Alpha Fold was promised as a “revolutionary AI paradigm” to predict protein folding. In a fascinating rebuttal published on Chemistry World, this is worth your time to understand the nuances and avoid the hype.
Why AlphaFold won’t revolutionise drug discovery | Opinion | Chemistry World
Instead, we have thousands and thousands of new protein structure predictions, well before we might have expected them. And they really do seem to be mostly correct, albeit with some exceptions. Some of the structures are more solidly determined than others, but then some proteins are intrinsically more determined than others. AlphaFold’s algorithms are at a loss when confronted by disordered protein regions, as well they might be: when your entire computational technique is built on finding analogies to known structures, what can you do when there’s no structure to compare to and never will be? Some disordered proteins snap into orderly arrangement in the presence of their various protein partners, but others never show ordered structures under any conditions. What’s more, that property seems to be essential to their function! Some protein behaviour is simply beyond structure, and thus beyond AlphaFold’s ability to help.
My concern is the eventual “progress” in cancer genomics. It will require invasive monitoring and deep recesses to understand its impact on outcomes. I am also worried about the positive spin in mainstream journals and increased complexity/costs of healthcare. I don’t foresee much utility in clinical practice, yet.
RadOncNotes 