy to correct them right away! Alternatily, you can follow me on Twitter and reach out to me there.

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