A major scientific advance in protein modeling developed by Microsoft Research AI for Science, has been published in Science.

The SAIR database is designed to help scientists train AI models to better predict protein-ligand binding affinities for drug discovery.

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 final atomic model rationalizes over four decades of biochemical data on the ribosome, and provides a wealth of information about RNA and protein structure, protein–RNA interactions and ...

Molecules from the 20-million-year-old teeth of a rhino relative are among the oldest ever sequenced, opening tantalizing ...

Achieving good oral bioavailability for targeted protein degraders (TPDs) is vital in providing a patient-friendly way to ...

In biology textbooks and beyond, the human genome and DNA therein typically are taught in only one dimension. While it can be ...

A major scientific advance in protein modeling, developed by Microsoft Research AI for Science, has been published in the July 10 issue of Science.

Here we use cryogenic electron microscopy to determine the structure of TbAQP2 from Trypanosoma brucei, bound to either the substrate glycerol or to the sleeping sickness drugs, pentamidine or ...

Explore how the ratio of pd-1+ treg to ctl and the presence of tertiary lymphoid structures can influence treatment outcomes ...

The molecular data provided by the two papers is potentially ... adding that the dense crystalline structure of dental calculus may help prevent the host DNA from being lost. The protein signatures Fu ...