It’s been five years since AlphaFold 2 started to change how we see the biological universe. 🔬 From the solution of a 50-year-old protein folding challenge to winning the 2024 Nobel Prize in Chemistry, the #AlphaFold breakthrough has been a journey of discovery. But the real impact lies in how the tool is being used today – helping over 3 million researchers accelerate their work. Here’s some of the ways the scientific community is making a difference: 🫀Fighting heart disease: Researchers revealed the structure of a key protein linked to “bad cholesterol,” providing a blueprint for new preventative therapies. 🐝Saving bees: Conservationists are using AlphaFold to understand honeybee immune systems, helping protect endangered populations. 💊Accelerating drug design: Alongside Isomorphic Labs, we introduced AlphaFold 3 to help speed up the creation of potential new medicines. Find out more about the breakthrough and its impact 5 years on → https://goo.gle/48huV38
Wild to think that AlphaFold didn’t just solve structures, it proved how much clarity you gain when truth is engineered at the origin. When the foundation is right, everything built on top accelerates. Huge respect for this work.
Remarkable milestone. In my opinion, AlphaFold has become one of the clearest examples of AI reshaping science at scale. I think solving protein folding unlocked not just a Nobel-worthy breakthrough, but a platform that now accelerates drug design, conservation, and preventative medicine for millions of researchers. Exciting to see how AlphaFold 3 continues to expand the frontier of digital biology.
It's incredible to see how AlphaFold revolutionized basic science. I’m eagerly waiting for DeepMind to expand this paradigm into the engineering realm. Predicting and optimizing extreme acoustic structures for Smartphones and XR devices shares complex topological challenges with protein folding. Looking forward to an 'AlphaFold for Engineering' that solves these physical constraints!
Your perspective shines connect today? Such inspiring progress! Seeing how AlphaFold is truly transforming diverse fields is incredible. What’s next for AI in advancing biomedical research?
This is exactly why I'm passionate about AI seeing tools like AlphaFold accelerate everything from drug design to conservation work. The breadth of applications here (heart disease, bees, medicine) shows how one breakthrough can unlock solutions across completely different fields. Inspiring work!
I've been astonished and inspired by Alpha fold since my student years when I was studying Biology and Neuroscience. Even more inspired by all the achievement over these five years, and excited to see what else this technology can unlock for us in healthcare, life sciences and preserving nature.
There is a difference between a real scientific breakthrough and improved protein homology models based on statistics. The impact of AlphaFold in drug discovery has still to be demonstrated.
AlphaFold didn’t just transform biology — it demonstrated what happens when an AI system crosses the threshold from pattern recognition to genuine scientific reasoning. What’s even more striking is how its impact keeps expanding as researchers use it to solve problems far beyond its original scope. It’s one of the clearest signals we have that specialized breakthroughs can become stepping stones toward more general forms of intelligence. The last five years have redefined what AI can contribute to science. The next five may redefine what AI can become.
AlphaFold didnt just solve a scientific puzzle it quietly rewired the future of biology. The bigger question now is whether our institutions are ready for breakthroughs that move faster than policy safety frameworks and even our imagination.
AlphaFold didn’t just crack a 50-year puzzle, it quietly rewired the math of R&D. When “impossible-to-measure” structure becomes a routine input, whole categories of heart disease, pollinator collapse, and drug discovery move from “too hard” to “now or never.” Huge respect to the teams and the 3M+ researchers building on this; feels like we’re still underestimating how much this will change what biotech companies, labs, and regulators even dare to attempt.