Protein structures can provide invaluable information, both for reasoning about biological
processes and for enabling interventions such as structure-based drug development or …

The inapplicability of amino acid covariation methods to small protein families has limited
their use for structural annotation of whole genomes. Recently, deep learning has shown …

Glutamate has dual roles in metabolism and signaling; thus, signaling functions must be
isolatable and distinct from metabolic fluctuations, as seen in low-glutamate domains at …

Motivation Significant improvements in the prediction of protein residue–residue contacts
are observed in the recent years. These contacts, predicted using a variety of coevolution …

Motivation Residue contact prediction was revolutionized recently by the introduction of
direct coupling analysis (DCA). Further improvements, in particular for small families, have …

Deep learning-based prediction of protein structure usually begins by constructing a multiple
sequence alignment (MSA) containing homologs of the target protein. The most successful …

Background Contact-guided protein structure prediction methods are becoming more and
more successful because of the latest advances in residue-residue contact prediction. To …

Accurate structural information plays a crucial role in comprehending biological processes
and designing drugs. Indeed, the remarkable precision of the AlphaFold2 has facilitated …

Motivation Deep learning has become the dominant technology for protein contact
prediction. However, the factors that affect the performance of deep learning in contact …

Highlights•Structural modeling of a cell is an evolving strategic direction.•Experimental
techniques provide data and validation for the modeling.•Key modeling approaches to …