Reply to post: Re: It's good somebody's doing this

DeepMind quits playing games with AI, ups the protein stakes with machine-learning code

Anonymous Coward
Anonymous Coward

Re: It's good somebody's doing this

I'd be very interested in some more detailed analysis of how the approaches compare,

They both suck. I am speaking this as someone who has done both Mol Biol (though mostly DNA), some AI and has a chemistry degree which has a very heavy theoretical physics slant.

Our knowledge of what is going in a solution which contains all kinds of "stuff" leaves a LOT to be desired. Our knowledge of _EXACT_ structures of some proteins as generated by crystallography is _NOT_ for their natural configurations in solution. To add insult to injury for a real protein in eukaryotes it is not 20 aminoacids. It is 20 aminoacids + a lot of glycoside tails attached in various places. Without those it does not fold correctly and this is one of the reasons why are not producing a lot of stuff in bacteria at present. While we can program bacteria to synthesize a particular protein, it ends up "wrong" due to lack of glycosilation. Where and what are those tails is in the realm of black voodoo - we can read the aminosequence from the DNA (that is what is usually done), but we often have only guesses on where the glycoside tails are because the chemical methods for their analysis are fairly imprecise.

Both approaches produce approximations.

IMO the truth is somewhere in-between. Most approaches which model using a model of forces and molecular interactions have a ridiculous time for initial convergence. It takes them ages to get a point where they are actually working on something resembling the actual structure. Compared to that the AI cruises through this phase - it is not much different from a game for it (in fact, training is similar). Once it is done with this phase it does not know what to do. No training can replace a molecular forces model. That is the fundamental reason for the low accuracy.

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