6-Benzyl-3,4-dimeth­oxy-10-methyl­pyrido[2′,1′:2,3]imidazo[4,5-c]isoquinolin-5(6H)-one

Pyrido[2′,1′:2,3]imidazo[4,5-c]isoquinolin-5(6H)-ones such as the title compound, C24H21N3O3, can be obtained in a few minutes in a microwave-assisted three-component reaction from 2-amino­pyridines, isocyanides and 2-carboxy­benz­aldehydes. In the title compound, the pyrido[2′,1′:2,3]imidazo[4,5-c]isoquinolin-5(6H)-one ring system is almost planar (mean deviation 0.068 Å). The dihedral angle between the benzyl ring and the pyrido[2′,1′:2,3]imidazo[4,5-c]isoquinolin-5(6H)-one ring system is 78.2°. The crystal structure is stabilized by inter­molecular C—H⋯O and C—H⋯N hydrogen bonds

The Structure of the Oligomerization Domain of Lsr2 from Mycobacterium tuberculosis Reveals a Mechanism for Chromosome Organization and Protection

Lsr2 is a small DNA-binding protein present in mycobacteria and related actinobacteria that regulates gene expression and influences the organization of bacterial chromatin. Lsr2 is a dimer that binds to AT-rich regions of chromosomal DNA and physically protects DNA from damage by reactive oxygen intermediates (ROI). A recent structure of the C-terminal DNA-binding domain of Lsr2 provides a rationale for its interaction with the minor groove of DNA, its preference for AT-rich tracts, and its similarity to other bacterial nucleoid-associated DNA-binding domains. In contrast, the details of Lsr2 dimerization (and oligomerization) via its N-terminal domain, and the mechanism of Lsr2-mediated chromosomal cross-linking and protection is unknown. We have solved the structure of the N-terminal domain of Lsr2 (N-Lsr2) at 1.73 Å resolution using crystallographic ab initio approaches. The structure shows an intimate dimer of two ß-ß-a motifs with no close homologues in the structural databases. The organization of individual N-Lsr2 dimers in the crystal also reveals a mechanism for oligomerization. Proteolytic removal of three N-terminal residues from Lsr2 results in the formation of an anti-parallel β-sheet between neighboring molecules and the formation of linear chains of N-Lsr2. Oligomerization can be artificially induced using low concentrations of trypsin and the arrangement of N-Lsr2 into long chains is observed in both monoclinic and hexagonal crystallographic space groups. In solution, oligomerization of N-Lsr2 is also observed following treatment with trypsin. A change in chromosomal topology after the addition of trypsin to full-length Lsr2-DNA complexes and protection of DNA towards DNAse digestion can be observed using electron microscopy and electrophoresis. These results suggest a mechanism for oligomerization of Lsr2 via protease-activation leading to chromosome compaction and protection, and concomitant down-regulation of large numbers of genes. This mechanism is likely to be relevant under conditions of stress where cellular proteases are known to be upregulated

SEQUENCE SLIDER: expanding polyalanine fragments for phasing with multiple side-chain hypotheses.

Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content

Practical structure solution with ARCIMBOLDO

ARCIMBOLDO combines the location of small fragments with Phaser and density modification with SHELXE of all possible Phaser solutions. Its uses are explained and illustrated through practical test cases

The Structure of the Oligomerization Domain of Lsr2 from Mycobacterium tuberculosis Reveals a Mechanism for Chromosome Organization and Protection

Lsr2 is a small DNA-binding protein present in mycobacteria and related actinobacteria that regulates gene expression and influences the organization of bacterial chromatin. Lsr2 is a dimer that binds to AT-rich regions of chromosomal DNA and physically protects DNA from damage by reactive oxygen intermediates (ROI). A recent structure of the C-terminal DNA-binding domain of Lsr2 provides a rationale for its interaction with the minor groove of DNA, its preference for AT-rich tracts, and its similarity to other bacterial nucleoid-associated DNA-binding domains. In contrast, the details of Lsr2 dimerization (and oligomerization) via its N-terminal domain, and the mechanism of Lsr2-mediated chromosomal cross-linking and protection is unknown. We have solved the structure of the N-terminal domain of Lsr2 (N-Lsr2) at 1.73 Å resolution using crystallographic ab initio approaches. The structure shows an intimate dimer of two ß–ß–a motifs with no close homologues in the structural databases. The organization of individual N-Lsr2 dimers in the crystal also reveals a mechanism for oligomerization. Proteolytic removal of three N-terminal residues from Lsr2 results in the formation of an anti-parallel β-sheet between neighboring molecules and the formation of linear chains of N-Lsr2. Oligomerization can be artificially induced using low concentrations of trypsin and the arrangement of N-Lsr2 into long chains is observed in both monoclinic and hexagonal crystallographic space groups. In solution, oligomerization of N-Lsr2 is also observed following treatment with trypsin. A change in chromosomal topology after the addition of trypsin to full-length Lsr2-DNA complexes and protection of DNA towards DNAse digestion can be observed using electron microscopy and electrophoresis. These results suggest a mechanism for oligomerization of Lsr2 via protease-activation leading to chromosome compaction and protection, and concomitant down-regulation of large numbers of genes. This mechanism is likely to be relevant under conditions of stress where cellular proteases are known to be upregulated

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.Peer reviewe

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10

More about systematic errors in charge-density studies

In order to detect and graphically visualize the absence or presence of systematic errors in fit data, conditional probabilities are employed to analyze the statistical independence or dependence of fit residuals. This concept is completely general and applicable to all scientific fields in which model parameters are fitted to experimental data. The applications presented in this work refer to published charge-density data. © 2014 International Union of Crystallography.Peer Reviewe

Statistical tests against systematic errors in data sets based on the equality of residual means and variances from control samples: Theory and applications

Supplementary material at doi: 10.1107/S2053273314027363/pc5048sup1.pdf© 2015 International Union of Crystallography. Statistical tests are applied for the detection of systematic errors in data sets from least-squares refinements or other residual-based reconstruction processes. Samples of the residuals of the data are tested against the hypothesis that they belong to the same distribution. For this it is necessary that they show the same mean values and variances within the limits given by statistical fluctuations. When the samples differ significantly from each other, they are not from the same distribution within the limits set by the significance level. Therefore they cannot originate from a single Gaussian function in this case. It is shown that a significance cutoff results in exactly this case. Significance cutoffs are still frequently used in charge-density studies. The tests are applied to artificial data with and without systematic errors and to experimental data from the literature.Peer Reviewe