Striated muscle tissues undergo adaptive remodelling in response to mechanical load. This process involves the myofilament titin and, specifically, its kinase domain (TK; titin kinase) that translates mechanical signals into regulatory pathways of gene expression in the myofibril. TK mechanosensing appears mediated by a C-terminal regulatory tail (CRD) that sterically inhibits its active site. Allegedly, stretch-induced unfolding of this tail during muscle function releases TK inhibition and leads to its catalytic activation. However, the cellular pathway of TK is poorly understood and substrates proposed to date remain controversial. TK's best-established substrate is Tcap, a small structural protein of the Z-disc believed to link TK to myofibrillogenesis. Here, we show that TK is a pseudokinase with undetectable levels of catalysis and, therefore, that Tcap is not its substrate. Inactivity is the result of two atypical residues in TK's active site, M34 and E147, that do not appear compatible with canonical kinase patterns. While not mediating stretch-dependent phospho-transfers, TK binds the E3 ubiquitin ligase MuRF1 that promotes sarcomeric ubiquitination in a stress-induced manner. Given previous evidence of MuRF2 interaction, we propose that the cellular role of TK is to act as a conformationally regulated scaffold that functionally couples the ubiquitin ligases MuRF1 and MuRF2, thereby coordinating muscle-specific ubiquitination pathways and myofibril trophicity. Finally, we suggest that an evolutionary dichotomy of kinases/pseudokinases has occurred in TK-like kinases, where invertebrate members are active enzymes but vertebrate counterparts perform their signalling function as pseudokinase scaffolds.

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Bacterial competence, which can be natural or induced, allows the uptake of exogenous double stranded DNA (dsDNA) into a competent bacterium. This process is known as transformation. A multiprotein assembly binds and processes the dsDNA to import one strand and degrade another yet the underlying molecular mechanisms are relatively poorly understood. Here distant relationships of domains in Competence protein EC (ComEC) of Bacillus subtilis (Uniprot: P39695) were characterized. DNA‐protein interactions were investigated in silico by analyzing models for structural conservation, surface electrostatics and structure‐based DNA binding propensity; and by data‐driven macromolecular docking of DNA to models. Our findings suggest that the DUF4131 domain contains a cryptic DNA‐binding OB fold domain and that the β‐lactamase‐like domain is the hitherto cryptic competence nuclease. Proteins 2016; 84:1431–1442. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR) benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any -strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental methods. Finally, predicted contacts can distinguish between biologically relevant interfaces and mere lattice contacts in a final crystal structure, and have potential in the identification of functionally important regions and in foreseeing the consequences of mutations.

SIMBAD is a sequence-independent molecular-replacement pipeline for solving difficult molecular-replacement cases where contaminants have been crystallized. It can also be used to find structurally related search models where no obvious homologue can be found through sequence-based searching.