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 ...

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 ...

On Wednesday, the Nobel Committee announced that it had awarded the Nobel Prize in chemistry to researchers who pioneered major breakthroughs in computational chemistry. These include two researchers ...

Fully open source model accurately predicts the 3D structures of proteins and biomolecules in silico, and serves as a foundational model for next generation of cutting-edge Protein AI tools The ...

A research group led by Gian Gaetano Tartaglia, Principal Investigator at the Italian Institute of Technology (IIT), developed a machine-learning algorithm to study the behavior of proteins within ...

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.

This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying computational ...

A machine-learning algorithm to study the behavior of proteins within cells and to predict their ability to trigger neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS), Parkinson's, ...