AlphaFold2 (AF2) and RoseTTaFold (RF) have revolutionized structural biology, serving as
highly reliable and effective methods for predicting protein structures. This article explores …

Artificial intelligence has made significant advances in the field of protein structure prediction
in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated …

Predicting model quality is a fundamental component of any modeling procedure, and blind
assessment of these methods constitutes a crucial aspect of the Critical Assessment of …

The 'structure assessment'web server is a one-stop shop for interactive evaluation and
benchmarking of structural models of macromolecular complexes including proteins and …

Abstract Structure-resolved protein interactions with other proteins, peptides and nucleic
acids are key for understanding molecular mechanisms. The PPI3D web server enables …

For the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community
experiment included a section on computing multiple conformations for protein and RNA …

Protein–protein interactions (PPIs) are pivotal for driving diverse biological processes, and
any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been …

The three-dimensional structure of proteins determines their function in vital biological
processes. Thus, when the structure is known, the molecular mechanism of protein function …

The last five years have seen impressive progress in deep learning models applied to
protein research. Most notably, sequence-based structure predictions have seen …

Recent progress in protein structure prediction based on deep learning revolutionized the
field of Structural Biology. Beyond single proteins, it also enabled high-throughput prediction …