Open-Sourcing of Protein-Structure Software is Already Paying Off

upstart writes:

Open-sourcing of protein-structure software is already paying off:

It is now relatively trivial to determine the order of amino acids in a protein. Figuring out how that order translates to a complicated three-dimensional structure that performs a specific function, however, is extremely challenging. But after decades of slow progress, Google's DeepMind AI group announced that it has made tremendous strides toward solving the problem. In July, the system, called AlphaFold, was made open source. At the same time, a group of academic researchers released its own protein-folding software, called RoseTTAFold, built in part using ideas derived from DeepMind's work.

How effective are these tools? Even if they aren't as good as some of the statistics suggested, it's clear they're far better than anything we've ever had. So how will scientists use them?

We got a partial answer this week, as a large research collaboration set the software loose on a related problem: how these individual three-dimensional structures come together to form the large, multi-protein complexes that perform some of the most important functions in biology.

Many individual proteins work just fine on their own, but some aspects of biology require the careful coordination of multiple chemical changes performed as a series of ordered, sequential steps. And for those processes, it's often easiest for the proteins that need to coordinate to be part of a single complex. For example, the complex that makes copies of our chromosomes typically consists of more than a dozen proteins. Photosystem I, part of plants' photosynthetic process, is similar in scale. The ribosome, which translates the information in messenger RNAs into the amino acid sequence of proteins, can require over 75 proteins in some species.

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