BackgroundDistinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved.ResultsWe present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts.ConclusionsAn evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org.

Most secretory preproteins exit bacterial cells through the protein translocase, comprising the SecYEG channel and the dimeric peripheral ATPase motor SecA. Energetic coupling to work remains elusive. We now demonstrate that translocation is driven by unusually dynamic quaternary changes in SecA. The dimer occupies several successive states with distinct protomer arrangements. SecA docks on SecYEG as a dimer and becomes functionally asymmetric. Docking occurs via only one protomer. The second protomer allosterically regulates downstream steps. Binding of one preprotein signal peptide to the SecYEG-docked SecA protomer elongates the SecA dimer and triggers the translocase holoenzyme to obtain a lower activation energy conformation. ATP hydrolysis monomerizes the triggered SecA dimer, causing mature chain trapping and processive translocation. This is a unique example of one protein exploiting quaternary dynamics to become a substrate receptor, a "loading clamp," and a "processive motor." This mechanism has widespread implications on protein translocases, chaperones, and motors.

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Microtubule plus-end tracking proteins (؉TIPs) are involved in many microtubule-based processes. End binding (EB) proteins constitute a highly conserved family of ؉TIPs. They play a pivotal role in regulating microtubule dynamics and in the recruitment of diverse ؉TIPs to growing microtubule plus ends. Here we used a combination of methods to investigate the dimerization properties of the three human EB proteins EB1, EB2, and EB3. Based on Förster resonance energy transfer, we demonstrate that the C-terminal dimerization domains of EBs (EBc) can readily exchange their chains in solution. We further document that EB1c and EB3c preferentially form heterodimers, whereas EB2c does not participate significantly in the formation of heterotypic complexes. Measurements of the reaction thermodynamics and kinetics, homology modeling, and mutagenesis provide details of the molecular determinants of homo-versus heterodimer formation of EBc domains. Fluorescence spectroscopy and nuclear magnetic resonance studies in the presence of the cytoskeleton-associated protein-glycinerich domains of either CLIP-170 or p150 glued or of a fragment derived from the adenomatous polyposis coli tumor suppressor protein show that chain exchange of EBc domains can be controlled by binding partners. Extension of these studies of the EBc domains to full-length EBs demonstrate that heterodimer formation between EB1 and EB3, but not between EB2 and the other two EBs, occurs both in vitro and in cells as revealed by live cell imaging. Together, our data provide molecular insights for rationalizing the dominant negative control by C-terminal EB domains and form a basis for understanding the functional role of heterotypic chain exchange by EBs in cells.

Fine-tuning protein stability: The non-natural amino acids (2S,4R)- and (2S,4S)-fluoroproline modulate protein stability by biasing the proline ring pucker and the cis/trans equilibrium of prolyl peptide bonds. We incorporated both fluoroproline stereoisomers at the invariant cis-proline residue of the thioredoxin fold. The results show that tertiary structure context overrules the conformational preferences of fluoroprolines.

Background: ␣-Proteobacteria, extant relatives of mitochondria, are model organisms for studying assembly of bacterial and mitochondrial metalloenzymes. Results: Periplasmic thioredoxin TlpA is a specific reductant for copper chaperone ScoI and cytochrome oxidase subunit II (CoxB). Conclusion: Cysteines in the copper-binding sites of ScoI and CoxB must be reduced prior to metallation. Significance: Structures of TlpA-ScoI and TlpA-CoxB intermediates reveal mechanistic details of the reduction process.

Cis prolyl peptide bonds are conserved structural elements in numerous protein families, although their formation is energetically unfavorable, intrinsically slow and often rate-limiting for folding. Here we investigate the reasons underlying the conservation of the cis proline that is diagnostic for the fold of thioredoxin-like thiol-disulfide oxidoreductases. We show that replacement of the conserved cis proline in thioredoxin by alanine can accelerate spontaneous folding to the native, thermodynamically most stable state by more than four orders of magnitude. However, the resulting trans alanine bond leads to small structural rearrangements around the active site that impair the function of thioredoxin as catalyst of electron transfer reactions by more than 100-fold. Our data provide evidence for the absence of a strong evolutionary pressure to achieve intrinsically fast folding rates, which is most likely a consequence of proline isomerases and molecular chaperones that guarantee high in vivo folding rates and yields.

Protein crystals contain two different types of interfaces: biologically relevant ones, observed in protein-protein complexes and oligomeric proteins, and nonspecific ones, corresponding to crystal lattice contacts. Because of the increasing complexity of the objects being tackled in structural biology, distinguishing biological contacts from crystal contacts is not always a trivial task and can lead to wrong interpretation of macromolecular structures. We devised an approach (CRK, core-rim K(a)/K(s) ratio) for distinguishing biologically relevant interfaces from nonspecific ones. Given a protein-protein interface, CRK finds a set of homologs to the sequences of the proteins involved in the interface, retrieves and aligns the corresponding coding sequences, on which it carries out a residue-by-residue K(a)/K(s) ratio (omega) calculation. It divides interface residues into a "rim" and a "core" set and analyzes the selection pressure on the residues belonging to the two sets. We developed and tested CRK on different datasets and test cases, consisting of biologically relevant contacts, nonspecific ones or of both types. The method proves very effective in distinguishing the two categories of interfaces, with an overall accuracy rate of 84%. As it relies on different principles when compared with existing tools, CRK is optimally suited to be used in combination with them. In addition, CRK has potential applications in the validation of structures of oligomeric proteins and protein complexes.