Most biomolecular modeling energy functions for structure prediction, sequence design, and
molecular docking have been parametrized using existing macromolecular structural data; …

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for studying the
structure and dynamics of proteins in their native state. For high-resolution NMR structure …

The description of protein disordered states is important for understanding protein folding
mechanisms and their functions. In this short review, we briefly describe a simulation …

We describe several notable aspects of our structure predictions using Rosetta in CASP12
in the free modeling (FM) and refinement (TR) categories. First, we had previously …

NMR studies can provide unique information about protein conformations in solution. In
CASP14, three reference structures provided by solution NMR methods were available …

Recent advances in molecular modeling using deep learning have the potential to
revolutionize the field of structural biology. In particular, AlphaFold has been observed to …

The optimization approaches classically used during the determination of protein structure
encounter various difficulties, especially when the size of the conformational space is large …

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein
structure prediction. NOESY and 15N‐1H residual dipolar coupling data, typical of that …

Cryo-EM has become one of the prime methods for protein structure elucidation, frequently
yielding density maps with near-atomic or medium resolution. If protein structures cannot be …

Computational methods that produce accurate protein structure models from limited
experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold …