Dynamic quantum clustering: a method for visual exploration of structures in data

A given set of data-points in some feature space may be associated with a Schrodinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schrodinger equation. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition or feature filtering.Comment: 15 pages, 9 figure

The N-end rule pathway is a sensor of heme

The conjugation of arginine, by arginyl-transferase, to N-terminal aspartate, glutamate or oxidized cysteine is a part of the N-end rule pathway of protein degradation. We report that arginyl-transferase of either the mouse or the yeast Saccharomyces cerevisiae is inhibited by hemin (Fe3+-heme). Furthermore, we show that hemin inhibits arginyl-transferase through a redox mechanism that involves the formation of disulfide between the enzyme's Cys-71 and Cys-72 residues. Remarkably, hemin also induces the proteasome-dependent degradation of arginyl-transferase in vivo, thus acting as both a "stoichiometric" and "catalytic" down-regulator of the N-end rule pathway. In addition, hemin was found to interact with the yeast and mouse E3 ubiquitin ligases of the N-end rule pathway. One of substrate-binding sites of the yeast N-end rule's ubiquitin ligase UBR1 targets CUP9, a transcriptional repressor. This site of UBR1 is autoinhibited but can be allosterically activated by peptides that bear destabilizing N-terminal residues and interact with two other substrate-binding sites of UBR1. We show that hemin does not directly occlude the substrate-binding sites of UBR1 but blocks the activation of its CUP9-binding site by dipeptides. The N-end rule pathway, a known sensor of short peptides, nitric oxide, and oxygen, is now a sensor of heme as well. One function of the N-end rule pathway may be to coordinate the activities of small effectors, both reacting to and controlling the redox dynamics of heme, oxygen, nitric oxide, thiols, and other compounds, in part through conditional degradation of specific transcription factors and G protein regulators

Regulatory mechanisms controlling biogenesis of ubiquitin and the proteasome

Analysis of several Saccharomyces cerevisiae ump mutants with defects in ubiquitin (Ub)-mediated proteolysis yielded insights into the regulation of the polyubiquitin gene UB14 and of proteasome genes. High-molecular weight Ub-protein conjugates accumulated in ump mutants with impaired proteasome function with a concomitant decrease in the amount of free Ub. In these mutants, transcriptional induction of UB14 was depending in part on the transcription factor Rpn4. Deletion of UB14 partially suppressed the growth defects of ump1 mutants, indicating that accumulation of polyubiquitylated proteins is deleterious to cell growth. Transcription of proteasome subunit genes was induced in ump mutants affecting the proteasome, as well as under conditions that mediate DNA damage or the formation of abnormal proteins. This induction required the transcriptional activator Rpn4. Elevated Rpn4 levels in proteasome-deficient mutants or as a response to abnormal proteins were due to increased metabolic stability. Up-regulation of proteasome genes in response to DNA damage, in contrast, is shown to operate via induction of RPN4 transcription. (C) 2004 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.info:eu-repo/semantics/publishedVersio

Fission yeast 26S proteasome mutants are multi-drug resistant due to stabilization of the pap1 transcription factor

Here we report the result of a genetic screen for mutants resistant to the microtubule poison methyl benzimidazol-2-yl carbamate (MBC) that were also temperature sensitive for growth. In total the isolated mutants were distributed in ten complementation groups. Cloning experiments revealed that most of the mutants were in essential genes encoding various 26S proteasome subunits. We found that the proteasome mutants are multi-drug resistant due to stabilization of the stress-activated transcription factor Pap1. We show that the ubiquitylation and ultimately the degradation of Pap1 depend on the Rhp6/Ubc2 E2 ubiquitin conjugating enzyme and the Ubr1 E3 ubiquitin-protein ligase. Accordingly, mutants lacking Rhp6 or Ubr1 display drug-resistant phenotypes

Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

BACKGROUND: A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. METHODOLOGY/PRINCIPAL FINDINGS: We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. CONCLUSIONS: Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide insights in erroneous and missed annotations