The intrinsically disordered proteins (IDPs) do not attain a stable secondary or tertiary structure and rapidly change their conformation, making structure prediction particularly challenging. These ...

With MassiveFold, scientists have unlocked AlphaFold's full potential, making high-confidence protein predictions faster and more accessible, fueling breakthroughs in biology and drug discovery. Brief ...

Jia’s team developed a protocol to improve the screening of protein pockets. This involved identifying the pockets, removing ...

AlphaFold arrived as a technical moonshot that suddenly made protein structures feel like software rather than secrets of nature, and five years on it has rewired how laboratories plan experiments, ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

Neo-1 is the first model to unify de novo molecular generation and atomic-level structure prediction in a single model, by generating latent representations of whole molecules instead of predicting ...

In 2020, news headlines repeated John Moult’s words at the end of a stunning competition: Artificial intelligence had “solved” a long-standing grand challenge in biology, protein structure prediction.

Google DeepMind’s work with AlphaFold has been nothing short of a miracle, but it is computationally expensive. With that in mind, Apple researchers set off to develop an alternative method to use AI ...

Artificial intelligence (AI) is reshaping the scientific landscape, offering fantastic solutions to some of the most pressing global challenges. From combating climate change to transforming ...

The 2024 Nobel Prize in Chemistry recognized Dr. David Baker for his pioneering work in computational protein design, along with Drs. Demis Hassabis and John Jumper for their contributions to protein ...