“To understand life,” says The Economist, “you must understand proteins. These molecular chains, each assembled from a menu of twenty types of amino acids, do biology’s heavy lifting. In the guise of enzymes, they catalyze the chemistry that keeps bodies running. Actin and Myosin, the proteins of muscles, permit those bodies to move around. Keratin provides their skin and hair. Haemoglobin carries their oxygen. Insulin regulates their metabolism. And a protein called spike allows coronaviruses to invade human cells, thereby shutting down entire economies.” Proteins are the origin of existence; the tail of a human sperm is a structure composed of many types of proteins that work together to form a complex rotary engine that propels the sperm forward to fertilize an egg, and to create life.

It is not surprising therefore, that the breakthrough that made me a convert to the religion of AI, had to do with proteins. AlphaFold by Google DeepMind cracked one of the hardest problems in medical science – predicting how a protein would fold. Every carbon-based life form is made of proteins, and it is how they fold that decides almost everything about our physiology and life. There are over 200 million known proteins today, and each of them folds in a unique three-dimensional shape. It was impossible for scientists to study each one of them, which considerably hindered efforts to tackle disease. If proteins fold wrongly, for instance, they can cause horrific harm; the accumulation of misshapen proteins is said to cause Alzheimer’s, Parkinson’s, Huntington’s, and Lou Gehrig’s (ALS) disease. Wrong folds also cause cystic fibrosis and sickle cell anaemia, and thousands of diseases we do not know yet. DeepMind built on an existing product AlphaGo (the same one that had famously defeated world champion Lee Sedol in the complex game of Go) on the sequences and structures of a hundred thousand proteins, and in four years brought it to a level where it can predict the folded shape of a protein, right down to the molecular level. In 2020, the problem was declared solved; a breakthrough as important as mapping the human genome, or the discovery of antibiotics, something that can change medical science forever. As a scientist remarked, “What took us months and years to do, AlphaFold was able to do in a weekend.”

AlphaFold is built on deep learning and neural networks, technologies that shaped AI. Now the next powerful AI technology, LLMs and Generative AI, is doing even more magical stuff. GenAI based image generators like DallE, Midjourney and now Sora and GPT4o have taken the world by storm, with innocent word prompts creating wondrous images and breathtaking videos out of thin air. Researchers are using the same technologies to generate blueprints for new proteins, ones that nature has not been able to produce yet. These new proteins could revolutionise our ability to battle diseases that our body has not be able to do naturally. David Baker of the University of Washington has been building artisanal proteins for years, (https://bit.ly/3V8ie3U ), but with this new technology he can design new more sophisticated protein molecules with a higher success rate, shrinking the timeframe from “years to weeks”. As an example, GenAI can be used to create proteins of a uniquely distinctive shapes, such as the spike protein of the Covid virus. “What we need are new proteins that can solve modern-day problems, like cancer and viral pandemics,” says Dr Baker. “We can’t wait for evolution.” The amazing part is that this can happen through the right kind of text prompts to begin with, the same way prompt engineers use complex prompts skilfully to do organisational tasks. As former Stanford researcher Namrata Anand tells Cade Metz of the NYT (https://bit.ly/3V8ie3U) : “…protein engineers can ask for a protein that binds to another in a particular way — or some other design constraint — and the generative model can build it.”

AI’s astonishing innovation in biology and genetics has just begun. A California company Profluent released a research (https://bit.ly/454t4wy ) where GenAI technologies can build new gene editors to edit human DNA, using a Nobel prize winning technology called CRISPR (I had written about it here: https://bit.ly/3V45WcW ). Profluent’s technology learns from how nature creates cellular structures and create entirely new ones on its own. This would be another weapon doctors and scientists would have to create new medicines and highly personalised treatments. It does not stop here: DeepMind just released AlphaFold 3, which goes beyond proteins and peers into biochemical networks that make cells and organisms functions. This astonishing marriage of AI and molecular biology has started having demonstrable effects. The Financial Times quotes an BCG study that indicates that drugs discovered by Ai have a higher early-stage trials success rates than by usual methods ( https://bit.ly/3yDhT1w )

For a lot of us today, AI is a gee-whiz experience of creating stunning videos, travel itineraries and food recipes. But its real benefits to humankind will be deeper and more fundamental, and nowhere more in helping humans transcend our biology.