Since the first revelation of proteins functioning as macromolecular machines through their
three dimensional structures, researchers have been intrigued by the marvelous ways the …

Proteins are molecular machines whose function depends on their ability to achieve
complex folds with precisely defined structural and dynamic properties. The rational design …

Abstract The AlphaFold Protein Structure Database, containing predictions for over 200
million proteins, has been met with enthusiasm over its potential in enriching structural …

While deep learning models have seen increasing applications in protein science, few have
been implemented for protein backbone generation—an important task in structure-based …

Motivation It is fundamental to cut multi-domain proteins into individual domains, for precise
domain-based structural and functional studies. In the past, sequence-based and structure …

Motivation Protein domains are fundamental units of protein structure and play a pivotal role
in understanding folding, function, evolution, and design. The advent of accurate structure …

While deep learning models have seen increasing applications in protein science, few have
been implemented for protein backbone generation—an important task in structure-based …

Following the hugely successful application of deep learning methods to protein structure
prediction, an increasing number of design methods seek to leverage generative models to …

The ability to finely control the structure of protein folds is an important prerequisite to
functional protein design. The TIM barrel fold is an important target for these efforts as it is …

Protein domains are distinct, modular and locally compact units of protein structures which
may fold and function independently to the rest of the protein. Identifying the regions …