A lot of the AI work in biology has been focused on designing proteins. That’s partly because proteins do most of the business of life, catalyzing the interesting chemistry and structuring cells. So, figuring out how to make a new protein can mean directly tinkering with biochemistry, providing new and potentially useful functions.
Since the genetic code provides a layer of abstraction between DNA and proteins, it wasn’t obvious what a model trained on DNA could do. Yet people went ahead and made a large genome model, and it turned out to be able to output DNA sequences that could encode functional proteins in bacteria and mimic the gene structures found in complex cells. Now, those same models have been used to output the genomes of viruses that infect bacteria.
This isn’t science fiction—all the viruses the models created are closely related to an existing virus. But they do have some distinct features that would be challenging to evolve. And the researchers who did the work, based at Stanford University, suggest we may want to start thinking now about preparing for the potential that someone could develop a related AI that can design a virus that targets vertebrates.
Large genome models #
Large language models are essentially trained on their ability to predict the next bit of verbiage in as large a compendium of human-generated text as their developers can get ahold of. Large genome models are the same approach, but applied to DNA. To an extent, that simplifies matters, given that DNA only uses four “letters,” A, T, C, and G. But it’s more complicated in that genomes typically have areas where the next letter matters a great deal, interspersed with sequences where the next base could be anything and it wouldn’t matter.
So large genome models need to recognize the biological context of the sequence they’re outputting in many situations where we humans haven’t figured it out yet. Yet, if we feed them enough genome sequences, they seem to be able to. Bacterial genes with related functions tend to cluster together. Prompt a large genome model with the sequence of part of a cluster, and it’ll output DNA sequences that encode proteins with related functions—potentially including working proteins that look like nothing else we’ve identified so far.