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Message:

> As shown by an AI program:
> 
> https://www.scientificamerican.com/article/one-of-the-biggest-problems-in-biology-has-finally-been-solved/?utm_source=newsletter&utm_medium=email&utm_campaign=today-in-science&utm_content=link&utm_term=2022-10-31_featured-this-week&spMailingID=72263866&spUserID=NTY2MTUwNzM1NTM4S0&spJobID=2258674929&spReportId=MjI1ODY3NDkyOQS2
> 
> "There’s an age-old adage in biology: structure determines function. In order to understand the function of the myriad proteins that perform vital jobs in a healthy body—or malfunction in a diseased one—scientists have to first determine these proteins’ molecular structure. But this is no easy feat: protein molecules consist of long, twisty chains of up to thousands of amino acids, chemical compounds that can interact with one another in many ways to take on an enormous number of possible three-dimensional shapes. Figuring out a single protein’s structure, or solving the “protein-folding problem, can take years of finicky experiments.
> 
> "But earlier this year an artificial intelligence program called AlphaFold developed by the Google-owned company DeepMind, predicted the 3-D structures of almost every known protein—about 200 million in all.
> 
> ***
> 
> "There are 32 different component algorithms, and each of them is needed. It’s a pretty complicated architecture, and it needed a lot of innovation. That’s why it took so long. It was really important to have all these different inputs from different backgrounds and disciplines. And I think something we do uniquely well at DeepMind is mix that together—not just machine learning and engineering.
> 
> ***
> 
> "One of the things we built in was this understanding of chemical bond angles and also evolutionary history using a process called multisequence alignment. These bring in some constraints, which help to narrow the search space of possible protein structures. The search space is too huge to do by brute force. But obviously, real-world physics solves this somehow because proteins fold up in nanoseconds or milliseconds. Effectively, we’re trying to reverse engineer that process by learning from the output examples. I think AlphaFold has captured something quite deep about the physics and the chemistry of molecules." 
> 
> Comment: the underlying principle is every atom has a charge which dictates its contribution 
> to the folding by the attraction of the different charges. The AI program understand this. So, in thinking about design folding is not much of a design problem. It is the sequence of atoms in the protein that is required to be designed with an anticipated understanding of the desired protein function to be expressed. Not by chance.