603 research outputs found

    Repositioning of Verrucosidin, a purported inhibitor of chaperone protein GRP78, as an inhibitor of mitochondrial electron transport chain complex I.

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    Verrucosidin (VCD) belongs to a group of fungal metabolites that were identified in screening programs to detect molecules that preferentially kill cancer cells under glucose-deprived conditions. Its mode of action was proposed to involve inhibition of increased GRP78 (glucose regulated protein 78) expression during hypoglycemia. Because GRP78 plays an important role in tumorigenesis, inhibitors such as VCD might harbor cancer therapeutic potential. We therefore sought to characterize VCD's anticancer activity in vitro. Triple-negative breast cancer cell lines MDA-MB-231 and MDA-MB-468 were treated with VCD under different conditions known to trigger increased expression of GRP78, and a variety of cellular processes were analyzed. We show that VCD was highly cytotoxic only under hypoglycemic conditions, but not in the presence of normal glucose levels, and VCD blocked GRP78 expression only when glycolysis was impaired (due to hypoglycemia or the presence of the glycolysis inhibitor 2-deoxyglucose), but not when GRP78 was induced by other means (hypoxia, thapsigargin, tunicamycin). However, VCD's strictly hypoglycemia-specific toxicity was not due to the inhibition of GRP78. Rather, VCD blocked mitochondrial energy production via inhibition of complex I of the electron transport chain. As a result, cellular ATP levels were quickly depleted under hypoglycemic conditions, and common cellular functions, including general protein synthesis, deteriorated and resulted in cell death. Altogether, our study identifies mitochondria as the primary target of VCD. The possibility that other purported GRP78 inhibitors (arctigenin, biguanides, deoxyverrucosidin, efrapeptin, JBIR, piericidin, prunustatin, pyrvinium, rottlerin, valinomycin, versipelostatin) might act in a similar GRP78-independent fashion will be discussed

    Syrbactin-class dual constitutive- and immuno-proteasome inhibitor TIR-199 impedes myeloma-mediated bone degeneration in vivo

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    Proteasome-addicted neoplastic malignancies present a considerable refractory and relapsed phenotype with patients exhibiting drug resistance and high mortality rates. To counter this global problem, novel proteasome-based therapies are being developed. In the current study, we extensively characterize TIR-199, a syrbactin-class proteasome inhibitor derived from a plant virulence factor of bacterium Pseudomonas syringae pv syringae. We report that TIR-199 is a potent constitutive and immunoproteasome inhibitor, capable of inducing cell death in multiple myeloma, triple-negative breast cancer, (TNBC) and non-small cell lung cancer lines. TIR-199 also effectively inhibits the proteasome in primary myeloma cells of patients, and bypasses the PSMB5 A49T+A50V bortezomib-resistant mutant. TIR-199 treatment leads to accumulation of canonical proteasome substrates in cells, it is specific, and does not inhibit 50 other enzymes tested in vitro. The drug exhibits synergistic cytotoxicity in combination with proteasome-activating kinase DYRK2 inhibitor LDN192960. Furthermore, low-doses of TIR-199 exhibits in vivo activity by delaying myeloma-mediated bone degeneration in a mouse xenograft model. Together, our data indicates that proteasome inhibitor TIR-199 could indeed be a promising next-generation drug within the repertoire of proteasome-based therapeutics

    A format for phylogenetic placements

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    We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g. short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements, and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.Comment: Documents version 3 of the forma

    TopiaryExplorer: visualizing large phylogenetic trees with environmental metadata

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    Motivation: Microbial community profiling is a highly active area of research, but tools that facilitate visualization of phylogenetic trees and associated environmental data have not kept up with the increasing quantity of data generated in these studies

    Library Design in Combinatorial Chemistry by Monte Carlo Methods

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    Strategies for searching the space of variables in combinatorial chemistry experiments are presented, and a random energy model of combinatorial chemistry experiments is introduced. The search strategies, derived by analogy with the computer modeling technique of Monte Carlo, effectively search the variable space even in combinatorial chemistry experiments of modest size. Efficient implementations of the library design and redesign strategies are feasible with current experimental capabilities.Comment: 5 pages, 3 figure

    Phylotastic! Making Tree-of-Life Knowledge Accessible, Reusable and Convenient

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    Scientists rarely reuse expert knowledge of phylogeny, in spite of years of effort to assemble a great "Tree of Life" (ToL). A notable exception involves the use of Phylomatic, which provides tools to generate custom phylogenies from a large, pre-computed, expert phylogeny of plant taxa. This suggests great potential for a more generalized system that, starting with a query consisting of a list of any known species, would rectify non-standard names, identify expert phylogenies containing the implicated taxa, prune away unneeded parts, and supply branch lengths and annotations, resulting in a custom phylogeny suited to the user's needs. Such a system could become a sustainable community resource if implemented as a distributed system of loosely coupled parts that interact through clearly defined interfaces. Results: With the aim of building such a "phylotastic" system, the NESCent Hackathons, Interoperability, Phylogenies (HIP) working group recruited 2 dozen scientist-programmers to a weeklong programming hackathon in June 2012. During the hackathon (and a three-month follow-up period), 5 teams produced designs, implementations, documentation, presentations, and tests including: (1) a generalized scheme for integrating components; (2) proof-of-concept pruners and controllers; (3) a meta-API for taxonomic name resolution services; (4) a system for storing, finding, and retrieving phylogenies using semantic web technologies for data exchange, storage, and querying; (5) an innovative new service, DateLife.org, which synthesizes pre-computed, time-calibrated phylogenies to assign ages to nodes; and (6) demonstration projects. These outcomes are accessible via a public code repository (GitHub.com), a website (www.phylotastic.org), and a server image. Conclusions: Approximately 9 person-months of effort (centered on a software development hackathon) resulted in the design and implementation of proof-of-concept software for 4 core phylotastic components, 3 controllers, and 3 end-user demonstration tools. While these products have substantial limitations, they suggest considerable potential for a distributed system that makes phylogenetic knowledge readily accessible in computable form. Widespread use of phylotastic systems will create an electronic marketplace for sharing phylogenetic knowledge that will spur innovation in other areas of the ToL enterprise, such as annotation of sources and methods and third-party methods of quality assessment.NESCent (the National Evolutionary Synthesis Center)NSF EF-0905606iPlant Collaborative (NSF) DBI-0735191Biodiversity Synthesis Center (BioSync) of the Encyclopedia of LifeComputer Science
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