Non-canonical amino acids can expand the scope of proteins available for therapeutics and machine learning platforms can ...

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 ...

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 ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational model that could expedite the use of nanomaterials in biomedical applications.

The small size of nanoparticles is associated with several unique properties that mediate a profound impact on the development of many technological fields, including medicine. The nanoparticles in ...

Their overview highlights innovative methods based on B-factor analysis, ancestral sequence reconstruction (ASR), and machine learning (ML), providing tools to design enzymes that withstand high ...

Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design ...

It has long been thought that protein function and stability are highly sensitive to changes in the composition of the internal structures, or protein cores. However, a large-scale experiment probing ...

Proteins are life's molecular workhorses, doing everything from turning sunlight into food to fighting viruses. They are built from 20 different types of amino acid molecules, so even a small protein ...