Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods
to determine three-dimensional macromolecular structures, which are required to …

The prediction of protein three-dimensional structure from amino acid sequence has been a
grand challenge problem in computational biophysics for decades, owing to its intrinsic …

Structure prediction for proteins lacking homologous templates in the Protein Data Bank
(PDB) remains a significant unsolved problem. We developed a protocol, CI-TASSER, to …

AlphaFold can predict the structure of single-and multiple-chain proteins with very high
accuracy. However, the accuracy decreases with the number of chains, and the available …

There has been considerable recent progress in protein structure prediction using deep
neural networks to predict inter-residue distances from amino acid sequences,–. Here we …

The prediction of interresidue contacts and distances from coevolutionary data using deep
learning has considerably advanced protein structure prediction. Here, we build on these …

Thermophilic polyester hydrolases (PES-H) have recently enabled biocatalytic recycling of
the mass-produced synthetic polyester polyethylene terephthalate (PET), which has found …

This article describes the implementation of real-space refinement in the phenix.
real_space_refine program from the PHENIX suite. The use of a simplified refinement target …

Proton-coupled monocarboxylate transporters MCT1-4 catalyze the transmembrane
movement of metabolically essential monocarboxylates and have been targeted for cancer …

Computational prediction of protein structure from sequence is broadly viewed as a
foundational problem of biochemistry and one of the most difficult challenges in …