Google DeepMind has published the source code and parameters of AlphaFold 3 models for academic use. This can accelerate scientific discoveries and drug development. This is reported by VentureBeat.

AlphaFold 3 has made a huge leap forward from its predecessors. While AlphaFold 2 could predict the structure of proteins, version 3 can now model complex interactions between proteins, DNA, RNA, and small molecules.

This is important because understanding these molecular interactions is at the heart of the development of modern medicines and disease treatment. Traditional methods of studying these interactions often require months of laboratory work and millions of dollars in research costs-with no guarantee of success.

The release of AlphaFold 3 revealed tensions in modern science. In May 2024, DeepMind decided not to publish the code but to provide access through a web interface, which drew criticism from researchers. This issue has raised an important dilemma: how to balance open science and commercial interests when companies like DeepMind Isomorphic Labs are working on medicines using these technologies.

The open source release offers a middle way. While the code is freely available under a Creative Commons license, access to important model weights requires Google’s permission for academic use. This approach tries to meet both academic and commercial needs.

Of course, problems remain. The system sometimes creates irregular structures in disordered regions and can only predict static structures, not molecular motion. These limitations show that while AI tools such as AlphaFold 3 are advancing the field, they work best when used in conjunction with traditional experimental methods.

The release of AlphaFold 3 is an important step forward in artificial intelligence-based science. Its impact will go beyond drug development and molecular biology. When researchers use this tool to solve various problems – from creating enzymes to breeding resistant crops – we will see new areas of computational biology application.

The true test of AlphaFold 3 is yet to come – its practical impact on scientific discovery and human health. As researchers around the world begin to use this tool, we may see faster progress in understanding and treating disease than ever before.

By the way, the creators of the AlphaFold model, Demis Hassabis and John Jumper, received the Nobel Prize in Chemistry in 2024 for their work on protein structure prediction.