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Abstract: A family of leucine-rich-repeat-containing G-protein-coupled receptors (LGRs) mediate diverse physiological responses when complexed with their cognate ligands. LGRs are present in all metazoan animals. In humans, the LGR ligands include glycoprotein hormones (GPHs) chorionic gonadotropin (hCG), luteinizing hormone, follicle-stimulating hormone (hFSH), and thyroid-stimulating hormone (hTSH). These hormones are αβ heterodimers of cystine-knot protein chains. LGRs and their ligand chains have coevolved. Ancestral hormone homologs, present in both bilaterian animals and chordates, are identified as α2β5. We have used single-wavelength anomalous diffraction and molecular replacement to determine structures of the α2β5 hormone from Caenorhabditis elegans (Ceα2β5). Ceα2β5 is unglycosylated, as are many other α2β5 hormones. Both Hsα2β5, the human homolog of Ceα2β5, and hTSH activate the same receptor (hTSHR). Despite having little sequence similarity to vertebrate GPHs, apart from the cysteine patterns from core disulfide bridges, Ceα2β5 is generally similar in structure to these counterparts; however, its α2 and β5 subunits are more symmetric as compared with α and β of hCG and hFSH. This quasisymmetry suggests a hypothetical homodimeric antecedent of the α2β5 and αβ heterodimers. Known structures together with AlphaFold models from the sequences for other LGR ligands provide representatives for the molecular evolution of LGR ligands from early metazoans through the present-day GPHs. The experimental Ceα2β5 structure validates its AlphaFold model, and thus also that for Hsα2β5; and interfacial characteristics in a model for the Hsα2β5:hTSHR complex are similar to those found in an experimental hTSH:hTSHR structure.

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Abstract: β-Galactosidases catalyse the hydrolysis of lactose into galactose and glucose; as an alternative reaction, some β-galactosidases also catalyse the formation of galactooligosaccharides by transglycosylation. Both reactions have industrial importance: lactose hydrolysis is used to produce lactose-free milk, while galactooligosaccharides have been shown to act as prebiotics. For some multi-domain β-galactosidases, the hydrolysis/transglycosylation ratio can be modified by the truncation of carbohydrate-binding modules. Here, an analysis of BbgIII, a multidomain β-galactosidase from Bifidobacterium bifidum, is presented. The X-ray structure has been determined of an intact protein corresponding to a gene construct of eight domains. The use of evolutionary covariance-based predictions made sequence docking in low-resolution areas of the model spectacularly easy, confirming the relevance of this rapidly developing deep-learning-based technique for model building. The structure revealed two alternative orientations of the CBM32 carbohydrate-binding module relative to the GH2 catalytic domain in the six crystallographically independent chains. In one orientation the CBM32 domain covers the entrance to the active site of the enzyme, while in the other orientation the active site is open, suggesting a possible mechanism for switching between the two activities of the enzyme, namely lactose hydrolysis and transgalactosylation. The location of the carbohydrate-binding site of the CBM32 domain on the opposite site of the module to where it comes into contact with the catalytic GH2 domain is consistent with its involvement in adherence to host cells. The role of the CBM32 domain in switching between hydrolysis and transglycosylation modes offers protein-engineering opportunities for selective β-galactosidase modification for industrial purposes in the future.

Open Access

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Abstract: The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here, SIMBAD, a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD, this approach has solved novel cases that have otherwise proved difficult to solve.

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Abstract: Bacterial phosphoinositide-specific phospholipases C (PI-PLCs) are the smallest members of the PI-PLC family, which includes much larger mammalian enzymes responsible for signal transduction as well as enzymes from protozoan parasites, yeast and plants. Eukaryotic PI-PLCs have calcium in the active site, but this is absent in the known structures of Gram-positive bacteria, where its role is instead played by arginine. In addition to their use in a number of industrial applications, the bacterial enzymes attract special interest because they can serve as convenient models of the catalytic domains of eukaryotic enzymes for in vitro activity studies. Here, the structure of a PI-PLC from Pseudomonas sp. 62186 is reported, the first from a Gram-negative bacterium and the first of a native bacterial PI-PLC with calcium present in the active site. Solution of the structure posed particular problems owing to the low sequence identity of available homologous structures. Its dependence on calcium for catalysis makes this enzyme a better model for studies of the mammalian PI-PLCs than the previously used calcium-independent bacterial PI-PLCs.

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Abstract: The presence of pseudo-symmetry in a macromolecular crystal and its interplay with twinning may lead to an incorrect space-group (SG) assignment. Moreover, if the pseudo-symmetry is very close to an exact crystallographic symmetry, the structure can be solved and partially refined in the wrong SG. Typically, in such incorrectly determined structures all or some of the pseudo-symmetry operations are, in effect, taken for crystallographic symmetry operations and vice versa. A mistake only becomes apparent when the Rfree ceases to decrease below 0.39 and further model rebuilding and refinement cannot improve the refinement statistics. If pseudo-symmetry includes pseudo-translation, the uncertainty in SG assignment may be associated with an incorrect choice of origin, as demonstrated by the series of examples provided here. The program Zanuda presented in this article was developed for the automation of SG validation. Zanuda runs a series of refinements in SGs compatible with the observed unit-cell parameters and chooses the model with the highest symmetry SG from a subset of models that have the best refinement statistics.