Advances in structural biology have allowed scientists to determine molecular structures with atomic-level detail, sometimes yielding static snapshots that do not reflect the dynamism of proteins.

Drug designers working on protein-level chemistry have long been blocked by a hard computational wall: classical supercomputers cannot fully model the electronic structure of large biomolecules.

A newly developed generative AI model is helping researchers explore protein dynamics with increased speed. The deep learning system, called BioEmu, predicts the full range of conformations a protein ...

The targeted engineering of artificial proteins with unique properties is now possible with the assistance of a novel method developed by a research team led by Prof. Dr. Dominik Niopek at the ...

Researchers from the Massachusetts Institute of Technology (MIT) Jameel Clinic for Machine Learning in Health have announced the open-source release of Boltz-2, which now predicts molecular binding ...

Researchers present BioEmu – a new AI model that rapidly and accurately predicts the full range of shapes a protein can adopt, offering a faster, cheaper alternative to traditional molecular ...

Researchers at IBM, the Cleveland Clinic, and Japan’s RIKEN research institute have used quantum computers in conjunction with two of the world’s most powerful supercomputers to simulate a protein ...

University of Maine researchers have published new findings about how muscles form, why certain muscle diseases develop and ...

For many of us, a warm cup of coffee is how we start our day. For Texas A&M Health researchers, it may also offer a new way ...

Professor Jonathan Wittenberg used this model of sperm whale myoglobin structure as a teaching tool at the Albert Einstein College of Medicine at Yeshiva University in the Bronx. It was used beginning ...