Nature Methods published (online) a comparative study of leading Protein-Protein Interaction (PPI) Networks. The publication entitled “A scored human protein-protein interaction network to catalyze ...

Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...

Washington State University researchers have found a way to modulate a common virus protein to prevent viruses from entering cells where it can cause illness, a discovery that could someday lead to ...

Protein engineering is a powerful biotechnological process that focuses on creating new enzymes or proteins and improving the functions of existing ones by manipulating their natural macromolecular ...

Researchers create Disobind, an AI tool predicting protein interactions, advancing disease biology and drug design applications.

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 ...

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 ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin has introduced CGSchNet, a machine-learned coarse-grained (CG) model that can ...

UT researchers have developed the first viable alternative to a 75-year-old method for sequencing proteins. Image of amino acids, the building blocks of proteins. Scientists at The University of Texas ...