It has long been recognized that certain sites within a protein, such as sites in the protein
core or catalytic residues in enzymes, are evolutionarily more conserved than other sites …

Heavy metal contamination is a global environmental issue as it poses a significant threat to
public health, and exposure to metals above a certain threshold level can cause deleterious …

Abstract Machine learning-based models of protein fitness typically learn from either
unlabeled, evolutionarily related sequences or variant sequences with experimentally …

Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven
to be an effective means of capturing the functionally important long-time and large-length …

The quantitative characterization of mutational landscapes is a task of outstanding
importance in evolutionary and medical biology: It is, for example, of central importance for …

Generative models emerge as promising candidates for novel sequence-data driven
approaches to protein design, and for the extraction of structural and functional information …

The heme iron complex is one of the most important cofactors in biological systems (Figure
1). The major functions of the heme iron complex are to serve as the O2 binding site for …

Light-switchable proteins enable unparalleled control of molecular biological processes in
live organisms. Previously, we have engineered red/far-red and green/red photoreversible …

A novel family of 2Fe–2S proteins, the NEET family, was discovered during the last decade
in numerous organisms, including archea, bacteria, algae, plant and human; suggesting an …

Machine learning has been proposed as an alternative to theoretical modeling when
dealing with complex problems in biological physics. However, in this perspective, we argue …