Our bodies are capable of producing 20,000 proteins, which are used to move oxygen through the bloodstream. Researchers are trying to improve our ability to fight disease and do things that our bodies can't do on their own by creating a new type of proteins.

David Baker is the director of the Institute forProtein Design at the University of Washington. He and his team showed this was doable. They didn't know how the rise of new A.I. technologies would speed this work up.

Dr. Baker said that new proteins that can solve modern-day problems are needed. We can't wait for the future. He said, "Now, we can design theseProteins much faster, and with higher success rates, and create more sophisticated Molecules that can help solve these problems."

ImageDavid Baker stands in his lab, holding a white and blue model of a protein. Behind him are shelves stacked with bottles and boxes.
David Baker of the University of Washington.Credit...Evan McGlinn for The New York Times

Several A.I. techniques were described in a pair of papers last year. The newer paper draws on the techniques that drive tools like DALL-E to show how new genes can be created from scratch.

One of the most powerful things about this technology is that it is able to do what you tell it to do. It can be generated from a single prompt.

Artificial intelligence researchers call a neural network a mathematical system that is modeled on the network of brain cells. This technology is similar to the one that allows self-driving cars to identify pedestrians and translate languages.

A neural network learns how to analyze data. It can learn to recognize corgis by studying thousands of corgi photos. Researchers built a neural network that looked for patterns when analyzing millions of digital images and the text caption that described them. It was able to recognize the links between the images and words.

Key features are generated by a neural network when you describe an image for DALL-E. There is a curve in a teddy bear's ear. There is a line at the edge of a skateboard A second neural network called a diffusion model is used to create the features.

The model is trained on a series of images in which noise is added to a photograph until it becomes a sea of randomness. The model learns to run this process in reverse after analyzing the images. A coherent image can be created when the noise is removed by feeding it randompixels.

At the University of Washington, other academic labs and new start-ups are using the same techniques.

There are strings of chemical compounds that are twisted and folded into three-dimensional shapes. In recent years, artificial intelligence labs like DeepMind, owned by the same parent company as Google, have shown that neural networks can accurately guess the three-dimensional shape of any proteins in the body based just on the small compounds it contains.

These systems are being used by researchers like Dr. Baker to create blueprints for new proteins that are not found in nature. The goal is to create proteins that take on specific shapes and serve a specific purpose, such as fighting the Covid virus.

Similar systems can leverage the relationship between a description of what theProtein can do and the shape it adopts. A model can be used to create a three-dimensional shape.

A protein diffusion model doing unconditional generation, converting noise into plausible structures. Video by Namrata Anand
Namrata Anand, a former Stanford University researcher. She is now building a company in generative A.I. protein design.Credit...Herve Philippe/TerrificShot Photography

With DALL-E, you can ask for an image of a panda eating a shoot of bamboo. The generative model can build it if the engineers want it to bind to another molecule in a specific way.

A DALL-E image can be instantly judged by the human eye. It can't do the same with a structure that's made of a specific type of cells. Scientists need to make sure they do what they're supposed to do after artificial intelligence technologies produce the blueprints.

Artificial intelligence technologies should be taken with a grain of salt according to some experts. Making a new structure is nothing more than a game according to a professor at the California Institute of Technology. What can that structure do that is important?

New techniques are helping researchers create new candidates for the wet lab. Researchers can explore new innovations on their own, but they can't do that with them.

Jue Wang, a researcher at the University of Washington, said that they are creative while satisfying certain design objectives. It saves you from having to check every single one.

Artificially intelligent machines can perform skills that come naturally to humans, like playing a board game. Dr. Wang asked what machines can do that humans can't.