Not solved, no. Definitely much much better than before. The difference AlphaFold made is significant: we’re talking about getting a decent model in a couple minutes using a PC compared to several months of calculations before.
However we still need experimental data: in many occasions AlphaFold gives an incorrect model. With some experimental data that model can be improved, but we still have no reliable way to know what the structure of a protein is starting from the amino acidic sequence without extensive experimentation.
That’s the big promise of quantum computers, there are however two major problems in my opinion:
There’s still no theoretical framework which explains how once we have a quantum computer we may tackle protein folding
Plenty quantum computing companies closed shortly after AlphaFold was published since they lost all funding because protein folding was “solved”
Agreed, I still do hope they can maintain some of their promises. However until now, I have not really seen any real advances towards making something useful.
I do not have a deep knowledge of quantum computers, but I know plenty people working on them and often get to talk about it.
I know people working on chemical problems who are basically approximating atoms to point charges. And either way those calculations are slower than on a CPU. For the uninformed, in chemistry the interactions between electronic orbitals is fundamental; this is in no way an approximation useful to obtain any kind of information.
This is fine, I understand methodologies take time to develop; however as far as I understand it those techniques they’re using are mathematically limited to using point charges: no matter how much they improve them that’ll be the highest level of accuracy.
I hope someone finds a way to handle such things better: as much as you can make a great machine learning model you’re always depending on available data.
Not solved, no. Definitely much much better than before. The difference AlphaFold made is significant: we’re talking about getting a decent model in a couple minutes using a PC compared to several months of calculations before.
However we still need experimental data: in many occasions AlphaFold gives an incorrect model. With some experimental data that model can be improved, but we still have no reliable way to know what the structure of a protein is starting from the amino acidic sequence without extensive experimentation.
That’s the big promise of quantum computers, there are however two major problems in my opinion:
90% of quantum computing is a hype scam anyway.
Agreed, I still do hope they can maintain some of their promises. However until now, I have not really seen any real advances towards making something useful.
I do not have a deep knowledge of quantum computers, but I know plenty people working on them and often get to talk about it.
I know people working on chemical problems who are basically approximating atoms to point charges. And either way those calculations are slower than on a CPU. For the uninformed, in chemistry the interactions between electronic orbitals is fundamental; this is in no way an approximation useful to obtain any kind of information.
This is fine, I understand methodologies take time to develop; however as far as I understand it those techniques they’re using are mathematically limited to using point charges: no matter how much they improve them that’ll be the highest level of accuracy.
I hope someone finds a way to handle such things better: as much as you can make a great machine learning model you’re always depending on available data.
Gotcha, thank you ❤️
Didn’t google shut down alphafold recently?