New distinguished classes of spectral spaces: a survey

In the present survey paper, we present several new classes of Hochster's spectral spaces "occurring in nature", actually in multiplicative ideal theory, and not linked to or realized in an explicit way by prime spectra of rings. The general setting is the space of the semistar operations (of finite type), endowed with a Zariski-like topology, which turns out to be a natural topological extension of the space of the overrings of an integral domain, endowed with a topology introduced by Zariski. One of the key tool is a recent characterization of spectral spaces, based on the ultrafilter topology, given in a paper by C. Finocchiaro in Comm. Algebra 2014. Several applications are also discussed

Structural analysis of MDM2 RING separates degradation from regulation of p53 transcription activity

MDM2–MDMX complexes bind the p53 tumor-suppressor protein, inhibiting p53's transcriptional activity and targeting p53 for proteasomal degradation. Inhibitors that disrupt binding between p53 and MDM2 efficiently activate a p53 response, but their use in the treatment of cancers that retain wild-type p53 may be limited by on-target toxicities due to p53 activation in normal tissue. Guided by a novel crystal structure of the MDM2–MDMX–E2(UbcH5B)–ubiquitin complex, we designed MDM2 mutants that prevent E2–ubiquitin binding without altering the RING-domain structure. These mutants lack MDM2's E3 activity but retain the ability to limit p53′s transcriptional activity and allow cell proliferation. Cells expressing these mutants respond more quickly to cellular stress than cells expressing wild-type MDM2, but basal p53 control is maintained. Targeting the MDM2 E3-ligase activity could therefore widen the therapeutic window of p53 activation in tumors

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Discovery of Molecular Markers to Discriminate Corneal Endothelial Cells in the Human Body

The corneal endothelium is a monolayer of hexagonal corneal endothelial cells (CECs) on the inner surface of the cornea. CECs are critical in maintaining corneal transparency through their barrier and pump functions. CECs in vivo have a limited capacity in proliferation, and loss of a significant number of CECs results in corneal edema called bullous keratopathy which can lead to severe visual loss. Corneal transplantation is the most effective method to treat corneal endothelial dysfunction, where it suffers from donor shortage. Therefore, regeneration of CECs from other cell types attracts increasing interests, and specific markers of CECs are crucial to identify actual CECs. However, the currently used markers are far from satisfactory because of their non-specific expression in other cell types. Here, we explored molecular markers to discriminate CECs from other cell types in the human body by integrating the published RNA-seq data of CECs and the FANTOM5 atlas representing diverse range of cell types based on expression patterns. We identified five genes, CLRN1, MRGPRX3, HTR1D, GRIP1 and ZP4 as novel markers of CECs, and the specificities of these genes were successfully confirmed by independent experiments at both the RNA and protein levels. Notably none of them have been documented in the context of CEC function. These markers could be useful for the purification of actual CECs, and also available for the evaluation of the products derived from other cell types. Our results demonstrate an effective approach to identify molecular markers for CECs and open the door for the regeneration of CECs in vitro

Small molecules, big targets: drug discovery faces the protein-protein interaction challenge.

Protein-protein interactions (PPIs) are of pivotal importance in the regulation of biological systems and are consequently implicated in the development of disease states. Recent work has begun to show that, with the right tools, certain classes of PPI can yield to the efforts of medicinal chemists to develop inhibitors, and the first PPI inhibitors have reached clinical development. In this Review, we describe the research leading to these breakthroughs and highlight the existence of groups of structurally related PPIs within the PPI target class. For each of these groups, we use examples of successful discovery efforts to illustrate the research strategies that have proved most useful.JS, DES and ARB thank the Wellcome Trust for funding.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nrd.2016.2

The MDM2-p53 pathway is involved in preconditioning-induced neuronal tolerance to ischemia.

Brain preconditioning (PC) refers to a state of transient tolerance against a lethal insult that can be evoked by a prior mild event. It is thought that PC may induce different pathways responsible for neuroprotection, which may involve the attenuation of cell damage pathways, including the apoptotic cell death. In this context, p53 is a stress sensor that accumulates during brain ischemia leading to neuronal death. The murine double minute 2 gene (MDM2), a p53-specific E3 ubiquitin ligase, is the main cellular antagonist of p53, mediating its degradation by the proteasome. Here, we study the role of MDM2-p53 pathway on PC-induced neuroprotection both in cultured neurons (in vitro) and rat brain (in vivo). Our results show that PC increased neuronal MDM2 protein levels, which prevented ischemiainduced p53 stabilization and neuronal death. Indeed, PC attenuated ischemia-induced activation of the p53/PUMA/caspase-3 signaling pathway. Pharmacological inhibition of MDM2-p53 interaction in neurons abrogated PC-induced neuroprotection against ischemia. Finally, the relevance of the MDM2-p53 pathway was confirmed in rat brain using a PC model in vivo. These findings demonstrate the key role of the MDM2-p53 pathway in PC-induced neuroprotection against a subsequent ischemic insult and poses MDM2 as an essential target in ischemic tolerance

In Vitro Transformation of Primary Human CD34+ Cells by AML Fusion Oncogenes: Early Gene Expression Profiling Reveals Possible Drug Target in AML

Different fusion oncogenes in acute myeloid leukemia (AML) have distinct clinical and laboratory features suggesting different modes of malignant transformation. Here we compare the in vitro effects of representatives of 4 major groups of AML fusion oncogenes on primary human CD34+ cells. As expected from their clinical similarities, MLL-AF9 and NUP98-HOXA9 had very similar effects in vitro. They both caused erythroid hyperplasia and a clear block in erythroid and myeloid maturation. On the other hand, AML1-ETO and PML-RARA had only modest effects on myeloid and erythroid differentiation. All oncogenes except PML-RARA caused a dramatic increase in long-term proliferation and self-renewal. Gene expression profiling revealed two distinct temporal patterns of gene deregulation. Gene deregulation by MLL-AF9 and NUP98-HOXA9 peaked 3 days after transduction. In contrast, the vast majority of gene deregulation by AML1-ETO and PML-RARA occurred within 6 hours, followed by a dramatic drop in the numbers of deregulated genes. Interestingly, the p53 inhibitor MDM2 was upregulated by AML1-ETO at 6 hours. Nutlin-3, an inhibitor of the interaction between MDM2 and p53, specifically inhibited the proliferation and self-renewal of primary human CD34+ cells transduced with AML1-ETO, suggesting that MDM2 upregulation plays a role in cell transformation by AML1-ETO. These data show that differences among AML fusion oncogenes can be recapitulated in vitro using primary human CD34+ cells and that early gene expression profiling in these cells can reveal potential drug targets in AML

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com

On the Mechanism of Action of SJ-172550 in Inhibiting the Interaction of MDM4 and p53

SJ-172550 (1) was previously discovered in a biochemical high throughput screen for inhibitors of the interaction of MDMX and p53 and characterized as a reversible inhibitor (J. Biol. Chem. 2010; 285∶10786). Further study of the biochemical mode of action of 1 has shown that it acts through a complicated mechanism in which the compound forms a covalent but reversible complex with MDMX and locks MDMX into a conformation that is unable to bind p53. The relative stability of this complex is influenced by many factors including the reducing potential of the media, the presence of aggregates, and other factors that influence the conformational stability of the protein. This complex mechanism of action hinders the further development of compound 1 as a selective MDMX inhibitor