Recent work has shown that NMR structures can be determined by integrating sparse NMR
data with structure prediction methods such as Rosetta. The experimental data serve to …

A key challenge of modern biology is to uncover the functional role of the protein entities that
compose cellular proteomes. To this end, the availability of reliable three-dimensional …

One of critical difficulties of molecular dynamics (MD) simulations in protein structure
refinement is that the physics-based energy landscape lacks a middle-range funnel to guide …

Recent breakthroughs in highly accurate protein structure prediction using deep neural
networks have made considerable progress in solving the structure prediction component of …

To accurately predict protein conformations in atomic detail, a computational method must
be capable of sampling models sufficiently close to the native structure. All-atom sampling is …

We describe AlphaFold, the protein structure prediction system that was entered by the
group A7D in CASP13. Submissions were made by three free‐modeling (FM) methods …

Computer-based structure prediction becomes a major tool to provide large-scale structure
models for annotating biological function of proteins. Information of residue-level accuracy …

Three-dimensional protein structures provide invaluable information for understanding and
regulating biological functions of proteins. The GalaxyWEB server predicts protein structure …

The primary obstacle to de novo protein structure prediction is conformational sampling: the
native state generally has lower free energy than nonnative structures but is exceedingly …

Deep-learning methods have revolutionized protein structure prediction and design but are
presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which …