The field of protein design has made remarkable progress over the past decade. Historically,
the low reliability of purely structure-based design methods limited their application, but …

The rapid progress in the field of deep learning has had a significant impact on protein
design. Deep learning methods have recently produced a breakthrough in protein structure …

Complex integral membrane proteins, which are embedded in the cell surface lipid bilayer
by multiple transmembrane spanning polypeptides, encompass families of proteins that are …

Computational protein design is advancing rapidly. Here we describe efficient routes starting
from validated parallel and antiparallel peptide assemblies to design two families of α …

Membrane proteins are critical to biological processes and central to life sciences and
modern medicine. However, membrane proteins are notoriously challenging to study, mainly …

Recent advances in machine learning techniques have led to development of a number of
protein design and engineering approaches. One of them, ProteinMPNN, predicts an amino …

De novo protein design expands the protein universe by creating new sequences to
accomplish tailor‐made enzymes in the future. A promising topology to implement diverse …

The optimal residue identity at each position in a protein is determined by its structural,
evolutionary, and functional context. We seek to learn the representation space of the …

Computational protein design is advancing rapidly. Here we describe efficient routes to two
families of α-helical-barrel proteins with central channels that bind small molecules. The …

With recent methodological advances in the field of computational protein design, in
particular those based on deep learning, there is an increasing need for frameworks that …