Artificial intelligence-based protein structure prediction approaches have had a
transformative effect on biomolecular sciences. The predicted protein models in the …

Artificial intelligence-based protein structure prediction methods such as AlphaFold have
revolutionized structural biology. The accuracies of these predictions vary, however, and …

Ramachandran plots report the distribution of the (ϕ, ψ) torsion angles of the protein
backbone and are one of the best quality metrics of experimental structure models. Typically …

Sialic acid (N-acetylneuraminic acid (Neu5Ac)) is commonly found in the terminal location of
colonic mucin glycans where it is a much-coveted nutrient for gut bacteria, including …

The power of structural information for informing biological mechanisms is clear for stable
folded macromolecules, but similar structure–function insight is more difficult to obtain for …

The availability and repartition of fucosylated glycans within the gastrointestinal tract
contributes to the adaptation of gut bacteria species to ecological niches. To access this …

The oligosaccharides in N-glycosylation provide key structural and functional contributions
to a glycoprotein. These contributions are dependent on the composition and overall …

AI-based methods such as AlphaFold have raised the possibility of using predicted models
in place of experimentally-determined structures. Here we assess the accuracy of AlphaFold …

Autosomal dominant tubulointerstitial kidney disease (ADTKD) is a genetically
heterogeneous renal disorder leading to progressive loss of renal function. ADTKD-REN is …

The performance of automated protein model building usually decreases with resolution,
mainly owing to the lower information content of the experimental data. This calls for a more …