Structure of an Hsp90-Cdc37-Cdk4 complex

Activation of many protein kinases depends on their interaction with the Hsp90 molecular chaperone system. Recruitment of protein kinase clients to the Hsp90 chaperone system is mediated by the cochaperone adaptor protein Cdc37, which acts as a scaffold, simultaneously binding protein kinases and Hsp90. We have now expressed and purified an Hsp90-Cdc37-Cdk4 complex, defined its stoichiometry, and determined its 3D structure by single-particle electron microscopy. Comparison with the crystal structure of Hsp90 allows us to identify the locations of Cdc37 and Cdk4 in the complex and suggests a mechanism by which conformational changes in the kinase are coupled to the Hsp90 ATPase cycle

Characterization of the proneural gene regulatory network during mouse telencephalon development

BACKGROUND: The proneural proteins Mash1 and Ngn2 are key cell autonomous regulators of neurogenesis in the mammalian central nervous system, yet little is known about the molecular pathways regulated by these transcription factors. RESULTS: Here we identify the downstream effectors of proneural genes in the telencephalon using a genomic approach to analyze the transcriptome of mice that are either lacking or overexpressing proneural genes. Novel targets of Ngn2 and/or Mash1 were identified, such as members of the Notch and Wnt pathways, and proteins involved in adhesion and signal transduction. Next, we searched the non-coding sequence surrounding the predicted proneural downstream effector genes for evolutionarily conserved transcription factor binding sites associated with newly defined consensus binding sites for Ngn2 and Mash1. This allowed us to identify potential novel co-factors and co-regulators for proneural proteins, including Creb, Tcf/Lef, Pou-domain containing transcription factors, Sox9, and Mef2a. Finally, a gene regulatory network was delineated using a novel Bayesian-based algorithm that can incorporate information from diverse datasets. CONCLUSION: Together, these data shed light on the molecular pathways regulated by proneural genes and demonstrate that the integration of experimentation with bioinformatics can guide both hypothesis testing and hypothesis generation

Molecular determinants of binding to the Plasmodium subtilisin-like protease 1.

PfSUB1, a subtilisin-like protease of the human malaria parasite Plasmodium falciparum, is known to play important roles during the life cycle of the parasite and has emerged as a promising antimalarial drug target. In order to provide a detailed understanding of the origin of binding determinants of PfSUB1 substrates, we performed molecular dynamics simulations in combination with MM-GBSA free energy calculations using a homology model of PfSUB1 in complex with different substrate peptides. Key interactions, as well as residues that potentially make a major contribution to the binding free energy, are identified at the prime and nonprime side of the scissile bond and comprise peptide residues P4 to P2'. This finding stresses the requirement for peptide substrates to interact with both prime and nonprime side residues of the PfSUB1 binding site. Analyzing the energetic contributions of individual amino acids within the peptide-PfSUB1 complexes indicated that van der Waals interactions and the nonpolar part of solvation energy dictate the binding strength of the peptides and that the most favorable interactions are formed by peptide residues P4 and P1. Hot spot residues identified in PfSUB1 are dispersed over the entire binding site, but clustered areas of hot spots also exist and suggest that either the S4-S2 or the S1-S2' binding site should be exploited in efforts to design small molecule inhibitors. The results are discussed with respect to which binding determinants are specific to PfSUB1 and, therefore, might allow binding selectivity to be obtained

Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1,727 healthy Caucasians

Copyright: Copyright 2008 Elsevier B.V., All rights reserved.The associations of the adiponectin (APM1) gene with parameters of the metabolic syndrome are inconsistent. We performed a systematic investigation based on fine-mapped single nucleotide polymorphisms (SNPs) highlighting the genetic architecture and their role in modulating adiponectin plasma concentrations in a particularly healthy population of 1,727 Caucasians avoiding secondary effects from disease processes. Genotyping 53 SNPs (average spacing of 0.7 kb) in the APM1 gene region in 81 Caucasians revealed a two-block linkage disequilibrium (LD) structure and enabled comprehensive tag SNP selection. We found particularly strong associations with adiponectin concentrations for 11 of the 15 tag SNPs in the 1,727 subjects (five P values <0.0001). Haplotype analysis provided a thorough differentiation of adiponectin concentrations with 9 of 17 haplotypes showing significant associations (three P values <0.0001). No significant association was found for any SNP with the parameters of the metabolic syndrome. We observed a two-block LD structure of APM1 pointing toward at least two independent association signals, one including the promoter SNPs and a second spanning the relevant exons. Our data on a large number of healthy subjects suggest a clear modulation of adiponectin concentrations by variants of APM1, which are not merely a concomitant effect in the course of type 2 diabetes or coronary artery disease.publishersversionPeer reviewe

Prediction of Ligand Binding Using an Approach Designed to Accommodate Diversity in Protein-Ligand Interactions

Computational determination of protein-ligand interaction potential is important for many biological applications including virtual screening for therapeutic drugs. The novel internal consensus scoring strategy is an empirical approach with an extended set of 9 binding terms combined with a neural network capable of analysis of diverse complexes. Like conventional consensus methods, internal consensus is capable of maintaining multiple distinct representations of protein-ligand interactions. In a typical use the method was trained using ligand classification data (binding/no binding) for a single receptor. The internal consensus analyses successfully distinguished protein-ligand complexes from decoys (r2, 0.895 for a series of typical proteins). Results are superior to other tested empirical methods. In virtual screening experiments, internal consensus analyses provide consistent enrichment as determined by ROC-AUC and pROC metrics

Genetic association of zinc transporter 8 (ZnT8) autoantibodies in type 1 diabetes cases

Autoantibodies to zinc transporter 8 (ZnT8A) are associated with risk of type 1 diabetes. Apart from the SLC30A8 gene itself, little is known about the genetic basis of ZnT8A. We hypothesise that other loci in addition to SLC30A8 are associated with ZnT8A. The levels of ZnT8A were measured in 2,239 British type 1 diabetic individuals diagnosed before age 17 years, with a median duration of diabetes of 4 years. Cases were tested at over 775,000 loci genome wide (including 53 type 1 diabetes associated regions) for association with positivity for ZnT8A. ZnT8A were also measured in an independent dataset of 855 family members with type 1 diabetes. Only FCRL3 on chromosome 1q23.1 and the HLA class I region were associated with positivity for ZnT8A. rs7522061T &gt; C was the most associated single nucleotide polymorphism (SNP) in the FCRL3 region (p = 1.13 x 10(-16)). The association was confirmed in the family dataset (p a parts per thousand currency signaEuro parts per thousand 9.20 x 10(-4)). rs9258750A &gt; G was the most associated variant in the HLA region (p = 2.06 x 10(-9) and p = 0.0014 in family cases). The presence of ZnT8A was not associated with HLA-DRB1, HLA-DQB1, HLA-A, HLA-B or HLA-C (p &gt; 0.05). Unexpectedly, the two loci associated with the presence of ZnT8A did not alter risk of having type 1 diabetes, and the 53 type 1 diabetes risk loci did not influence positivity for ZnT8A, despite them being disease specific. ZnT8A are not primary pathogenic factors in type 1 diabetes. Nevertheless, ZnT8A testing in combination with other autoantibodies facilitates disease prediction, despite the biomarker not being under the same genetic control as the disease

Limitations of Ab Initio Predictions of Peptide Binding to MHC Class II Molecules

Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical potentials derived from the analysis of known protein structures; energetic evaluation of different peptide snapshots in a molecular dynamics simulation; and direct analysis of contacts made in known 3D structures of peptide:MHC complexes. These methods are ab initio in that they require structural data of the MHC molecule examined, but no specific peptide:MHC binding data. Moreover, these methods retain the ability to make predictions in a sufficiently short time scale to be useful in a real world application, such as screening a whole proteome for candidate binding peptides. A rigorous evaluation of each methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results together in order to support the notion that generating structure based predictions of peptide:MHC binding without using binding data is unlikely to give satisfactory results

Guidelines On Diabetes, Pre-Diabetes, And Cardiovascular Diseases: Executive Summary.The Task Force on Diabetes and Cardiovascular Diseases of the European Society of Cardiology (ESC) and of the European Association for the Study of Diabetes (EASD).

Guidelines and Expert Consensus documents aim to present management and recommendations based on all of the relevant evidence on a particular subject in order to help physicians to select the best possible management strategies for the individual patient, suffering from a specific condition, taking into account not only the impact on outcome, but also the risk benefit ratio of a particular diagnostic or therapeutic procedure. The ESC recommendations for guidelines production can be found on the ESC website†. In brief, the ESC appoints experts in the field to carry out a comprehensive and critical evaluation of the use of diagnostic and therapeutic procedures and to assess the risk–benefit ratio of the therapies recommended for management and/or prevention of a given condition. The strength of evidence for or against particular procedures or treatments is weighed according to predefined scales for grading recommendations and levels of evidence, as outlined below. Once the document has been finalized and approved by all the experts involved in the Task Force, it is submitted to outside specialists for review. If necessary, the document is revised once more to be finally approved by the Committee for Practice Guidelines and selected members of the Board of the ESC. The ESC Committee for Practice Guidelines (CPG) supervises and coordinates the preparation of new Guidelines and Expert Consensus Documents produced by Task Forces, expert groups, or consensus panels. The chosen experts in these writing panels are asked to provide disclosure statements of all relationships they may have, which might be perceived as real or potential conflicts of interest. These disclosure forms are kept on file at the European Heart House, headquarters of the ESC. The Committee is also responsible for the endorsement of these Guidelines and Expert Consensus Documents or statements

Majorana quantization and half-integer thermal quantum Hall effect in a Kitaev spin liquid

The quantum Hall effect (QHE) in two-dimensional (2D) electron gases, which is one of the most striking phenomena in condensed matter physics, involves the topologically protected dissipationless charge current flow along the edges of the sample. Integer or fractional electrical conductance are measured in units of $e^2/2\pi\hbar$, which is associated with edge currents of electrons or quasiparticles with fractional charges, respectively. Here we discover a novel type of quantization of the Hall effect in an insulating 2D quantum magnet. In $\alpha$-RuCl$_3$ with dominant Kitaev interaction on 2D honeycomb lattice, the application of a parallel magnetic field destroys the long-range magnetic order, leading to a field-induced quantum spin liquid (QSL) ground state with massive entanglement of local spins. In the low-temperature regime of the QSL state, we report that the 2D thermal Hall conductance $\kappa_{xy}^{2D}$ reaches a quantum plateau as a function of applied magnetic field. $\kappa_{xy}^{2D}/T$ attains a quantization value of $(\pi/12)(k_B^2/\hbar)$, which is exactly half of $\kappa_{xy}^{2D}/T$ in the integer QHE. This half-integer thermal Hall conductance observed in a bulk material is a direct signature of topologically protected chiral edge currents of charge neutral Majorana fermions, particles that are their own antiparticles, which possess half degrees of freedom of conventional fermions. These signatures demonstrate the fractionalization of spins into itinerant Majorana fermions and $Z_2$ fluxes predicted in a Kitaev QSL. Above a critical magnetic field, the quantization disappears and $\kappa_{xy}^{2D}/T$ goes to zero rapidly, indicating a topological quantum phase transition between the states with and without chiral Majorana edge modes. Emergent Majorana fermions in a quantum magnet are expected to have a major impact on strongly correlated topological quantum matter.Comment: 7 pages, 8 figures. Submitted versio