The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

Fusion oncoproteins arise when a gene fuses with another gene and acquires new abilities. Such abilities can include the formation of biomolecular condensates, "droplets" of concentrated proteins, DNA ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the scientific journal ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin introduces a breakthrough in protein simulation. The study, published in the ...

Industrial yeasts are a powerhouse of protein production, used to manufacture vaccines, biopharmaceuticals, and other useful compounds.

CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...

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, ...