Inhibition by small-molecule ligands of formation of amyloid fibrils of an immunoglobulin light chain variable domain.

Overproduction of immunoglobulin light chains leads to systemic amyloidosis, a lethal disease characterized by the formation of amyloid fibrils in patients' tissues. Excess light chains are in equilibrium between dimers and less stable monomers which can undergo irreversible aggregation to the amyloid state. The dimers therefore must disassociate into monomers prior to forming amyloid fibrils. Here we identify ligands that inhibit amyloid formation by stabilizing the Mcg light chain variable domain dimer and shifting the equilibrium away from the amyloid-prone monomer

Extradermal melanin transfer? : lack of macroscopic spleen melanization in old C57BL/6 mice with de-synchronized hair cycle

In quest of alternate, extradermal path of melanin transfer from skin to the visceral organs, we suggested that some portions of such melanin may be deposited in the spleen, which in young black C57BL/6 mice is often melanized. Here, we confirm these observation using young C57BL/6 female mice (up to 17 weeks) and show that this phenomenon cannot be observed in old animals where the hair cycle is not synchronized any more. The experiments were carried out both on spontaneous and depilation-induced hair cycle. We have checked it as a side-observation over many other experiments carried out on young and old C57BL/6 female mice (up to 2.5 years of life). The presence or absence of melanin in the spleens was checked macroscopically, and histologically by Fontana-Masson (FM) staining, and synchronization of the hair cycle - by standard histomorphometric analysis of the back skin hair follicles. In about 40% of old spleens black FM-stainable 'debris' could be found under closer histological examination. This study shows that, at least in part, the phenomenon of splenic melanosis in C57BL/6 mice can be correlated with the synchronized skin melanization parallel to the hair cycle progress, and that splenic melanin undergoes gradual degradation during the mouse life

Graph theoretic analysis of protein interaction networks of eukaryotes

Thanks to recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are universal across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and the yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interlogs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interlogs addition, for which we present a possible scenario through an in silico modeling.Comment: 7 pages, 6 figures, 2 table

Impact of observational incompleteness on the structural properties of protein interaction networks

The observed structure of protein interaction networks is corrupted by many false positive/negative links. This observational incompleteness is abstracted as random link removal and a specific, experimentally motivated (spoke) link rearrangement. Their impact on the structural properties of gene-duplication-and-mutation network models is studied. For the degree distribution a curve collapse is found, showing no sensitive dependence on the link removal/rearrangement strengths and disallowing a quantitative extraction of model parameters. The spoke link rearrangement process moves other structural observables, like degree correlations, cluster coefficient and motif frequencies, closer to their counterparts extracted from the yeast data. This underlines the importance to take a precise modeling of the observational incompleteness into account when network structure models are to be quantitatively compared to data.Comment: 17 pages, 7 figures, accepted by Physica

Numerical analysis of magnetic circuits in the ferrofluid seals

У статті представлені результати числових розрахунків магнітних ланцюгів з використанням методу кінцевих елементів. Описано процес моделювання ущільнень з феррорідиною, показаний вплив основних параметрів і геометрії ущільнення на розподіл магнітного поля. Показано можливість визначення розподілу магнітного поля в робочому зазорі ущільнення, що відіграє основну роль при визначенні максимального тиску, який сприймається ущільненням без втрати щільності й має вирішальне значення при виборі габаритів конструкції ущільнення.В статье представлены результаты численных расчетов магнитных цепей с использованием метода конечных элементов. Описывается моделирование уплотнений из феррожикостей, показано влияние основных параметров и геометрии уплотнения на распределение магнитного поля. Показана возможность определения распределения магнитного поля в рабочем зазоре уплотнения, что играет основную роль при определении максимального давления, которое воспринимается уплотнением без потери плотности и имеет решающее значение при выборе габаритов конструкции уплотнения.The article presents the results of numerical calculations of magnetic circuits using the finite element method. The modeling process of the seals with ferrofluid is described. The influence of the main parameters and geometry of the seal on the distribution of magnetic field is shown. The possibility of determining the distribution of the magnetic field in the working gap of seals, which plays a major role in determining the maximum pressure that is perceived by seal without losing density and is crucial in choosing the design dimensions of the seal

IsoBase: a database of functionally related proteins across PPI networks

We describe IsoBase, a database identifying functionally related proteins, across five major eukaryotic model organisms: Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus and Homo Sapiens. Nearly all existing algorithms for orthology detection are based on sequence comparison. Although these have been successful in orthology prediction to some extent, we seek to go beyond these methods by the integration of sequence data and protein–protein interaction (PPI) networks to help in identifying true functionally related proteins. With that motivation, we introduce IsoBase, the first publicly available ortholog database that focuses on functionally related proteins. The groupings were computed using the IsoRankN algorithm that uses spectral methods to combine sequence and PPI data and produce clusters of functionally related proteins. These clusters compare favorably with those from existing approaches: proteins within an IsoBase cluster are more likely to share similar Gene Ontology (GO) annotation. A total of 48 120 proteins were clustered into 12 693 functionally related groups. The IsoBase database may be browsed for functionally related proteins across two or more species and may also be queried by accession numbers, species-specific identifiers, gene name or keyword. The database is freely available for download at http://isobase.csail.mit.edu/.National Institute of General Medical Sciences (U.S.) (Grant Number 1R01GM081871)Fannie and John Hertz FoundationNational Science Foundation (U.S.) (NSF MSPRF)National Science Council of Taiwan (NSC99-2218-E-007-010)National Institutes of Health (U.S.) (1R01GM081871

The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins

Literature curation of protein interactions: measuring agreement across major public databases

Literature curation of protein interaction data faces a number of challenges. Although curators increasingly adhere to standard data representations, the data that various databases actually record from the same published information may differ significantly. Some of the reasons underlying these differences are well known, but their global impact on the interactions collectively curated by major public databases has not been evaluated. Here we quantify the agreement between curated interactions from 15 471 publications shared across nine major public databases. Results show that on average, two databases fully agree on 42% of the interactions and 62% of the proteins curated from the same publication. Furthermore, a sizable fraction of the measured differences can be attributed to divergent assignments of organism or splice isoforms, different organism focus and alternative representations of multi-protein complexes. Our findings highlight the impact of divergent curation policies across databases, and should be relevant to both curators and data consumers interested in analyzing protein-interaction data generated by the scientific community

PIG—the pathogen interaction gateway

Protein–protein interactions (PPIs) play a vital role in initiating infection in a number of pathogens. Identifying which interactions allow a pathogen to infect its host can help us to understand methods of pathogenesis and provide potential targets for therapeutics. Public resources for studying host–pathogen systems, in particular PPIs, are scarce. To facilitate the study of host–pathogen PPIs, we have collected and integrated host–pathogen PPI (HP–PPI) data from a number of public resources to create the Pathogen Interaction Gateway (PIG). PIG provides a text based search and a BLAST interface for searching the HP–PPI data. Each entry in PIG includes information such as the functional annotations and the domains present in the interacting proteins. PIG provides links to external databases to allow for easy navigation among the various websites. Additionally, PIG includes a tool for visualizing a single HP–PPI network or two HP–PPI networks. PIG can be accessed at http://pig.vbi.vt.edu

MatrixDB, the extracellular matrix interaction database

MatrixDB (http://matrixdb.ibcp.fr) is a freely available database focused on interactions established by extracellular proteins and polysaccharides. Only few databases report protein–polysaccharide interactions and, to the best of our knowledge, there is no other database of extracellular interactions. MatrixDB takes into account the multimeric nature of several extracellular protein families for the curation of interactions, and reports interactions with individual polypeptide chains or with multimers, considered as permanent complexes, when appropriate. MatrixDB is a member of the International Molecular Exchange consortium (IMEx) and has adopted the PSI-MI standards for the curation and the exchange of interaction data. MatrixDB stores experimental data from our laboratory, data from literature curation, data imported from IMEx databases, and data from the Human Protein Reference Database. MatrixDB is focused on mammalian interactions, but aims to integrate interaction datasets of model organisms when available. MatrixDB provides direct links to databases recapitulating mutations in genes encoding extracellular proteins, to UniGene and to the Human Protein Atlas that shows expression and localization of proteins in a large variety of normal human tissues and cells. MatrixDB allows researchers to perform customized queries and to build tissue- and disease-specific interaction networks that can be visualized and analyzed with Cytoscape or Medusa