Patterns observed by examining the evolutionary relationships among proteins of common origin can reveal the structural and functional importance of specific residue positions. In particular, amino acids that are highly conserved (i.e., their positions evolve at a slower rate than other positions) are particularly likely to be of biological importance, for example, for ligand binding. ConSurf is a bioinformatics tool for accurately estimating the evolutionary rate of each position in a protein family. Here we introduce a new release of ConSurf‐DB, a database of precalculated ConSurf evolutionary conservation profiles for proteins of known structure. ConSurf‐DB provides high‐accuracy estimates of the evolutionary rates of the amino acids in each protein. A reliable estimate of a query protein's evolutionary rates depends on having a sufficiently large number of effective homologues (i.e., nonredundant yet sufficiently similar). With current sequence data, ConSurf‐DB covers 82% of the PDB proteins. It will be updated on a regular basis to ensure that coverage remains high—and that it might even increase. Much effort was dedicated to improving the user experience. The repository is available at https://consurfdb.tau.ac.il/.Broader audienceBy comparing a protein to other proteins of similar origin, it is possible to determine the extent to which each amino acid position in the protein evolved slowly or rapidly. A protein's evolutionary profile can provide valuable insights: For example, amino acid positions that are highly conserved (i.e., evolved slowly) are particularly likely to be of structural and/or functional importance, for example, for ligand binding and catalysis. We introduce here a new and improved version of ConSurf‐DB, a continually updated database that provides precalculated evolutionary profiles of proteins with known structure.

CueR (Cu export regulator) is a metalloregulator protein that "senses" Cu(I) ions with very high affinity, thereby stimulating DNA binding and the transcription activation of two other metalloregulator proteins. The crystal structures of CueR when unbound or bound to DNA and a metal ion are very similar to each other, and the role of CueR and Cu(I) in initiating the transcription has not been fully understood yet. Using double electron-electron resonance (DEER) measurements and structure modeling, we investigate the conformational changes that CueR undergoes upon binding Cu(I) and DNA in solution. We observe three distinct conformations, corresponding to apo-CueR, DNA-bound CueR in the absence of Cu(I) (the "repression" state), and CueR-Cu(I)-DNA (the "activation" state). We propose a detailed structural mechanism underlying CueR's regulation of the transcription process. The mechanism explicitly shows the dependence of CueR activity on copper, thereby revealing the important negative feedback mechanism essential for regulating the intracellular copper concentration.

Proteins’ interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein–adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein–adenine interactions in the Watson–Crick edge of adenine and shows that all of adenine’s edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments (“themes”) that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.

Protein function involves conformational changes, but often, for a given protein, only some of these conformations are known. The missing conformations could be predicted using the wealth of data in the PDB. Most PDB proteins have multiple structures, and proteins sharing one similar conformation often share others as well. The ConTemplate web server (http://bental.tau.ac.il/contemplate) exploits these observations to suggest conformations for a query protein with at least one known conformation (or model thereof). We demonstrate ConTemplate on a ribose-binding protein that undergoes significant conformational changes upon substrate binding. Querying ConTemplate with the ligand-free (or bound) structure of the protein produces the ligand-bound (or free) conformation with a root-mean-square deviation of 1.7 Å (or 2.2 Å); the models are derived from conformations of other sugar-binding proteins, sharing approximately 30% sequence identity with the query. The calculation also suggests intermediate conformations and a pathway between the bound and free conformations.

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