Identification of novel mutations in HFE, HFE2, TfR2, and SLC40A1 genes in Chinese patients affected by hereditary hemochromatosis.

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Wang, Yongwei; Du, Yali; Liu, Gang; Guo, Shanshan; Hou, Bo; Jiang, Xianyong; Han, Bing; Chang, Yanzhong; Nie, Guangjun

2017-04-01

Hereditary hemochromatosis (HH) is a group of inherited iron-overload disorders associated with pathogenic defects in the genes encoding hemochromatosis (HFE), hemojuvelin (HJV/HFE2), hepcidin (HAMP), transferrin receptor 2 (TfR2), and ferroportin (FPN1/SLC40A1) proteins, and the clinical features are well described. However, there have been only a few detailed reports of HH in Chinese populations. Thus, there is insufficient patient information for population-based analyses in Chinese populations or comparative studies among different ethical groups. In the current work, we describe eight Chinese cases of hereditary hemochromatosis. Gene sequencing results revealed eight mutations (five novel mutations) in HFE, HFE2, TfR2, and SLC40A1 genes in these Chinese HH patients. In addition, we used Polymorphism Phenotyping v2 (Polyphen), Sorting Intolerant From Tolerant (SIFT), and a sequence alignment program to predict the molecular consequences of missense mutations.

Manganese Transport and Toxicity in Polarized WIF-B Hepatocytes.

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Thompson, Khristy J; Hein, Jennifer; Baez, Andrew; Sosa, Jose Carlo; Wessling-Resnick, Marianne

2018-05-24

Mn toxicity arises from nutritional problems, community and occupational exposures, and genetic risks. Mn blood levels are controlled by hepatobiliary clearance. The goals of this study were to determine the cellular distribution of Mn transporters in polarized hepatocytes, to establish an in vitro assay for hepatocyte Mn efflux, and to examine possible roles the Mn transporters would play in metal import and export. For these experiments, hepatocytoma WIF-B cells were grown for 12-14 days to achieve maximal polarity. Immunoblots showed that Mn transporters ZIP8, ZnT10, ferroportin (Fpn), and ZIP14 were present. Indirect immunofluorescence microscopy localized Fpn and ZIP14 to WIF-B cell basolateral domains while ZnT10 and ZIP8 associated with intracellular vesicular compartments. ZIP8-positive structures were distributed uniformly throughout the cytoplasm, but ZnT10-positive vesicles were adjacent to apical bile compartments. WIF-B cells were sensitive to Mn toxicity, showing decreased viability after 16 h exposure to > 250 M MnCl2. However, the hepatocytes were resistant to 4 h exposures of up to 500 M MnCl2 despite 50-fold increased Mn content. Washout experiments showed time-dependent efflux with 80% Mn released after a 4 h chase period. Hepcidin reduced levels of Fpn in WIF-B cells, clearing Fpn from the cell surface, but Mn efflux was unaffected. The secretory inhibitor brefeldin A did block release of Mn from WIF-B cells, suggesting vesicle fusion may be involved in export. These results point to a possible role of ZnT10 to import Mn into vesicles that subsequently fuse with the apical membrane and empty their contents into bile.

Chaperone turns gatekeeper: PCBP2 and DMT1 form an iron-transport pipeline.

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Lane, Darius J R; Richardson, Des R

2014-08-15

How is cellular iron (Fe) uptake and efflux regulated in mammalian cells? In this issue of the Biochemical Journal, Yanatori et al. report for the first time that a member of the emerging PCBP [poly(rC)-binding protein] Fe-chaperone family, PCBP2, physically interacts with the major Fe importer DMT1 (divalent metal transporter 1) and the Fe exporter FPN1 (ferroportin 1). In both cases, the interaction of the Fe transporter with PCBP2 is Fe-dependent. Interestingly, another PCBP Fe-chaperone, PCBP1, does not appear to bind to DMT1. Strikingly, the PCBP2-DMT1 interaction is required for DMT1-dependent cellular Fe uptake, suggesting that, in addition to functioning as an intracellular Fe chaperone, PCBP2 may be a molecular 'gate- keeper' for transmembrane Fe transport. These new data hint at the possibility that PCBP2 may be a component of a yet-to-be-described Fe-transport metabolon that engages in Fe channelling to and from Fe transporters and intracellular sites.

Estrogen-dependent changes in serum iron levels as a translator of the adverse effects of estrogen during infection: a conceptual framework.

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Hamad, Mawieh; Awadallah, Samir

2013-12-01

Elevated levels of estrogen often associate with increased susceptibility to infection. This has been attributed to the ability of estrogen to concomitantly enhance the growth and virulence of pathogens and suppress host immunity. But the exact mechanism of how estrogen mediates such effects, especially in cases where the pathogen and/or the immune components in question do not express estrogen receptors, has yet to be elucidated. Here we propose that translating the adverse effects of estrogen during infection is dependent to a significant degree upon its ability to manipulate iron homeostasis. For elevated levels of estrogen alter the synthesis and/or activity of several factors involved in iron metabolism including hypoxia inducible factor 1α (HIF-1α) and hepcidin among others. This leads to the inhibition of hepcidin synthesis in hepatocytes and the maintenance of ferroportin (FPN) integrity on the surface of iron-releasing duodenal enterocytes, hepatocytes, and macrophages. Intact FPN permits the continuous efflux of dietary and stored iron into the circulation, which further enhances pathogen growth and virulence on the one hand and suppresses host immunity on the other. This new conceptual framework may help explain a multitude of disparate clinical and experimental observations pertinent to the relationship between estrogen and infection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Iron addiction: a novel therapeutic target in ovarian cancer

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Basuli, D.

2017-01-01

Ovarian cancer is a lethal malignancy that has not seen a major therapeutic advance in over 30 years. We demonstrate that ovarian cancer exhibits a targetable alteration in iron metabolism. Ferroportin (FPN), the iron efflux pump, is decreased, and transferrin receptor (TFR1), the iron importer, is increased in tumor tissue from patients with high grade but not low grade serous ovarian cancer. A similar profile of decreased FPN and increased TFR1 is observed in a genetic model of ovarian cancer tumor-initiating cells (TICs). The net result of these changes is an accumulation of excess intracellular iron and an augmented dependence on iron for proliferation. A forced reduction in intracellular iron reduces the proliferation of ovarian cancer TICs in vitro, and inhibits both tumor growth and intraperitoneal dissemination of tumor cells in vivo. Some mechanistic studies demonstrate that iron increases metastatic spread by facilitating invasion through expression of matrix metalloproteases and synthesis of interleukin 6 (IL-6). Here, we show that the iron dependence of ovarian cancer TICs renders them exquisitely sensitive in vivo to agents that induce iron-dependent cell death (ferroptosis) as well as iron chelators, and thus creates a metabolic vulnerability that can be exploited therapeutically.

Role of hepcidin-ferroportin axis in the pathophysiology, diagnosis, and treatment of anemia of chronic inflammation.

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Langer, Arielle L; Ginzburg, Yelena Z

2017-06-01

Anemia of chronic inflammation (ACI) is a frequently diagnosed anemia and portends an independently increased morbidity and poor outcome associated with multiple underlying diseases. The pathophysiology of ACI is multifactorial, resulting from the effects of inflammatory cytokines which both directly and indirectly suppress erythropoiesis. Recent advances in molecular understanding of iron metabolism provide strong evidence that immune mediators, such as IL-6, lead to hepcidin-induced hypoferremia, iron sequestration, and decreased iron availability for erythropoiesis. The role of hepcidin-ferroportin axis in the pathophysiology of ACI is stimulating the development of new diagnostics and targeted therapies. In this review, we present an overview of and rationale for inflammation-, iron-, and erythropoiesis-related strategies currently in development. © 2017 International Society for Hemodialysis.

Disruption of the Hepcidin/Ferroportin Regulatory System Causes Pulmonary Iron Overload and Restrictive Lung Disease

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Joana Neves

2017-06-01

Full Text Available Emerging evidence suggests that pulmonary iron accumulation is implicated in a spectrum of chronic lung diseases. However, the mechanism(s involved in pulmonary iron deposition and its role in the in vivo pathogenesis of lung diseases remains unknown. Here we show that a point mutation in the murine ferroportin gene, which causes hereditary hemochromatosis type 4 (Slc40a1C326S, increases iron levels in alveolar macrophages, epithelial cells lining the conducting airways and lung parenchyma, and in vascular smooth muscle cells. Pulmonary iron overload is associated with oxidative stress, restrictive lung disease with decreased total lung capacity and reduced blood oxygen saturation in homozygous Slc40a1C326S/C326S mice compared to wild-type controls. These findings implicate iron in lung pathology, which is so far not considered a classical iron-related disorder.

Current understanding of iron homeostasis.

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Anderson, Gregory J; Frazer, David M

2017-12-01

Iron is an essential trace element, but it is also toxic in excess, and thus mammals have developed elegant mechanisms for keeping both cellular and whole-body iron concentrations within the optimal physiologic range. In the diet, iron is either sequestered within heme or in various nonheme forms. Although the absorption of heme iron is poorly understood, nonheme iron is transported across the apical membrane of the intestinal enterocyte by divalent metal-ion transporter 1 (DMT1) and is exported into the circulation via ferroportin 1 (FPN1). Newly absorbed iron binds to plasma transferrin and is distributed around the body to sites of utilization with the erythroid marrow having particularly high iron requirements. Iron-loaded transferrin binds to transferrin receptor 1 on the surface of most body cells, and after endocytosis of the complex, iron enters the cytoplasm via DMT1 in the endosomal membrane. This iron can be used for metabolic functions, stored within cytosolic ferritin, or exported from the cell via FPN1. Cellular iron concentrations are modulated by the iron regulatory proteins (IRPs) IRP1 and IRP2. At the whole-body level, dietary iron absorption and iron export from the tissues into the plasma are regulated by the liver-derived peptide hepcidin. When tissue iron demands are high, hepcidin concentrations are low and vice versa. Too little or too much iron can have important clinical consequences. Most iron deficiency reflects an inadequate supply of iron in the diet, whereas iron excess is usually associated with hereditary disorders. These disorders include various forms of hemochromatosis, which are characterized by inadequate hepcidin production and, thus, increased dietary iron intake, and iron-loading anemias whereby both increased iron absorption and transfusion therapy contribute to the iron overload. Despite major recent advances, much remains to be learned about iron physiology and pathophysiology. © 2017 American Society for Nutrition.

Experimental characterization of a 10 μW 55 μm-pitch FPN-compensated CMOS digital pixel sensor for X-ray imagers

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Figueras, Roger, E-mail: roger.figueras@imb-cnm.csic.es [Institut de Microelectrònica de Barcelona IMB-CNM(CSIC), Bellaterra (Spain); Martínez, Ricardo; Terés, Lluís [Institut de Microelectrònica de Barcelona IMB-CNM(CSIC), Bellaterra (Spain); Serra-Graells, Francisco [Institut de Microelectrònica de Barcelona IMB-CNM(CSIC), Bellaterra (Spain); Department of Microelectronics and Electronic Systems, Universitat Autònoma de Barcelona, Bellaterra (Spain)

2014-10-11

This paper presents experimental results obtained from both electrical and radiation tests of a new room-temperature digital pixel sensor (DPS) circuit specifically optimized for digital direct X-ray imaging. The 10 μW 55 μm-pitch CMOS active pixel circuit under test includes self-bias capability, built-in test, selectable e{sup −}/h{sup +} collection, 10-bit charge-integration A/D conversion, individual gain tuning for fixed pattern noise (FPN) cancellation, and digital-only I/O interface, which make it suitable for 2D modular chip assemblies in large and seamless sensing areas. Experimental results for this DPS architecture in 0.18 μm 1P6M CMOS technology are reported, returning good performance in terms of linearity, 2ke{sub rms}{sup −} of ENC, inter-pixel crosstalk below 0.5 LSB, 50 Mbps of I/O speed, and good radiation response for its use in digital X-ray imaging.

Lactoferrin Efficiently Counteracts the Inflammation-Induced Changes of the Iron Homeostasis System in Macrophages.

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Cutone, Antimo; Rosa, Luigi; Lepanto, Maria Stefania; Scotti, Mellani Jinnett; Berlutti, Francesca; Bonaccorsi di Patti, Maria Carmela; Musci, Giovanni; Valenti, Piera

2017-01-01

Human lactoferrin (hLf), an 80-kDa multifunctional iron-binding cationic glycoprotein, is constitutively secreted by exocrine glands and by neutrophils during inflammation. hLf is recognized as a key element in the host immune defense system. The in vitro and in vivo experiments are carried out with bovine Lf (bLf), which shares high sequence homology and identical functions with hLf, including anti-inflammatory activity. Here, in "pure" M1 human macrophages, obtained by stimulation with a mixture of 10 pg/ml LPS and 20 ng/ml IFN-γ, as well as in a more heterogeneous macrophage population, challenged with high-dose of LPS (1 µg/ml), the effect of bLf on the expression of the main proteins involved in iron and inflammatory homeostasis, namely ferroportin (Fpn), membrane-bound ceruloplasmin (Cp), cytosolic ferritin (Ftn), transferrin receptor 1, and cytokines has been investigated. The increase of IL-6 and IL-1β cytokines, following the inflammatory treatments, is associated with both upregulation of cytosolic Ftn and downregulation of Fpn, membrane-bound Cp, and transferrin receptor 1. All these changes take part into intracellular iron overload, a very unsafe condition leading in vivo to higher host susceptibility to infections as well as iron deficiency in the blood and anemia of inflammation. It is, therefore, of utmost importance to counteract the persistence of the inflammatory status to rebalance iron levels between tissues/secretions and blood. Moreover, levels of the antiinflammatory cytokine IL-10 were increased in cells treated with high doses of LPS. Conversely, IL-10 decreased when the LPS/IFN-γ mix was used, suggesting that only the inflammation triggered by LPS high doses can switch on an anti-inflammatory response in our macrophagic model. Here, we demonstrate that bLf, when included in the culture medium, significantly reduced IL-6 and IL-1β production and efficiently prevented the changes of Fpn, membrane-bound Cp, cytosolic Ftn, and

Lactoferrin Efficiently Counteracts the Inflammation-Induced Changes of the Iron Homeostasis System in Macrophages

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Antimo Cutone

2017-06-01

Full Text Available Human lactoferrin (hLf, an 80-kDa multifunctional iron-binding cationic glycoprotein, is constitutively secreted by exocrine glands and by neutrophils during inflammation. hLf is recognized as a key element in the host immune defense system. The in vitro and in vivo experiments are carried out with bovine Lf (bLf, which shares high sequence homology and identical functions with hLf, including anti-inflammatory activity. Here, in “pure” M1 human macrophages, obtained by stimulation with a mixture of 10 pg/ml LPS and 20 ng/ml IFN-γ, as well as in a more heterogeneous macrophage population, challenged with high-dose of LPS (1 µg/ml, the effect of bLf on the expression of the main proteins involved in iron and inflammatory homeostasis, namely ferroportin (Fpn, membrane-bound ceruloplasmin (Cp, cytosolic ferritin (Ftn, transferrin receptor 1, and cytokines has been investigated. The increase of IL-6 and IL-1β cytokines, following the inflammatory treatments, is associated with both upregulation of cytosolic Ftn and downregulation of Fpn, membrane-bound Cp, and transferrin receptor 1. All these changes take part into intracellular iron overload, a very unsafe condition leading in vivo to higher host susceptibility to infections as well as iron deficiency in the blood and anemia of inflammation. It is, therefore, of utmost importance to counteract the persistence of the inflammatory status to rebalance iron levels between tissues/secretions and blood. Moreover, levels of the antiinflammatory cytokine IL-10 were increased in cells treated with high doses of LPS. Conversely, IL-10 decreased when the LPS/IFN-γ mix was used, suggesting that only the inflammation triggered by LPS high doses can switch on an anti-inflammatory response in our macrophagic model. Here, we demonstrate that bLf, when included in the culture medium, significantly reduced IL-6 and IL-1β production and efficiently prevented the changes of Fpn, membrane-bound Cp

EGCG Protects against 6-OHDA-Induced Neurotoxicity in a Cell Culture Model

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Dan Chen

2015-01-01

Full Text Available Background. Parkinson’s disease (PD is a progressive neurodegenerative disease that causes severe brain dopamine depletion. Disruption of iron metabolism may be involved in the PD progression. Objective. To test the protective effect of (−-epigallocatechin-3-gallate (EGCG against 6-hydroxydopamine- (6-OHDA- induced neurotoxicity by regulating iron metabolism in N27 cells. Methods. Protection by EGCG in N27 cells was assessed by SYTOX green assay, MTT, and caspase-3 activity. Iron regulatory gene and protein expression were measured by RT-PCR and Western blotting. Intracellular iron uptake was measured using 55Fe. The EGCG protection was further tested in primary mesencephalic dopaminergic neurons by immunocytochemistry. Results. EGCG protected against 6-OHDA-induced cell toxicity. 6-OHDA treatment significantly (p<0.05 increased divalent metal transporter-1 (DMT1 and hepcidin and decreased ferroportin 1 (Fpn1 level, whereas pretreatment with EGCG counteracted the effects. The increased 55Fe (by 96%, p<0.01 cell uptake confirmed the iron burden by 6-OHDA and was reduced by EGCG by 27% (p<0.05, supporting the DMT1 results. Pretreatment with EGCG and 6-OHDA significantly increased (p<0.0001 TH+ cell count (~3-fold and neurite length (~12-fold compared to 6-OHDA alone in primary mesencephalic neurons. Conclusions. Pretreatment with EGCG protected against 6-OHDA-induced neurotoxicity by regulating genes and proteins involved in brain iron homeostasis, especially modulating hepcidin levels.

Aspirin down Regulates Hepcidin by Inhibiting NF-κB and IL6/JAK2/STAT3 Pathways in BV-2 Microglial Cells Treated with Lipopolysaccharide

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Wan-Ying Li

2016-12-01

Full Text Available Aspirin down regulates transferrin receptor 1 (TfR1 and up regulates ferroportin 1 (Fpn1 and ferritin expression in BV-2 microglial cells treated without lipopolysaccharides (LPS, as well as down regulates hepcidin and interleukin 6 (IL-6 in cells treated with LPS. However, the relevant mechanisms are unknown. Here, we investigate the effects of aspirin on expression of hepcidin and iron regulatory protein 1 (IRP1, phosphorylation of Janus kinase 2 (JAK2, signal transducer and activator of transcription 3 (STAT3 and P65 (nuclear factor-κB, and the production of nitric oxide (NO in BV-2 microglial cells treated with and without LPS. We demonstrated that aspirin inhibited hepcidin mRNA as well as NO production in cells treated with LPS, but not in cells without LPS, suppresses IL-6, JAK2, STAT3, and P65 (nuclear factor-κB phosphorylation and has no effect on IRP1 in cells treated with or without LPS. These findings provide evidence that aspirin down regulates hepcidin by inhibiting IL6/JAK2/STAT3 and P65 (nuclear factor-κB pathways in the cells under inflammatory conditions, and imply that an aspirin-induced reduction in TfR1 and an increase in ferritin are not associated with IRP1 and NO.

Effects of acute dietary iron overload in pigs (Sus scrofa) with induced type 2 diabetes mellitus.

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Espinoza, A; Morales, S; Arredondo, M

2014-06-01

Epidemiological studies have reported an association between high iron (Fe) levels and elevated risk of developing type 2 diabetes mellitus (T2D). It is believed that the formation of Fe-catalyzed hydroxyl radicals may contribute to the development of diabetes. Our goal was to determine the effect of a diet with a high Fe content on type 2 diabetic pigs. Four groups of piglets were studied: (1) control group, basal diet; (2) Fe group, basal diet with 3,000 ppm ferrous sulfate; (3) diabetic group (streptozotocin-induced type 2 diabetes) with basal diet; (4) diabetic/Fe group, diabetic animals/3,000 ppm ferrous sulfate. For 2 months, biochemical and hematological parameters were evaluated. Tissue samples of liver and duodenum were obtained to determine mRNA relative abundance of DMT1, ferroportin (Fpn), ferritin (Fn), hepcidin (Hpc), and transferrin receptor by qRT-PCR. Fe group presented increased levels of hematological (erythrocytes, hematocrit, and hemoglobin) and iron parameters. Diabetic/Fe group showed similar behavior as Fe group but in lesser extent. The relative abundance of different genes in the four study groups yielded a different expression pattern. DMT1 showed a lower expression in the two iron groups compared with control and diabetic animals, and Hpc showed an increased on its expression in Fe and diabetic/Fe groups. Diabetic/Fe group presents greater expression of Fn and Fpn. These results suggest that there is an interaction between Fe nutrition, inflammation, and oxidative stress in the diabetes development.

Modelling Systemic Iron Regulation during Dietary Iron Overload and Acute Inflammation: Role of Hepcidin-Independent Mechanisms.

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Enculescu, Mihaela; Metzendorf, Christoph; Sparla, Richard; Hahnel, Maximilian; Bode, Johannes; Muckenthaler, Martina U; Legewie, Stefan

2017-01-01

Systemic iron levels must be maintained in physiological concentrations to prevent diseases associated with iron deficiency or iron overload. A key role in this process plays ferroportin, the only known mammalian transmembrane iron exporter, which releases iron from duodenal enterocytes, hepatocytes, or iron-recycling macrophages into the blood stream. Ferroportin expression is tightly controlled by transcriptional and post-transcriptional mechanisms in response to hypoxia, iron deficiency, heme iron and inflammatory cues by cell-autonomous and systemic mechanisms. At the systemic level, the iron-regulatory hormone hepcidin is released from the liver in response to these cues, binds to ferroportin and triggers its degradation. The relative importance of individual ferroportin control mechanisms and their interplay at the systemic level is incompletely understood. Here, we built a mathematical model of systemic iron regulation. It incorporates the dynamics of organ iron pools as well as regulation by the hepcidin/ferroportin system. We calibrated and validated the model with time-resolved measurements of iron responses in mice challenged with dietary iron overload and/or inflammation. The model demonstrates that inflammation mainly reduces the amount of iron in the blood stream by reducing intracellular ferroportin transcription, and not by hepcidin-dependent ferroportin protein destabilization. In contrast, ferroportin regulation by hepcidin is the predominant mechanism of iron homeostasis in response to changing iron diets for a big range of dietary iron contents. The model further reveals that additional homeostasis mechanisms must be taken into account at very high dietary iron levels, including the saturation of intestinal uptake of nutritional iron and the uptake of circulating, non-transferrin-bound iron, into liver. Taken together, our model quantitatively describes systemic iron metabolism and generated experimentally testable predictions for additional

Obesity as an Emerging Risk Factor for Iron Deficiency

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Elmar Aigner

2014-09-01

Full Text Available Iron homeostasis is affected by obesity and obesity-related insulin resistance in a many-facetted fashion. On one hand, iron deficiency and anemia are frequent findings in subjects with progressed stages of obesity. This phenomenon has been well studied in obese adolescents, women and subjects undergoing bariatric surgery. On the other hand, hyperferritinemia with normal or mildly elevated transferrin saturation is observed in approximately one-third of patients with metabolic syndrome (MetS or nonalcoholic fatty liver disease (NAFLD. This constellation has been named the “dysmetabolic iron overload syndrome (DIOS”. Both elevated body iron stores and iron deficiency are detrimental to health and to the course of obesity-related conditions. Iron deficiency and anemia may impair mitochondrial and cellular energy homeostasis and further increase inactivity and fatigue of obese subjects. Obesity-associated inflammation is tightly linked to iron deficiency and involves impaired duodenal iron absorption associated with low expression of duodenal ferroportin (FPN along with elevated hepcidin concentrations. This review summarizes the current understanding of the dysregulation of iron homeostasis in obesity.

Two novel mutations in the SLC40A1 and HFE genes implicated in iron overload in a Spanish man.

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Del-Castillo-Rueda, Alejandro; Moreno-Carralero, María-Isabel; Alvarez-Sala-Walther, Luis-Antonio; Cuadrado-Grande, Nuria; Enríquez-de-Salamanca, Rafael; Méndez, Manuel; Morán-Jiménez, María-Josefa

2011-03-01

The most common form of hemochromatosis is caused by mutations in the HFE gene. Rare forms of the disease are caused by mutations in other genes. We present a patient with hyperferritinemia and iron overload, and facial flushing. Magnetic resonance imaging was performed to measure hepatic iron overload, and a molecular study of the genes involved in iron metabolism was undertaken. The iron overload was similar to that observed in HFE hemochromatosis, and the patient was double heterozygous for two novel mutations, c.-20G>A and c.718A>G (p.K240E), in the HFE and ferroportin (FPN1 or SLC40A1) genes, respectively. Hyperferritinemia and facial flushing improved after phlebotomy. Two of the patient's children were also studied, and the daughter was heterozygous for the mutation in the SLC40A1 gene, although she did not have hyperferritinemia. The patient presented a mild iron overload phenotype probably because of the two novel mutations in the HFE and SLC40A1 genes. © 2011 John Wiley & Sons A/S.

Cytosolic iron chaperones: Proteins delivering iron cofactors in the cytosol of mammalian cells.

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Philpott, Caroline C; Ryu, Moon-Suhn; Frey, Avery; Patel, Sarju

2017-08-04

Eukaryotic cells contain hundreds of metalloproteins that are supported by intracellular systems coordinating the uptake and distribution of metal cofactors. Iron cofactors include heme, iron-sulfur clusters, and simple iron ions. Poly(rC)-binding proteins are multifunctional adaptors that serve as iron ion chaperones in the cytosolic/nuclear compartment, binding iron at import and delivering it to enzymes, for storage (ferritin) and export (ferroportin). Ferritin iron is mobilized by autophagy through the cargo receptor, nuclear co-activator 4. The monothiol glutaredoxin Glrx3 and BolA2 function as a [2Fe-2S] chaperone complex. These proteins form a core system of cytosolic iron cofactor chaperones in mammalian cells. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Iron and iron-related proteins in asbestosis.

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ABSTRACT: We tested the postulate that iron homeostasis is altered among patients diagnosed to have asbestosis. Lung tissue from six individuals diagnosed to have had asbestosis at autopsy was stained for iron, ferritin, divalent metal transporter 1 (DMT1), and ferroportin 1 (FP...

Nramp1 promotes efficient macrophage recycling of iron following erythrophagocytosis in vivo.

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Soe-Lin, Shan; Apte, Sameer S; Andriopoulos, Billy; Andrews, Marc C; Schranzhofer, Matthias; Kahawita, Tanya; Garcia-Santos, Daniel; Ponka, Prem

2009-04-07

Natural resistance-associated macrophage protein 1 (Nramp1) is a divalent metal transporter expressed exclusively in phagocytic cells. We hypothesized that macrophage Nramp1 may participate in the recycling of iron acquired from phagocytosed senescent erythrocytes. To evaluate the role of Nramp1 in vivo, the iron parameters of WT and KO mice were analyzed after acute and chronic induction of hemolytic anemia. We found that untreated KO mice exhibited greater serum transferrin saturation and splenic iron content with higher duodenal ferroportin (Fpn) and divalent metal transporter 1 (DMT1) expression. Furthermore, hepatocyte iron content and hepcidin mRNA levels were dramatically lower in KO mice, indicating that hepcidin levels can be regulated by low-hepatocyte iron stores despite increased transferrin saturation. After acute treatment with the hemolytic agent phenylhydrazine (Phz), KO mice experienced a significant decrease in transferrin saturation and hematocrit, whereas WT mice were relatively unaffected. After a month-long Phz regimen, KO mice retained markedly increased quantities of iron within the liver and spleen and exhibited more pronounced splenomegaly and reticulocytosis than WT mice. After injection of (59)Fe-labeled heat-damaged reticulocytes, KO animals accumulated erythrophagocytosed (59)Fe within their liver and spleen, whereas WT animals efficiently recycled phagocytosed (59)Fe to the marrow and erythrocytes. These data imply that without Nramp1, iron accumulates within the liver and spleen during erythrophagocytosis and hemolytic anemia, supporting our hypothesis that Nramp1 promotes efficient hemoglobin iron recycling in macrophages. Our observations suggest that mutations in Nramp1 could result in a novel form of human hereditary iron overload.

Copper Deficiency Leads to Anemia, Duodenal Hypoxia, Upregulation of HIF-2α and Altered Expression of Iron Absorption Genes in Mice

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Matak, Pavle; Zumerle, Sara; Mastrogiannaki, Maria; El Balkhi, Souleiman; Delga, Stephanie; Mathieu, Jacques R. R.; Canonne-Hergaux, François; Poupon, Joel; Sharp, Paul A.; Vaulont, Sophie; Peyssonnaux, Carole

2013-01-01

Iron and copper are essential trace metals, actively absorbed from the proximal gut in a regulated fashion. Depletion of either metal can lead to anemia. In the gut, copper deficiency can affect iron absorption through modulating the activity of hephaestin - a multi-copper oxidase required for optimal iron export from enterocytes. How systemic copper status regulates iron absorption is unknown. Mice were subjected to a nutritional copper deficiency-induced anemia regime from birth and injected with copper sulphate intraperitoneally to correct the anemia. Copper deficiency resulted in anemia, increased duodenal hypoxia and Hypoxia inducible factor 2α (HIF-2α) levels, a regulator of iron absorption. HIF-2α upregulation in copper deficiency appeared to be independent of duodenal iron or copper levels and correlated with the expression of iron transporters (Ferroportin - Fpn, Divalent Metal transporter – Dmt1) and ferric reductase – Dcytb. Alleviation of copper-dependent anemia with intraperitoneal copper injection resulted in down regulation of HIF-2α-regulated iron absorption genes in the gut. Our work identifies HIF-2α as an important regulator of iron transport machinery in copper deficiency. PMID:23555700

Expression and cellular localization of hepcidin mRNA and protein in normal rat brain

Czech Academy of Sciences Publication Activity Database

Raha-Chowdhury, R.; Raha, A.A.; Forostyak, Serhiy; Zhao, J.W.; Stott, S.R.W.; Bomford, A.

2015-01-01

Roč. 16, APR 21 (2015), s. 24 ISSN 1471-2202 Institutional support: RVO:68378041 Keywords : hepcidin * ferroportin * defensin * inflammatory cytokines * brain iron homeostasis * blood brain barrier * pericytes * sub-ventricular zone * neurogenesis Subject RIV: FH - Neurology Impact factor: 2.304, year: 2015

Multi-Copper Oxidases and Human Iron Metabolism

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Vashchenko, Ganna; MacGillivray, Ross T. A.

2013-01-01

Multi-copper oxidases (MCOs) are a small group of enzymes that oxidize their substrate with the concomitant reduction of dioxygen to two water molecules. Generally, multi-copper oxidases are promiscuous with regards to their reducing substrates and are capable of performing various functions in different species. To date, three multi-copper oxidases have been detected in humans—ceruloplasmin, hephaestin and zyklopen. Each of these enzymes has a high specificity towards iron with the resulting ferroxidase activity being associated with ferroportin, the only known iron exporter protein in humans. Ferroportin exports iron as Fe2+, but transferrin, the major iron transporter protein of blood, can bind only Fe3+ effectively. Iron oxidation in enterocytes is mediated mainly by hephaestin thus allowing dietary iron to enter the bloodstream. Zyklopen is involved in iron efflux from placental trophoblasts during iron transfer from mother to fetus. Release of iron from the liver relies on ferroportin and the ferroxidase activity of ceruloplasmin which is found in blood in a soluble form. Ceruloplasmin, hephaestin and zyklopen show distinctive expression patterns and have unique mechanisms for regulating their expression. These features of human multi-copper ferroxidases can serve as a basis for the precise control of iron efflux in different tissues. In this manuscript, we review the biochemical and biological properties of the three human MCOs and discuss their potential roles in human iron homeostasis. PMID:23807651

Hepcidin regulation in wild-type and Hfe knockout mice in response to alcohol consumption: evidence for an alcohol-induced hypoxic response.

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Heritage, Mandy L; Murphy, Therese L; Bridle, Kim R; Anderson, Gregory J; Crawford, Darrell H G; Fletcher, Linda M

2009-08-01

Expression of Hamp1, the gene encoding the iron regulatory peptide hepcidin, is inappropriately low in HFE-associated hereditary hemochromatosis and Hfe knockout mice (Hfe(-/-)). Since chronic alcohol consumption is also associated with disturbances in iron metabolism, we investigated the effects of alcohol consumption on hepcidin mRNA expression in Hfe(-/-) mice. Hfe(-/-) and C57BL/6 (wild-type) mice were pair-fed either an alcohol liquid diet or control diet for up to 8 weeks. The mRNA levels of hepcidin and ferroportin were measured at the mRNA level by RT-PCR and protein expression of hypoxia inducible factor-1 alpha (HIF-1alpha) was measured by western blot. Hamp1 mRNA expression was significantly decreased and duodenal ferroportin expression was increased in alcohol-fed wild-type mice at 8 weeks. Time course experiments showed that the decrease in hepcidin mRNA was not immediate, but was significant by 4 weeks. Consistent with the genetic defect, Hamp1 mRNA was decreased and duodenal ferroportin mRNA expression was increased in Hfe(-/-) mice fed on the control diet compared with wild-type animals and alcohol further exacerbated these effects. HIF-1alpha protein levels were elevated in alcohol-fed wild-type animals compared with controls. Alcohol may decrease Hamp1 gene expression independently of the HFE pathway possibly via alcohol-induced hypoxia.

Understanding the management of iron deficiency anaemia

African Journals Online (AJOL)

impact on cellular respiration and ATP production, which in turn, decreases DNA ... by stimulating the degradation of ferroportin, the protein responsible for the ... to respond to oral iron therapy after 4 to 6 weeks (an increase of less than 1 g ...

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

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Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

2015-09-16

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

Hepcidin mediates transcriptional changes that modulate acute cytokine-induced inflammatory responses in mice.

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De Domenico, Ivana; Zhang, Tian Y; Koening, Curry L; Branch, Ryan W; London, Nyall; Lo, Eric; Daynes, Raymond A; Kushner, James P; Li, Dean; Ward, Diane M; Kaplan, Jerry

2010-07-01

Hepcidin is a peptide hormone that regulates iron homeostasis and acts as an antimicrobial peptide. It is expressed and secreted by a variety of cell types in response to iron loading and inflammation. Hepcidin mediates iron homeostasis by binding to the iron exporter ferroportin, inducing its internalization and degradation via activation of the protein kinase Jak2 and the subsequent phosphorylation of ferroportin. Here we have shown that hepcidin-activated Jak2 also phosphorylates the transcription factor Stat3, resulting in a transcriptional response. Hepcidin treatment of ferroportin-expressing mouse macrophages showed changes in mRNA expression levels of a wide variety of genes. The changes in transcript levels for half of these genes were a direct effect of hepcidin, as shown by cycloheximide insensitivity, and dependent on the presence of Stat3. Hepcidin-mediated transcriptional changes modulated LPS-induced transcription in both cultured macrophages and in vivo mouse models, as demonstrated by suppression of IL-6 and TNF-alpha transcript and secreted protein. Hepcidin-mediated transcription in mice also suppressed toxicity and morbidity due to single doses of LPS, poly(I:C), and turpentine, which is used to model chronic inflammatory disease. Most notably, we demonstrated that hepcidin pretreatment protected mice from a lethal dose of LPS and that hepcidin-knockout mice could be rescued from LPS toxicity by injection of hepcidin. The results of our study suggest a new function for hepcidin in modulating acute inflammatory responses.

Suppression of iron-regulatory hepcidin by vitamin D.

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Bacchetta, Justine; Zaritsky, Joshua J; Sea, Jessica L; Chun, Rene F; Lisse, Thomas S; Zavala, Kathryn; Nayak, Anjali; Wesseling-Perry, Katherine; Westerman, Mark; Hollis, Bruce W; Salusky, Isidro B; Hewison, Martin

2014-03-01

The antibacterial protein hepcidin regulates the absorption, tissue distribution, and extracellular concentration of iron by suppressing ferroportin-mediated export of cellular iron. In CKD, elevated hepcidin and vitamin D deficiency are associated with anemia. Therefore, we explored a possible role for vitamin D in iron homeostasis. Treatment of cultured hepatocytes or monocytes with prohormone 25-hydroxyvitamin D or active 1,25-dihydroxyvitamin D decreased expression of hepcidin mRNA by 0.5-fold, contrasting the stimulatory effect of 25-hydroxyvitamin D or 1,25-dihydroxyvitamin D on related antibacterial proteins such as cathelicidin. Promoter-reporter and chromatin immunoprecipitation analyses indicated that direct transcriptional suppression of hepcidin gene (HAMP) expression mediated by 1,25-dihydroxyvitamin D binding to the vitamin D receptor caused the decrease in hepcidin mRNA levels. Suppression of HAMP expression was associated with a concomitant increase in expression of the cellular target for hepcidin, ferroportin protein, and decreased expression of the intracellular iron marker ferritin. In a pilot study with healthy volunteers, supplementation with a single oral dose of vitamin D (100,000 IU vitamin D2) increased serum levels of 25D-hydroxyvitamin D from 27±2 ng/ml before supplementation to 44±3 ng/ml after supplementation (P<0.001). This response was associated with a 34% decrease in circulating levels of hepcidin within 24 hours of vitamin D supplementation (P<0.05). These data show that vitamin D is a potent regulator of the hepcidin-ferroportin axis in humans and highlight a potential new strategy for the management of anemia in patients with low vitamin D and/or CKD.

The Impact of Aerobic Exercise on Fronto-Parietal Network Connectivity and Its Relation to Mobility: An Exploratory Analysis of a 6-Month Randomized Controlled Trial

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Chun L. Hsu

2017-06-01

Full Text Available Impaired mobility is a major concern for older adults and has significant consequences. While the widely accepted belief is that improved physical function underlies the effectiveness of targeted exercise training in improving mobility and reducing falls, recent evidence suggests cognitive and neural benefits gained through exercise may also play an important role in promoting mobility. However, the underlying neural mechanisms of this relationship are currently unclear. Thus, we hypothesize that 6 months of progressive aerobic exercise training would alter frontoparietal network (FPN connectivity during a motor task among older adults with mild subcortical ischemic vascular cognitive impairment (SIVCI—and exercise-induced changes in FPN connectivity would correlate with changes in mobility. We focused on the FPN as it is involved in top-down attentional control as well as motor planning and motor execution. Participants were randomized either to usual-care (CON, which included monthly educational materials about VCI and healthy diet; or thrice-weekly aerobic training (AT, which was walking outdoors with progressive intensity. Functional magnetic resonance imaging was acquired at baseline and trial completion, where the participants were instructed to perform bilateral finger tapping task. At trial completion, compared with AT, CON showed significantly increased FPN connectivity strength during right finger tapping (p < 0.05. Across the participants, reduced FPN connectivity was associated with greater cardiovascular capacity (p = 0.05. In the AT group, reduced FPN connectivity was significantly associated with improved mobility performance, as measured by the Timed-Up-and-Go test (r = 0.67, p = 0.02. These results suggest progressive AT may improve mobility in older adults with SIVCI via maintaining intra-network connectivity of the FPN.

Deletion of Iron Regulatory Protein 1 Causes Polycythemia and Pulmonary Hypertension in Mice through Translational De-repression of HIF2α

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Ghosh, Manik C.; Zhang, De-Liang; Jeong, Suh Young; Kovtunovych, Gennadiy; Ollivierre-Wilson, Hayden; Noguchi, Audrey; Tu, Tiffany; Senecal, Thomas; Robinson, Gabrielle; Crooks, Daniel R.; Tong, Wing-Hang; Ramaswamy, Kavitha; Singh, Anamika; Graham, Brian B.; Tuder, Rubin M.; Yu, Zu-Xi; Eckhaus, Michael; Lee, Jaekwon; Springer, Danielle A.; Rouault, Tracey A.

2013-01-01

SUMMARY Iron regulatory proteins 1 and 2 (Irps) post-transcriptionally control the expression of transcripts that contain iron responsive element (IRE) sequences, including ferritin, ferroportin, transferrin receptor and hypoxia inducible factor 2α (HIF2α). We report here that mice with targeted deletion of Irp1 developed pulmonary hypertension and polycythemia that was exacerbated by a low iron diet. Hematocrits increased to 65% in iron-starved mice, and many polycythemic mice died of abdominal hemorrhages. Irp1 deletion enhanced HIF2α protein expression in kidneys of Irp1−/− mice, which led to increased erythropoietin (EPO) expression, polycythemia and concomitant tissue iron deficiency. Increased HIF2α expression in pulmonary endothelial cells induced high expression of endothelin-1, likely contributing to the pulmonary hypertension of Irp1−/− mice. Our results reveal why anemia is an early physiological consequence of iron deficiency, highlight the physiological significance of Irp1 in regulating erythropoiesis and iron distribution, and provide important insights into the molecular pathogenesis of pulmonary hypertension. PMID:23395173

Functional Connectivity in Frontoparietal Network: Indicator of Preoperative Cognitive Function and Cognitive Outcome Following Surgery in Patients with Glioma.

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Lang, Stefan; Gaxiola-Valdez, Ismael; Opoku-Darko, Michael; Partlo, Lisa A; Goodyear, Bradley G; Kelly, John J P; Federico, Paolo

2017-09-01

Patients with diffuse glioma are known to have impaired cognitive functions preoperatively. However, the mechanism of these cognitive deficits remains unclear. Resting-state functional connectivity in the frontoparietal network (FPN) is associated with cognitive performance in healthy subjects. For this reason, it was hypothesized that functional connectivity of the FPN would be related to cognitive functioning in patients with glioma. To assess this relationship, preoperative cognitive status was correlated to patient-specific connectivity within the FPN. Further, we assessed whether connectivity could predict neuropsychologic outcome following surgery. Sixteen patients with diffuse glioma underwent neuropsychologic assessment and preoperative functional magnetic resonance imaging using task (n-back) and resting-state scans. Thirteen patients had postoperative cognitive assessment. An index of patient-specific functional connectivity in the FPN was derived by averaging connectivity values between 2 prefrontal and 2 parietal cortex regions defined by activation during the n-back task. The relationship of these indices with cognitive performance was assessed. Higher average connectivity within the FPN is associated with lower composite cognitive scores. Higher connectivity of the parietal region of the tumor-affected hemisphere is associated specifically with lower fluid cognition. Lower connectivity of the parietal region of the nontumor hemisphere is associated with worse neuropsychologic outcome 1 month after surgery. Resting-state functional connectivity between key regions of the FPN is associated with cognitive performance in patients with glioma and is related to cognitive outcome following surgery. Copyright © 2017 Elsevier Inc. All rights reserved.

Neurodegeneration with inflammation is accompanied by accumulation of iron and ferritin in microglia and neurons.

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Thomsen, Maj Schneider; Andersen, Michelle Vandborg; Christoffersen, Pia Rægaard; Jensen, Malene Duedal; Lichota, Jacek; Moos, Torben

2015-09-01

Chronic inflammation in the substantia nigra (SN) accompanies conditions with progressive neurodegeneration. This inflammatory process contributes to gradual iron deposition that may catalyze formation of free-radical mediated damage, hence exacerbating the neurodegeneration. This study examined proteins related to iron-storage (ferritin) and iron-export (ferroportin) (aka metal transporter protein 1, MTP1) in a model of neurodegeneration. Ibotenic acid injected stereotactically into the striatum leads to loss of GABAergic neurons projecting to SN pars reticulata (SNpr), which subsequently leads to excitotoxicity in the SNpr as neurons here become vulnerable to their additional glutamatergic projections from the subthalamic nucleus. This imbalance between glutamate and GABA eventually led to progressive shrinkage of the SNpr and neuronal loss. Neuronal cell death was accompanied by chronic inflammation as revealed by the presence of cells expressing ED1 and CD11b in the SNpr and the adjacent white matter mainly denoted by the crus cerebri. The SNpr also exhibited changes in iron metabolism seen as a marked accumulation of inflammatory cells containing ferric iron and ferritin with morphology corresponding to macrophages and microglia. Ferritin was detected in neurons of the lesioned SNpr in contrast to the non-injected side. Compared to non-injected rats, surviving neurons of the SNpr expressed ferroportin at unchanged level. Analyses of dissected SNpr using RT-qPCR showed a rise in ferritin-H and -L transcripts with increasing age but no change was observed in the lesioned side compared to the non-lesioned side, indicating that the increased expression of ferritin in the lesioned side occurred at the post-transcriptional level. Hepcidin transcripts were higher in the lesioned side in contrast to ferroportin mRNA that remained unaltered. The continuous entry of iron-containing inflammatory cells into the degenerating SNpr and their subsequent demise is probably

Common and distinct brain networks underlying verbal and visual creativity.

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Zhu, Wenfeng; Chen, Qunlin; Xia, Lingxiang; Beaty, Roger E; Yang, Wenjing; Tian, Fang; Sun, Jiangzhou; Cao, Guikang; Zhang, Qinglin; Chen, Xu; Qiu, Jiang

2017-04-01

Creativity is imperative to the progression of human civilization, prosperity, and well-being. Past creative researches tends to emphasize the default mode network (DMN) or the frontoparietal network (FPN) somewhat exclusively. However, little is known about how these networks interact to contribute to creativity and whether common or distinct brain networks are responsible for visual and verbal creativity. Here, we use functional connectivity analysis of resting-state functional magnetic resonance imaging data to investigate visual and verbal creativity-related regions and networks in 282 healthy subjects. We found that functional connectivity within the bilateral superior parietal cortex of the FPN was negatively associated with visual and verbal creativity. The strength of connectivity between the DMN and FPN was positively related to both creative domains. Visual creativity was negatively correlated with functional connectivity within the precuneus of the pDMN and right middle frontal gyrus of the FPN, and verbal creativity was negatively correlated with functional connectivity within the medial prefrontal cortex of the aDMN. Critically, the FPN mediated the relationship between the aDMN and verbal creativity, and it also mediated the relationship between the pDMN and visual creativity. Taken together, decreased within-network connectivity of the FPN and DMN may allow for flexible between-network coupling in the highly creative brain. These findings provide indirect evidence for the cooperative role of the default and executive control networks in creativity, extending past research by revealing common and distinct brain systems underlying verbal and visual creative cognition. Hum Brain Mapp 38:2094-2111, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution

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Avelar-Pereira, Bárbara; Bäckman, Lars; Wåhlin, Anders; Nyberg, Lars; Salami, Alireza

2017-01-01

Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture. PMID:28588476

Absorption of manganese and iron in a mouse model of hemochromatosis.

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Jonghan Kim

Full Text Available Hereditary hemochromatosis, an iron overload disease associated with excessive intestinal iron absorption, is commonly caused by loss of HFE gene function. Both iron and manganese absorption are regulated by iron status, but the relationships between the transport pathways of these metals and how they are affected by HFE-associated hemochromatosis remain poorly understood. Loss of HFE function is known to alter the intestinal expression of DMT1 (divalent metal transporter-1 and Fpn (ferroportin, transporters that have been implicated in absorption of both iron and manganese. Although the influence of HFE deficiency on dietary iron absorption has been characterized, potential effects on manganese metabolism have yet to be explored. To investigate the role of HFE in manganese absorption, we characterized the uptake and distribution of the metal in Hfe (-/- knockout mice after intravenous, intragastric, and intranasal administration of (54Mn. These values were compared to intravenous and intragastric administration of (59Fe. Intestinal absorption of (59Fe was increased and clearance of injected (59Fe was also increased in Hfe(-/- mice compared to controls. Hfe (-/- mice displayed greater intestinal absorption of (54Mn compared to wild-type Hfe(+/+ control mice. After intravenous injection, the distribution of (59Fe to heart and liver was greater in Hfe (-/- mice but no remarkable differences were observed for (54Mn. Although olfactory absorption of (54Mn into blood was unchanged in Hfe (-/- mice, higher levels of intranasally-instilled (54Mn were associated with Hfe(-/- brain compared to controls. These results show that manganese transport and metabolism can be modified by HFE deficiency.

High-Throughput Screening of Small Molecules Identifies Hepcidin Antagonists

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Fung, Eileen; Sugianto, Priscilla; Hsu, Jason; Damoiseaux, Robert; Ganz, Tomas

2013-01-01

Anemia of inflammation (AI) is common in patients with infection, autoimmune diseases, cancer, and chronic kidney disease. Unless the underlying condition can be reversed, treatment options are limited to erythropoiesis-stimulating agents with or without intravenous iron therapy, modalities that are not always effective and can cause serious adverse effects. Hepcidin, the iron regulatory hormone, has been identified as a pathogenic factor in the development of AI. To explore new therapeutic options for AI and other iron-related disorders caused by hepcidin excess, we developed a cell-based screen to identify hepcidin antagonists. Of the 70,000 small molecules in the library, we identified 14 compounds that antagonized the hepcidin effect on ferroportin. One of these was fursultiamine, a Food and Drug Administration (FDA)–approved thiamine derivative. Fursultiamine directly interfered with hepcidin binding to its receptor, ferroportin, by blocking ferroportin C326 thiol residue essential for hepcidin binding. Consequently, fursultiamine prevented hepcidin-induced ferroportin ubiquitination, endocytosis, and degradation in vitro and allowed continuous cellular iron export despite the presence of hepcidin, with IC50 in the submicromolar range. Thiamine, the fursultiamine metabolite, and benfotiamine, another thiamine derivative, did not interfere with the effect of hepcidin on ferroportin. Other FDA-approved thiol-reactive compounds were at least 1000-fold less potent than fursultiamine in antagonizing hepcidin. In vivo, fursultiamine did not reproducibly antagonize the effect of hepcidin on serum iron, likely because of its rapid conversion to inactive metabolites. Fursultiamine is a unique antagonist of hepcidin in vitro that could serve as a template for the development of drug candidates that inhibit the hepcidin-ferroportin interaction. PMID:23292796

The actin-binding protein profilin 2 is a novel regulator of iron homeostasis.

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Luscieti, Sara; Galy, Bruno; Gutierrez, Lucia; Reinke, Michael; Couso, Jorge; Shvartsman, Maya; Di Pascale, Antonio; Witke, Walter; Hentze, Matthias W; Pilo Boyl, Pietro; Sanchez, Mayka

2017-10-26

Cellular iron homeostasis is controlled by the iron regulatory proteins (IRPs) 1 and 2 that bind cis -regulatory iron-responsive elements (IRE) on target messenger RNAs (mRNA). We identified profilin 2 ( Pfn2 ) mRNA, which encodes an actin-binding protein involved in endocytosis and neurotransmitter release, as a novel IRP-interacting transcript, and studied its role in iron metabolism. A combination of electrophoretic mobility shift assay experiments and bioinformatic analyses led to the identification of an atypical and conserved IRE in the 3' untranslated region of Pfn2 mRNA. Pfn2 mRNA levels were significantly reduced in duodenal samples from mice with intestinal IRP ablation, suggesting that IRPs exert a positive effect on Pfn2 mRNA expression in vivo. Overexpression of Pfn2 in HeLa and Hepa1-6 cells reduced their metabolically active iron pool. Importantly, Pfn2-deficient mice showed iron accumulation in discrete areas of the brain (olfactory bulb, hippocampus, and midbrain) and reduction of the hepatic iron store without anemia. Despite low liver iron levels, hepatic hepcidin expression remained high, likely because of compensatory activation of hepcidin by mild inflammation. Splenic ferroportin was increased probably to sustain hematopoiesis. Overall, our results indicate that Pfn2 expression is controlled by the IRPs in vivo and that Pfn2 contributes to maintaining iron homeostasis in cell lines and mice. © 2017 by The American Society of Hematology.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

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Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

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Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

2018-01-01

Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

Rice and Bean Targets for Biofortification Combined with High Carotenoid Content Crops Regulate Transcriptional Mechanisms Increasing Iron Bioavailability

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Desirrê Morais Dias

2015-11-01

Full Text Available Iron deficiency affects thousands of people worldwide. Biofortification of staple food crops aims to support the reduction of this deficiency. This study evaluates the effect of combinations of common beans and rice, targets for biofortification, with high carotenoid content crops on the iron bioavailability, protein gene expression, and antioxidant effect. Iron bioavailability was measured by the depletion/repletion method. Seven groups were tested (n = 7: Pontal bean (PB; rice + Pontal bean (R + BP; Pontal bean + sweet potato (PB + SP; Pontal bean + pumpkin (PB + P; Pontal bean + rice + sweet potato (PB + R + P; Pontal bean + rice + sweet potato (PB + R + SP; positive control (Ferrous Sulfate. The evaluations included: hemoglobin gain, hemoglobin regeneration efficiency (HRE, gene expression of divalente metal transporter 1 (DMT-1, duodenal citocromo B (DcytB, ferroportin, hephaestin, transferrin and ferritin and total plasma antioxidant capacity (TAC. The test groups, except the PB, showed higher HRE (p < 0.05 than the control. Gene expression of DMT-1, DcytB and ferroportin increased (p < 0.05 in the groups fed with high content carotenoid crops (sweet potato or pumpkin. The PB group presented lower (p < 0.05 TAC than the other groups. The combination of rice and common beans, and those with high carotenoid content crops increased protein gene expression, increasing the iron bioavailability and antioxidant capacity.

Altered resting state connectivity in right side frontoparietal network in primary insomnia patients

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Li, Shumei; Tian, Junzhang; Li, Meng; Wang, Tianyue; Lin, Chulan; Yin, Yi; Jiang, Guihua [Guangdong Second Provincial General Hospital, Department of Medical Imaging, Guangzhou (China); Zeng, Luxian [Guangdong Second Provincial General Hospital, Department of Science and Education, Guangzhou (China); Li, Cheng [Guangdong Second Provincial General Hospital, Department of Renal Transplantation, Guangzhou (China)

2018-02-15

This study investigated alterations of resting-state networks (RSNs) in primary insomnia patients as well as relationships between these changes and clinical features. Fifty-nine primary insomnia patients and 53 healthy control subjects underwent a resting-state fMRI scan (rs-fMRI). Ten RSNs were identified using independent component analysis of rs-fMRI data. To assess significant differences between the two groups, voxel-wise analysis of ten RSNs was conducted using dual regression with FSL randomised non-parametric permutation testing and a threshold-free cluster enhanced technique to control for multiple comparisons. Relationships between abnormal functional connectivity and clinical variables were then investigated with Pearson's correlation analysis. Primary insomnia patients showed decreased connectivity in regions of the right frontoparietal network (FPN), including the superior parietal lobule and superior frontal gyrus. Moreover, decreased connectivity in the right middle temporal gyrus and right lateral occipital cortex with the FPN showed significant positive correlations with disease duration and self-rated anxiety, respectively. Our study suggests that primary insomnia patients are characterised by abnormal organisation of the right FPN, and dysfunction of the FPN is correlated with disease duration and anxiety. The results enhance our understanding of neural substrates underlying symptoms of primary insomnia from the viewpoint of resting-state networks. (orig.)

Altered resting state connectivity in right side frontoparietal network in primary insomnia patients

International Nuclear Information System (INIS)

Li, Shumei; Tian, Junzhang; Li, Meng; Wang, Tianyue; Lin, Chulan; Yin, Yi; Jiang, Guihua; Zeng, Luxian; Li, Cheng

2018-01-01

This study investigated alterations of resting-state networks (RSNs) in primary insomnia patients as well as relationships between these changes and clinical features. Fifty-nine primary insomnia patients and 53 healthy control subjects underwent a resting-state fMRI scan (rs-fMRI). Ten RSNs were identified using independent component analysis of rs-fMRI data. To assess significant differences between the two groups, voxel-wise analysis of ten RSNs was conducted using dual regression with FSL randomised non-parametric permutation testing and a threshold-free cluster enhanced technique to control for multiple comparisons. Relationships between abnormal functional connectivity and clinical variables were then investigated with Pearson's correlation analysis. Primary insomnia patients showed decreased connectivity in regions of the right frontoparietal network (FPN), including the superior parietal lobule and superior frontal gyrus. Moreover, decreased connectivity in the right middle temporal gyrus and right lateral occipital cortex with the FPN showed significant positive correlations with disease duration and self-rated anxiety, respectively. Our study suggests that primary insomnia patients are characterised by abnormal organisation of the right FPN, and dysfunction of the FPN is correlated with disease duration and anxiety. The results enhance our understanding of neural substrates underlying symptoms of primary insomnia from the viewpoint of resting-state networks. (orig.)

Absorption of Manganese and Iron in a Mouse Model of Hemochromatosis

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Kim, Jonghan; Buckett, Peter D.; Wessling-Resnick, Marianne

2013-01-01

Hereditary hemochromatosis, an iron overload disease associated with excessive intestinal iron absorption, is commonly caused by loss of HFE gene function. Both iron and manganese absorption are regulated by iron status, but the relationships between the transport pathways of these metals and how they are affected by HFE-associated hemochromatosis remain poorly understood. Loss of HFE function is known to alter the intestinal expression of DMT1 (divalent metal transporter-1) and Fpn (ferroportin), transporters that have been implicated in absorption of both iron and manganese. Although the influence of HFE deficiency on dietary iron absorption has been characterized, potential effects on manganese metabolism have yet to be explored. To investigate the role of HFE in manganese absorption, we characterized the uptake and distribution of the metal in Hfe −/− knockout mice after intravenous, intragastric, and intranasal administration of 54Mn. These values were compared to intravenous and intragastric administration of 59Fe. Intestinal absorption of 59Fe was increased and clearance of injected 59Fe was also increased in Hfe−/− mice compared to controls. Hfe −/− mice displayed greater intestinal absorption of 54Mn compared to wild-type Hfe+/+ control mice. After intravenous injection, the distribution of 59Fe to heart and liver was greater in Hfe −/− mice but no remarkable differences were observed for 54Mn. Although olfactory absorption of 54Mn into blood was unchanged in Hfe −/− mice, higher levels of intranasally-instilled 54Mn were associated with Hfe−/− brain compared to controls. These results show that manganese transport and metabolism can be modified by HFE deficiency. PMID:23705020

Disruptions in brain networks of older fallers are associated with subsequent cognitive decline: a 12-month prospective exploratory study.

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Chun Liang Hsu

Full Text Available Cognitive impairment and impaired mobility are major public health concerns. There is growing recognition that impaired mobility is an early biomarker of cognitive impairment and dementia. The neural basis for this association is currently unclear. We propose disrupted functional connectivity as a potential mechanism. In this 12-month prospective exploratory study, we compared functional connectivity of four brain networks- the default mode network (DMN, fronto-executive network (FEN, fronto-parietal network (FPN, and the primary motor sensory network (SMN--between community-dwelling older adults with ≥ two falls in the last 12 months and their non-falling counterparts (≤ one fall in the last 12 months. Functional connectivity was examined both at rest and during a simple motor tapping task. Compared with non-fallers, fallers showed more connectivity between the DMN and FPN during right finger tapping (p  = 0.04, and significantly less functional connectivity between the SMN and FPN during rest (p ≤ 0.05. Less connectivity between the SMN and FPN during rest was significantly associated with greater decline in both cognitive function and mobility over the12-month period (r =  -0.32 and 0.33 respectively; p ≤ 0.04. Thus, a recent history of multiple falls among older adults without a diagnosis of dementia may indicate sub-clinical changes in brain function and increased risk for subsequent decline.

Noise characteristics of neutron images obtained by cooled CCD device

International Nuclear Information System (INIS)

Taniguchi, Ryoichi; Sasaki, Ryoya; Okuda, Shuichi; Okamoto, Ken-Ichi; Ogawa, Yoshihiro; Tsujimoto, Tadashi

2009-01-01

The noise characteristics of a cooled CCD device induced by neutron and gamma ray irradiation have been investigated. In the cooled CCD images, characteristic white spot noises (CCD noise) frequently appeared, which have a shape like a pixel in most cases and their brightness is extremely high compared with that of the image pattern. They could be divided into the two groups, fixed pattern noise (FPN) and random noise. The former always appeared in the same position in the image and the latter appeared at any position. In the background image, nearly all of the CCD noises were found to be the FPN, while many of them were the random noise during the irradiation. The random CCD noises increased with irradiation and decreased soon after the irradiation. In the case of large irradiation, a part of the CCD noise remained as the FPN. These facts suggest that the CCD noise is a phenomenon strongly relating to radiation damage of the CCD device.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

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Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

Science.gov (United States)

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear

Specification and Verification of Medical Monitoring System Using Petri-nets.

Science.gov (United States)

Majma, Negar; Babamir, Seyed Morteza

2014-07-01

To monitor the patient behavior, data are collected from patient's body by a medical monitoring device so as to calculate the output using embedded software. Incorrect calculations may endanger the patient's life if the software fails to meet the patient's requirements. Accordingly, the veracity of the software behavior is a matter of concern in the medicine; moreover, the data collected from the patient's body are fuzzy. Some methods have already dealt with monitoring the medical monitoring devices; however, model based monitoring fuzzy computations of such devices have been addressed less. The present paper aims to present synthesizing a fuzzy Petri-net (FPN) model to verify behavior of a sample medical monitoring device called continuous infusion insulin (INS) because Petri-net (PN) is one of the formal and visual methods to verify the software's behavior. The device is worn by the diabetic patients and then the software calculates the INS dose and makes a decision for injection. The input and output of the infusion INS software are not crisp in the real world; therefore, we present them in fuzzy variables. Afterwards, we use FPN instead of clear PN to model the fuzzy variables. The paper follows three steps to synthesize an FPN to deal with verification of the infusion INS device: (1) Definition of fuzzy variables, (2) definition of fuzzy rules and (3) design of the FPN model to verify the software behavior.

Estrogen-induced disruption of intracellular iron metabolism leads to oxidative stress, membrane damage, and cell cycle arrest in MCF-7 cells.

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Bajbouj, Khuloud; Shafarin, Jasmin; Abdalla, Maher Y; Ahmad, Iman M; Hamad, Mawieh

2017-10-01

It is well established that several forms of cancer associate with significant iron overload. Recent studies have suggested that estrogen (E2) disrupts intracellular iron homeostasis by reducing hepcidin synthesis and maintaining ferroportin integrity. Here, the ability of E2 to alter intracellular iron status and cell growth potential was investigated in MCF-7 cells treated with increasing concentrations of E2. Treated cells were assessed for intracellular iron status, the expression of key proteins involved in iron metabolism, oxidative stress, cell survival, growth, and apoptosis. E2 treatment resulted in a significant reduction in hepcidin expression and a significant increase in hypoxia-inducible factor 1 alpha, ferroportin, transferrin receptor, and ferritin expression; a transient decrease in labile iron pool; and a significant increase in total intracellular iron content mainly at 20 nM/48 h E2 dose. Treated cells also showed increased total glutathione and oxidized glutathione levels, increased superoxide dismutase activity, and increased hemoxygenase 1 expression. Treatment with E2 at 20 nM for 48 h resulted in a significant reduction in cell growth (0.35/1 migration rate) and decreased cell survival (iron metabolism and precipitates adverse effects concerning cell viability, membrane integrity, and growth potential.

Suppression of fixed pattern noise for infrared image system

Science.gov (United States)

Park, Changhan; Han, Jungsoo; Bae, Kyung-Hoon

2008-04-01

In this paper, we propose suppression of fixed pattern noise (FPN) and compensation of soft defect for improvement of object tracking in cooled staring infrared focal plane array (IRFPA) imaging system. FPN appears an observable image which applies to non-uniformity compensation (NUC) by temperature. Soft defect appears glittering black and white point by characteristics of non-uniformity for IR detector by time. This problem is very important because it happen serious problem for object tracking as well as degradation for image quality. Signal processing architecture in cooled staring IRFPA imaging system consists of three tables: low, normal, high temperature for reference gain and offset values. Proposed method operates two offset tables for each table. This is method which operates six term of temperature on the whole. Proposed method of soft defect compensation consists of three stages: (1) separates sub-image for an image, (2) decides a motion distribution of object between each sub-image, (3) analyzes for statistical characteristic from each stationary fixed pixel. Based on experimental results, the proposed method shows an improved image which suppresses FPN by change of temperature distribution from an observational image in real-time.

Alterations of Brain Functional Architecture Associated with Psychopathic Traits in Male Adolescents with Conduct Disorder.

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Pu, Weidan; Luo, Qiang; Jiang, Yali; Gao, Yidian; Ming, Qingsen; Yao, Shuqiao

2017-09-12

Psychopathic traits of conduct disorder (CD) have a core callous-unemotional (CU) component and an impulsive-antisocial component. Previous task-driven fMRI studies have suggested that psychopathic traits are associated with dysfunction of several brain areas involved in different cognitive functions (e.g., empathy, reward, and response inhibition etc.), but the relationship between psychopathic traits and intrinsic brain functional architecture has not yet been explored in CD. Using a holistic brain-wide functional connectivity analysis, this study delineated the alterations in brain functional networks in patients with conduct disorder. Compared with matched healthy controls, we found decreased anti-synchronization between the fronto-parietal network (FPN) and default mode network (DMN), and increased intra-network synchronization within the frontothalamic-basal ganglia, right frontoparietal, and temporal/limbic/visual networks in CD patients. Correlation analysis showed that the weakened FPN-DMN interaction was associated with CU traits, while the heightened intra-network functional connectivity was related to impulsivity traits in CD patients. Our findings suggest that decoupling of cognitive control (FPN) with social understanding of others (DMN) is associated with the CU traits, and hyper-functions of the reward and motor inhibition systems elevate impulsiveness in CD.

Calibration method of microgrid polarimeters with image interpolation.

Science.gov (United States)

Chen, Zhenyue; Wang, Xia; Liang, Rongguang

2015-02-10

Microgrid polarimeters have large advantages over conventional polarimeters because of the snapshot nature and because they have no moving parts. However, they also suffer from several error sources, such as fixed pattern noise (FPN), photon response nonuniformity (PRNU), pixel cross talk, and instantaneous field-of-view (IFOV) error. A characterization method is proposed to improve the measurement accuracy in visible waveband. We first calibrate the camera with uniform illumination so that the response of the sensor is uniform over the entire field of view without IFOV error. Then a spline interpolation method is implemented to minimize IFOV error. Experimental results show the proposed method can effectively minimize the FPN and PRNU.

Energy landscapes of resting-state brain networks

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Takamitsu eWatanabe

2014-02-01

Full Text Available During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs including the default-mode network (DMN and frontoparietal network (FPN. Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics, the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.

Using polynomials to simplify fixed pattern noise and photometric correction of logarithmic CMOS image sensors.

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Li, Jing; Mahmoodi, Alireza; Joseph, Dileepan

2015-10-16

An important class of complementary metal-oxide-semiconductor (CMOS) image sensors are those where pixel responses are monotonic nonlinear functions of light stimuli. This class includes various logarithmic architectures, which are easily capable of wide dynamic range imaging, at video rates, but which are vulnerable to image quality issues. To minimize fixed pattern noise (FPN) and maximize photometric accuracy, pixel responses must be calibrated and corrected due to mismatch and process variation during fabrication. Unlike literature approaches, which employ circuit-based models of varying complexity, this paper introduces a novel approach based on low-degree polynomials. Although each pixel may have a highly nonlinear response, an approximately-linear FPN calibration is possible by exploiting the monotonic nature of imaging. Moreover, FPN correction requires only arithmetic, and an optimal fixed-point implementation is readily derived, subject to a user-specified number of bits per pixel. Using a monotonic spline, involving cubic polynomials, photometric calibration is also possible without a circuit-based model, and fixed-point photometric correction requires only a look-up table. The approach is experimentally validated with a logarithmic CMOS image sensor and is compared to a leading approach from the literature. The novel approach proves effective and efficient.

Iron uptake and transport at the blood-brain barrier

DEFF Research Database (Denmark)

Larsen, Annette Burkhart; Thomsen, Louiza Bohn; Moos, Torben

The mechanism by which iron is transported across the blood-brain barrier (BBB) remains controversial, and in this study we aimed to further clarify mechanisms by which iron is transported into the brain. We analyzed and compared the mRNA and protein expression of a variety of proteins involved...... in the transport of iron (transferrin receptor, divalent metal transporter I (DMT1), steap 2, steap 3, ceruloplasmin, hephaestin and ferroportin) in both primary rat brain capillary endothelial cells (BCEC) and immortalized rat brain capillary endothelial cell line (RBE4) grown in co-culture with defined polarity....... The mRNA expression of the iron-related molecules was also investigated in isolated brain capillaries from iron deficiency, iron reversible and normal rats. We also performed iron transport studies to analyze the routes by which iron is transported through the brain capillary endothelial cells: i) We...

Change in iron metabolism in rats after renal ischemia/reperfusion injury.

Directory of Open Access Journals (Sweden)

Guang-Liang Xie

Full Text Available Previous studies have indicated that hepcidin, which can regulate iron efflux by binding to ferroportin-1 (FPN1 and inducing its internalization and degradation, acts as the critical factor in the regulation of iron metabolism. However, it is unknown whether hepcidin is involved in acute renal ischemia/reperfusion injury (IRI. In this study, an IRI rat model was established via right renal excision and blood interruption for 45 min in the left kidney, and iron metabolism indexes were examined to investigate the change in iron metabolism and to analyze the role of hepcidin during IRI. From 1 to 24 h after renal reperfusion, serum creatinine and blood urea nitrogen were found to be time-dependently increased with different degrees of kidney injury. Regular variations in iron metabolism indexes in the blood and kidneys were observed in renal IRI. Renal iron content, serum iron and serum ferritin increased early after reperfusion and then declined. Hepcidin expression in the liver significantly increased early after reperfusion, and its serum concentration increased beginning at 8 h after reperfusion. The splenic iron content decreased significantly in the early stage after reperfusion and then increased time-dependently with increasing reperfusion time, and the hepatic iron content showed a decrease in the early stage after reperfusion. The early decrease of the splenic iron content and hepatic iron content might indicate their contribution to the increase in serum iron in renal IRI. In addition, the duodenal iron content showed time-dependently decreased since 12 h after reperfusion in the IRI groups compared to the control group. Along with the spleen, the duodenum might contribute to the decrease in serum iron in the later stage after reperfusion. The changes in iron metabolism indexes observed in our study demonstrate an iron metabolism disorder in renal IRI, and hepcidin might be involved in maintaining iron homeostasis in renal IRI. These

Epigallocatechin Gallate Has a Neurorescue Effect in a Mouse Model of Parkinson Disease.

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Xu, Qi; Langley, Monica; Kanthasamy, Anumantha G; Reddy, Manju B

2017-10-01

Background: Parkinson disease (PD) is a neurodegenerative disorder that has been associated with many factors, including oxidative stress, inflammation, and iron accumulation. The antioxidant, anti-inflammatory, and iron-chelating properties of epigallocatechin gallate (EGCG), a major polyphenol in green tea, may offer protection against PD. Objective: We sought to determine the neurorescue effects of EGCG and the role of iron in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD. Methods: We evaluated the neurorescue effect of EGCG (25 mg/kg, 7 d, oral administration) against MPTP-induced (20 mg/kg, 3 d, intraperitoneal injection) neurodegeneration in C57 male black mice. Thirty mice weighing ∼25 g were divided into 3 groups: control, MPTP, and MPTP + EGCG. The neurorescue effect of EGCG was assessed with the use of motor behavior tests, neurotransmitter analysis, oxidative stress indicators, and iron-related protein expression. Results: Compared with the control group, MPTP treatment shortened the mice's latency to fall from the rotarod by 16% ( P < 0.05), decreased the striatal dopamine concentration by 58% ( P < 0.001) and dihydroxyphenylacetic acid by 35% ( P < 0.05), and increased serum protein carbonyls by 71% ( P = 0.07). However, EGCG rescued MPTP-induced neurotoxicity by increasing the rotational latency by 17% ( P < 0.05) to a value similar to the control group. Striatal dopamine concentrations were 40% higher in the MPTP + EGCG group than in the MPTP group ( P < 0.05), but the values were significantly lower than in the control group. Compared with the MPTP and control groups, mice in the MPTP + EGCG group had higher substantia nigra ferroportin expression (44% and 35%, respectively) ( P < 0.05) but not hepcidin and divalent metal transporter 1 expression. Conclusion: Overall, our study demonstrated that EGCG regulated the iron-export protein ferroportin in substantia nigra, reduced oxidative stress, and exerted a neurorescue effect

Hepcidin Plays a Key Role in 6-OHDA Induced Iron Overload and Apoptotic Cell Death in a Cell Culture Model of Parkinson’s Disease

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Qi Xu

2016-01-01

Full Text Available Background. Elevated brain iron levels have been implicated in the pathogenesis of Parkinson’s disease (PD. However, the precise mechanism underlying abnormal iron accumulation in PD is not clear. Hepcidin, a hormone primarily produced by hepatocytes, acts as a key regulator in both systemic and cellular iron homeostasis. Objective. We investigated the role of hepcidin in 6-hydroxydopamine (6-OHDA induced apoptosis in a cell culture model of PD. Methods. We downregulated hepcidin using siRNA interference in N27 dopaminergic neuronal cells and made a comparison with control siRNA transfected cells to investigate the role of hepcidin in 6-OHDA induced neurodegeneration. Results. Hepcidin knockdown (32.3%, P<0.0001 upregulated ferroportin 1 expression and significantly (P<0.05 decreased intracellular iron by 25%. Hepcidin knockdown also reduced 6-OHDA induced caspase-3 activity by 42% (P<0.05 and DNA fragmentation by 29% (P=0.086 and increased cell viability by 22% (P<0.05. In addition, hepcidin knockdown significantly attenuated 6-OHDA induced protein carbonyls by 52% (P<0.05 and intracellular iron by 28% (P<0.01, indicating the role of hepcidin in oxidative stress. Conclusions. Our results demonstrate that hepcidin knockdown protected N27 cells from 6-OHDA induced apoptosis and that hepcidin plays a major role in reducing cellular iron burden and oxidative damage by possibly regulating cellular iron export mediated by ferroportin 1.

Histological Features of the Distal Third Metacarpal Bone in Thoroughbred Racehorses, With and Without Lateral Condylar Fractures.

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Pinilla, M J; Tranquille, C A; Blunden, A S; Chang, Y M; Parkin, T D H; Murray, R C

2017-07-01

A detailed histopathological study of the distal third metacarpal bone of Thoroughbred racehorses was undertaken to characterize lesions observed previously on magnetic resonance imaging (MRI). The bones were selected and grouped on the basis of MRI features. Representative sections in different planes were processed for histopathology. All lesions observed in the articular cartilage (AC) and subchondral bone (SCB) were recorded and graded with a scoring system, based partially on the Osteoarthritis Research Society International grading system. The scoring system included the severity of the lesion. Descriptive statistics and linear mixed effects models were performed. A positive correlation was observed between the severity of histopathological changes in the superficial and deeper osteochondral tissues, and between the number of race starts and AC score. Age was not correlated with AC or SCB score. A moderate variation in AC and SCB scores was observed between the groups; however, there were differences within individual bones. Bones with focal palmar necrosis (FPN) showed significant differences in the histological scoring of the AC compared with bones without FPN. Bones with incomplete fractures or larger areas of bone remodelling showed significant differences in SCB pathology when compared with bones with FPN. Haematoidin was detected in areas with excessive SCB and cancellous bone sclerosis and/or irregular bone density. This finding is suggestive of poor blood perfusion in these areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Software Design Modelling with Functional Petri Nets | Bakpo ...

African Journals Online (AJOL)

Software Design Modelling with Functional Petri Nets. ... of structured programs and a FPN Software prototype proposed for the conventional programming construct: if-then-else statement. ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

Resting State Default Mode Network Connectivity, Dual Task Performance, Gait Speed, and Postural Sway in Older Adults with Mild Cognitive Impairment.

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Crockett, Rachel A; Hsu, Chun Liang; Best, John R; Liu-Ambrose, Teresa

2017-01-01

Aging is associated with an increased risk of falling. In particular, older adults with mild cognitive impairment (MCI) are more vulnerable to falling compared with their healthy counterparts. Major contributors to this increased falls risk include a decline in dual task performance, gait speed, and postural sway. Recent evidence highlights the potential influence of the default mode network (DMN), the frontoparietal network (FPN), and the supplementary motor area (SMA) on dual task performance, gait speed, and postural sway. The DMN is active during rest and deactivates during task-oriented processes, to maintain attention and stay on task. The FPN and SMA are involved in top-down attentional control, motor planning, and motor execution. The DMN shows less deactivation during task in older adults with MCI. This lack of deactivation is theorized to increase competition for resources between the DMN and task-related brain regions (e.g., the FPN and SMA), increasing distraction from the task and reducing task performance. However, no study has yet investigated the relationship between the between-network connectivity of the DMN with these regions and dual task walking, gait speed or postural sway. We hypothesized that greater functional connectivity both within the DMN and between DMN-FPN and DMN-SMA, will be associated with poorer performance during dual task walking, slower gait speed, and greater postural sway in older adults with MCI. Forty older adults with MCI were measured on a dual task-walking paradigm, gait speed over a 4-m walk, and postural sway using a sway-meter. Greater within-DMN connectivity was significantly correlated with poorer dual task performance. Furthermore, greater inter-network connectivity between the DMN and SMA was significantly correlated with slower gait speed and greater postural sway on the eyes open floor sway task. Thus, greater resting state DMN functional connectivity may be an underlying neural mechanism for reduced dual task

SOFTWARE DESIGN MODELLING WITH FUNCTIONAL PETRI NETS

African Journals Online (AJOL)

Dr Obe

the system, which can be described as a set of conditions. ... FPN Software prototype proposed for the conventional programming construct: if-then-else ... mathematical modeling tool allowing for ... methods and techniques of software design.

Adolescent Gender Differences in Cognitive Control Performance and Functional Connectivity Between Default Mode and Fronto-Parietal Networks Within a Self-Referential Context

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Gabriela Alarcón

2018-04-01

Full Text Available Ineffective reduction of functional connectivity between the default mode network (DMN and frontoparietal network (FPN during cognitive control can interfere with performance in healthy individuals—a phenomenon present in psychiatric disorders, such as depression. Here, this mechanism is studied in healthy adolescents by examining gender differences in task-regressed functional connectivity using functional magnetic resonance imaging (MRI and a novel task designed to place the DMN—supporting self-referential processing (SRP—and FPN—supporting cognitive control—into conflict. Compared to boys, girls showed stronger functional connectivity between DMN and FPN during cognitive control in an SRP context (n = 40; boys = 20, a context that also elicited more errors of omission in girls. The gender difference in errors of omission was mediated by higher self-reported co-rumination—the extensive and repetitive discussion of problems and focus on negative feelings with a same-gender peer—by girls, compared to boys. These findings indicate that placing internal and external attentional demands in conflict lead to persistent functional connectivity between FPN and DMN in girls, but not boys; however, deficits in performance during this context were explained by co-rumination, such that youth with higher co-rumination displayed the largest performance deficits. Previous research shows that co-rumination predicts depressive symptoms during adolescence; thus, gender differences in the mechanisms involved with transitioning from internal to external processing may be relevant for understanding heightened vulnerability for depression in adolescent girls.

Radioactive waste management and advanced nuclear fuel cycle technologies

International Nuclear Information System (INIS)

2007-01-01

In 2007 ENEA's Department of Nuclear Fusion and Fission, and Related Technologies acted according to national policy and the role assigned to ENEA FPN by Law 257/2003 regarding radioactive waste management and advanced nuclear fuel cycle technologies

Rethinking Iron Regulation and Assessment in Iron Deficiency, Anemia of Chronic Disease, and Obesity: Introducing Hepcidin

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Tussing-Humphreys, Lisa; Pustacioglu, Cenk; Nemeth, Elizabeta; Braunschweig, Carol

2012-01-01

Adequate iron availability is essential to human development and overall health. Iron is a key component of oxygen-carrying proteins, has a pivotal role in cellular metabolism, and is essential to cell growth and differentiation. Inadequate dietary iron intake, chronic and acute inflammatory conditions, and obesity are each associated with alterations in iron homeostasis. Tight regulation of iron is necessary because iron is highly toxic and human beings can only excrete small amounts through sweat, skin and enterocyte sloughing, and fecal and menstrual blood loss. Hepcidin, a small peptide hormone produced mainly by the liver, acts as the key regulator of systemic iron homeostasis. Hepcidin controls movement of iron into plasma by regulating the activity of the sole known iron exporter ferroportin-1. Downregulation of the ferroportin-1 exporter results in sequestration of iron within intestinal enterocytes, hepatocytes, and iron-storing macrophages reducing iron bioavailability. Hepcidin expression is increased by higher body iron levels and inflammation and decreased by anemia and hypoxia. Importantly, existing data illustrate that hepcidin may play a significant role in the development of several iron-related disorders, including the anemia of chronic disease and the iron dysregulation observed in obesity. Therefore, the purpose of this article is to discuss iron regulation, with specific emphasis on systemic regulation by hepcidin, and examine the role of hepcidin within several disease states, including iron deficiency, anemia of chronic disease, and obesity. The relationship between obesity and iron depletion and the clinical assessment of iron status will also be reviewed. PMID:22717199

Nutrient transport in the mammary gland: calcium, trace minerals and water soluble vitamins.

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Montalbetti, Nicolas; Dalghi, Marianela G; Albrecht, Christiane; Hediger, Matthias A

2014-03-01

Milk nutrients are secreted by epithelial cells in the alveoli of the mammary gland by several complex and highly coordinated systems. Many of these nutrients are transported from the blood to the milk via transcellular pathways that involve the concerted activity of transport proteins on the apical and basolateral membranes of mammary epithelial cells. In this review, we focus on transport mechanisms that contribute to the secretion of calcium, trace minerals and water soluble vitamins into milk with particular focus on the role of transporters of the SLC series as well as calcium transport proteins (ion channels and pumps). Numerous members of the SLC family are involved in the regulation of essential nutrients in the milk, such as the divalent metal transporter-1 (SLC11A2), ferroportin-1 (SLC40A1) and the copper transporter CTR1 (SLC31A1). A deeper understanding of the physiology and pathophysiology of these transporters will be of great value for drug discovery and treatment of breast diseases.

Etude du faible poids de naissance associé à l’âge maternel et la parité dans une population couple mère-enfant suivi à Lubumbashi

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Luhete, Prosper Kakudji; Mukuku, Olivier; Kayamba, Prosper Kalenga Muenze

2015-01-01

Introduction Evaluer l'influence de l’âge maternel et de la parité sur la naissance d'un faible poids de naissance (FPN) à Lubumbashi. Méthodes Il s'agit d'une étude basée sur une analyse documentaire des dossiers médicaux des accouchées enregistrées dans les maternités des 10 hôpitaux généraux de référence (HGR) de la ville de Lubumbashi en République Démocratique du Congo entre le 1er décembre 2013 et le 31 mars 2014. Ces accouchées ont été réparties en deux groupes, en fonction du poids de naissance de leurs enfants: groupe I (femmes ayant accouché de nouveau-nés vivants dont le poids était inférieur à 2500 grammes) et groupe II (femmes ayant accouché de nouveau-nés vivants dont le poids était supérieur ou égal à 2500 grammes). Il s'agissait dans tous les cas de grossesses monofoetales âgées de 28 semaines ou plus. L’âge maternel et la parité ont été étudiés et comparés dans les deux groupes. Les données ont été analysées à l'aide des logiciels Épi info version 7.0 et SPSS version 19. Les différences étaient jugées significatives pour un seuil p < 0,05. Résultats La prévalence du FPN chez les nouveau-nés issus de ces accouchées était ainsi de 6,4% (71/1112). En analyse univariée, les femmes d’âge < 20 ans présentent un risque multiplié par 2,47 fois d'avoir un nouveau-né de FPN comparativement à celles de ≥20 ans (OR = 2,47; IC95%: 1,26-4,78) et celui pour les primipares d'avoir un enfant de FPN est 2,3 fois supérieur à celui de multipares (OR = 2,32; IC95%: 1,34-3,99). En faisant la régression logistique, nous avons observé que seule la parité est significativement corrélée au poids de naissance (OR ajusté = 2,61; IC95%: 1,43-4,74). Conclusion L’étude que nous avons menée montre que le taux de FPN diminue considérablement avec l’âge de la mère à partir de 20 ans et la multiparité. PMID:26161169

When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes.

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Shi, Yiquan; Wolfensteller, Uta; Schubert, Torsten; Ruge, Hannes

2018-02-01

Cognitive flexibility is essential to cope with changing task demands and often it is necessary to adapt to combined changes in a coordinated manner. The present fMRI study examined how the brain implements such multi-level adaptation processes. Specifically, on a "local," hierarchically lower level, switching between two tasks was required across trials while the rules of each task remained unchanged for blocks of trials. On a "global" level regarding blocks of twelve trials, the task rules could reverse or remain the same. The current task was cued at the start of each trial while the current task rules were instructed before the start of a new block. We found that partly overlapping and partly segregated neural networks play different roles when coping with the combination of global rule reversal and local task switching. The fronto-parietal control network (FPN) supported the encoding of reversed rules at the time of explicit rule instruction. The same regions subsequently supported local task switching processes during actual implementation trials, irrespective of rule reversal condition. By contrast, a cortico-striatal network (CSN) including supplementary motor area and putamen was increasingly engaged across implementation trials and more so for rule reversal than for nonreversal blocks, irrespective of task switching condition. Together, these findings suggest that the brain accomplishes the coordinated adaptation to multi-level demand changes by distributing processing resources either across time (FPN for reversed rule encoding and later for task switching) or across regions (CSN for reversed rule implementation and FPN for concurrent task switching). © 2017 Wiley Periodicals, Inc.

Temperature Sensors Integrated into a CMOS Image Sensor

NARCIS (Netherlands)

Abarca Prouza, A.N.; Xie, S.; Markenhof, Jules; Theuwissen, A.J.P.

2017-01-01

In this work, a novel approach is presented for measuring relative temperature variations inside the pixel array of a CMOS image sensor itself. This approach can give important information when compensation for dark (current) fixed pattern noise (FPN) is needed. The test image sensor consists of

White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

Science.gov (United States)

De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.

Performance evaluation of enterprise architecture with a formal fuzzy model (FPN

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Ashkan Marahel

2012-10-01

Full Text Available Preparing enterprise architecture is complicated procedure, which uses framework as structure regularity and style as the behavior director for controlling complexity. As in architecture behavior, precedence over structure, for better diagnosis of a behavior than other behaviors, there is a need to evaluate the architecture performance. Enterprise architecture cannot be organized without the benefit of the logical structure. Framework provides a logical structure for classifying architectural output. Among the common architectural framework, the C4ISR is one of the most appropriate frameworks because of the methodology of its production and the level of aggregation capability and minor revisions. C4ISR framework, in three views and by using some documents called product, describes the architecture. In this paper, for developing the systems, there are always uncertainties in information systems and we may use new version of UML called FUZZY-UML, which includes structure and behavior of the system. The proposed model of this paper also uses Fuzzy Petri nets to analyze the developed system.

Disrupted Module Efficiency of Structural and Functional Brain Connectomes in Clinically Isolated Syndrome and Multiple Sclerosis

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Yaou Liu

2018-04-01

Full Text Available Recent studies have demonstrated disrupted topological organization of brain connectome in multiple sclerosis (MS. However, whether the communication efficiency between different functional systems is affected in the early stage of MS remained largely unknown. In this study, we constructed the structural connectivity (SC and functional connectivity (FC networks in 41 patients with clinically isolated syndrome (CIS, 32 MS patients and 35 healthy controls (HC based on diffusion and resting-state functional MRI. To quantify the communication efficiency within and between different functional systems, we proposed two measures called intra- and inter-module efficiency. Based on the module parcellation of functional backbone network, the intra- and inter-module efficiency of SC and FC networks was calculated for each participant. For the SC network, CIS showed decreased inter-module efficiency between the sensory-motor network (SMN, the visual network (VN, the default-mode network (DMN and the fronto-parietal network (FPN compared with HC, while MS showed more widespread decreased module efficiency both within and between modules relative to HC and CIS. For the FC network, no differences were found between CIS and HC, and a decreased inter-module efficiency between SMN and FPN and between VN and FPN was identified in MS, compared with HC and CIS. Moreover, both intra- and inter-module efficiency of SC network were correlated with the disability and cognitive scores in MS. Therefore, our results demonstrated early SC changes between modules in CIS, and more widespread SC alterations and inter-module FC changes were observed in MS, which were further associated with cognitive impairment and physical disability.

Peter Nansen og Aalborg

DEFF Research Database (Denmark)

Bang, Karin

2005-01-01

Om Peter nansens tilknytning til Limfjordsegnen. Peter Nansen betragtede hele livet Aalborg som sin "hjemby" - det var her, han havde sin rod. Han kom til Aalborg som et-årig i april 1862, da hans far F.P.N. Nansen blev kapellan ved Budolfi Kirke. Mange af barndomsferierne tilbragte han hos sin...

Toll- like receptors expressed on embryonic macrophages couple inflammatory signals to iron metabolism during early ontogenesis

Czech Academy of Sciences Publication Activity Database

Balounová, Jana; Vavrochová, Tereza; Benešová, Martina; Ballek, Ondřej; Kolář, Michal; Filipp, Dominik

2014-01-01

Roč. 44, č. 5 (2014), s. 1491-1502 ISSN 0014-2980 R&D Projects: GA AV ČR IAA500520707 Institutional support: RVO:68378050 Keywords : Embryo nic macrophages * Ferroportin * Gene expression microarray * Iron metabolism * TLR stimulation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.034, year: 2014

Toll- like receptors expressed on embryonic macrophages couple inflammatory signals to iron metabolism during early ontogenesis

Czech Academy of Sciences Publication Activity Database

Balounová, Jana; Vavrochová, Tereza; Benešová, Martina; Ballek, Ondřej; Kolář, Michal; Filipp, Dominik

2014-01-01

Roč. 44, č. 5 (2014), s. 1491-1502 ISSN 0014-2980 R&D Projects: GA AV ČR IAA500520707 Institutional support: RVO:68378050 Keywords : Embryonic macrophages * Ferroportin * Gene expression microarray * Iron metabolism * TLR stimulation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.034, year: 2014

TIMP3 deficiency exacerbates iron overload-mediated cardiomyopathy and liver disease.

Science.gov (United States)

Zhabyeyev, Pavel; Das, Subhash K; Basu, Ratnadeep; Shen, Mengcheng; Patel, Vaibhav B; Kassiri, Zamaneh; Oudit, Gavin Y

2018-05-01

Chronic iron overload results in heart and liver diseases and is a common cause of morbidity and mortality in patients with genetic hemochromatosis and secondary iron overload. We investigated the role of tissue inhibitor of metalloproteinase 3 (TIMP3) in iron overload-mediated tissue injury by subjecting male mice lacking Timp3 ( Timp3 -/- ) and wild-type (WT) mice to 12 wk of chronic iron overload. Whereas WT mice with iron overload developed diastolic dysfunction, iron-overloaded Timp3 -/- mice showed worsened cardiac dysfunction coupled with systolic dysfunction. In the heart, loss of Timp3 was associated with increased myocardial fibrosis, greater Timp1, matrix metalloproteinase ( Mmp) 2, and Mmp9 expression, increased active MMP-2 levels, and gelatinase activity. Iron overload in Timp3 -/- mice showed twofold higher iron accumulation in the liver compared with WT mice because of constituently lower levels of ferroportin. Loss of Timp3 enhanced the hepatic inflammatory response to iron overload, leading to greater neutrophil and macrophage infiltration and increased hepatic fibrosis. Expression of inflammation-related MMPs (MMP-12 and MMP-13) and inflammatory cytokines (IL-1β and monocyte chemoattractant protein-1) was elevated to a greater extent in iron-overloaded Timp3 -/- livers. Gelatin zymography demonstrated equivalent increases in MMP-2 and MMP-9 levels in WT and Timp3 -/- iron-overloaded livers. Loss of Timp3 enhanced the susceptibility to iron overload-mediated heart and liver injury, suggesting that Timp3 is a key protective molecule against iron-mediated pathology. NEW & NOTEWORTHY In mice, loss of tissue inhibitor of metalloproteinase 3 ( Timp3) was associated with systolic and diastolic dysfunctions, twofold higher hepatic iron accumulation (attributable to constituently lower levels of ferroportin), and increased hepatic inflammation. Loss of Timp3 enhanced the susceptibility to iron overload-mediated injury, suggesting that Timp3 plays a key

Fluid Petri Nets and hybrid model-checking: a comparative case study

International Nuclear Information System (INIS)

Gribaudo, M.; Horvath, A.; Bobbio, A.; Tronci, E.; Ciancamerla, E.; Minichino, M.

2003-01-01

The modeling and analysis of hybrid systems is a recent and challenging research area which is actually dominated by two main lines: a functional analysis based on the description of the system in terms of discrete state (hybrid) automata (whose goal is to ascertain conformity and reachability properties), and a stochastic analysis (whose aim is to provide performance and dependability measures). This paper investigates a unifying view between formal methods and stochastic methods by proposing an analysis methodology of hybrid systems based on Fluid Petri Nets (FPNs). FPNs can be analyzed directly using appropriate tools. Our paper shows that the same FPN model can be fed to different functional analyzers for model checking. In order to extensively explore the capability of the technique, we have converted the original FPN into languages for discrete as well as hybrid as well as stochastic model checkers. In this way, a first comparison among the modeling power of well known tools can be carried out. Our approach is illustrated by means of a 'real world' hybrid system: the temperature control system of a co-generative plant

Inhibition of iron uptake is responsible for differential sensitivity to V-ATPase inhibitors in several cancer cell lines.

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Sarah Straud

2010-07-01

Full Text Available Many cell lines derived from tumors as well as transformed cell lines are far more sensitive to V-ATPase inhibitors than normal counterparts. The molecular mechanisms underlying these differences in sensitivity are not known. Using global gene expression data, we show that the most sensitive responses to HeLa cells to low doses of V-ATPase inhibitors involve genes responsive to decreasing intracellular iron or decreasing cholesterol and that sensitivity to iron uptake is an important determinant of V-ATPase sensitivity in several cancer cell lines. One of the most sensitive cell lines, melanoma derived SK-Mel-5, over-expresses the iron efflux transporter ferroportin and has decreased expression of proteins involved in iron uptake, suggesting that it actively suppresses cytoplasmic iron. SK-Mel-5 cells have increased production of reactive oxygen species and may be seeking to limit additional production of ROS by iron.

The impact of H63D HFE gene carriage on hemoglobin and iron status in children.

Science.gov (United States)

Barbara, Kaczorowska-Hac; Marcin, Luszczyk; Jedrzej, Antosiewicz; Wieslaw, Ziolkowski; Elzbieta, Adamkiewicz-Drozynska; Malgorzata, Mysliwiec; Ewa, Milosz; Jacek, Kaczor Jan

2016-12-01

The molecular mechanism that regulates iron homeostasis is based on a network of signals, which reflect on the iron requirements of the body. Hereditary hemochromatosis is a heterogenic metabolic syndrome which is due to unchecked transfer of iron into the bloodstream and its toxic effects on parenchymatous organs. It is caused by the mutation of genes that encode proteins that help hepcidin to monitor serum iron. These proteins include the human hemochromatosis protein -HFE, transferrin-receptor 2, hemojuvelin in rare instances, and ferroportin. HFE-related hemochromatosis is the most frequent form of the disease. Interestingly, the low penetrance of polymorphic HFE genes results in rare clinical presentation of the disease, predominantly in middle-aged males. Taking into account the wide dispersion of HFE mutation in our population and also its unknown role in heterozygotes, we analyzed the impact of H63D HFE carriage in the developmental age, with respect to gender, on the iron status and hemoglobin concentration of carriers in comparison to those of wild-type HFE gene (12.7 ± 3.07 years, 42 boys and 41 girls). H63D carriers presented higher blood iron, transferrin saturation, and ferritin concentration than wild-type probands (p HFE heterozygotes.

HO-1-mediated macroautophagy: a mechanism for unregulated iron deposition in aging and degenerating neural tissues.

Science.gov (United States)

Zukor, Hillel; Song, Wei; Liberman, Adrienne; Mui, Jeannie; Vali, Hojatollah; Fillebeen, Carine; Pantopoulos, Kostas; Wu, Ting-Di; Guerquin-Kern, Jean-Luc; Schipper, Hyman M

2009-05-01

Oxidative stress, deposition of non-transferrin iron, and mitochondrial insufficiency occur in the brains of patients with Alzheimer disease (AD) and Parkinson disease (PD). We previously demonstrated that heme oxygenase-1 (HO-1) is up-regulated in AD and PD brain and promotes the accumulation of non-transferrin iron in astroglial mitochondria. Herein, dynamic secondary ion mass spectrometry (SIMS) and other techniques were employed to ascertain (i) the impact of HO-1 over-expression on astroglial mitochondrial morphology in vitro, (ii) the topography of aberrant iron sequestration in astrocytes over-expressing HO-1, and (iii) the role of iron regulatory proteins (IRP) in HO-1-mediated iron deposition. Astroglial hHO-1 over-expression induced cytoplasmic vacuolation, mitochondrial membrane damage, and macroautophagy. HO-1 promoted trapping of redox-active iron and sulfur within many cytopathological profiles without impacting ferroportin, transferrin receptor, ferritin, and IRP2 protein levels or IRP1 activity. Thus, HO-1 activity promotes mitochondrial macroautophagy and sequestration of redox-active iron in astroglia independently of classical iron mobilization pathways. Glial HO-1 may be a rational therapeutic target in AD, PD, and other human CNS conditions characterized by the unregulated deposition of brain iron.

Acute Effects of Glucose and Fructose Administration on the Neural Correlates of Cognitive Functioning in Healthy Subjects: A Pilot Study

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Davide Zanchi

2018-03-01

Full Text Available The present randomized double-blinded cross-over study aims to extensively study the neural correlates underpinning cognitive functions in healthy subjects after acute glucose and fructose administration, using an integrative multimodal neuroimaging approach. Five minutes after glucose, fructose, or placebo administration through a nasogastric tube, 12 participants underwent 3 complementary neuroimaging techniques: 2 task-based functional magnetic resonance imaging (fMRI sequences to assess working memory (N-back and response inhibition (Go/No-Go and one resting state fMRI sequence to address the cognition-related fronto-parietal network (FPN and salience network (SN. During working memory processing, glucose intake decreased activation in the anterior cingulate cortex (ACC relative to placebo, while fructose decreased activation in the ACC and sensory cortex relative to placebo and glucose. During response inhibition, glucose and fructose decreased activation in the ACC, insula and visual cortex relative to placebo. Resting state fMRI indicated increased global connectivity strength of the FPN and the SN during glucose and fructose intake. The results demonstrate that glucose and fructose lead to partially different partially overlapping changes in regional brain activities that underpin cognitive performance in different tasks.

Rice and Bean Targets for Biofortification Combined with High Carotenoid Content Crops Regulate Transcriptional Mechanisms Increasing Iron Bioavailability

Science.gov (United States)

Dias, Desirrê Morais; de Castro Moreira, Maria Eliza; Gomes, Mariana Juste Contin; Lopes Toledo, Renata Celi; Nutti, Marilia Regini; Pinheiro Sant’Ana, Helena Maria; Martino, Hércia Stampini Duarte

2015-01-01

Iron deficiency affects thousands of people worldwide. Biofortification of staple food crops aims to support the reduction of this deficiency. This study evaluates the effect of combinations of common beans and rice, targets for biofortification, with high carotenoid content crops on the iron bioavailability, protein gene expression, and antioxidant effect. Iron bioavailability was measured by the depletion/repletion method. Seven groups were tested (n = 7): Pontal bean (PB); rice + Pontal bean (R + BP); Pontal bean + sweet potato (PB + SP); Pontal bean + pumpkin (PB + P); Pontal bean + rice + sweet potato (PB + R + P); Pontal bean + rice + sweet potato (PB + R + SP); positive control (Ferrous Sulfate). The evaluations included: hemoglobin gain, hemoglobin regeneration efficiency (HRE), gene expression of divalente metal transporter 1 (DMT-1), duodenal citocromo B (DcytB), ferroportin, hephaestin, transferrin and ferritin and total plasma antioxidant capacity (TAC). The test groups, except the PB, showed higher HRE (p bioavailability and antioxidant capacity. PMID:26610564

Hepcidin Protects Neuron from Hemin-Mediated Injury by Reducing Iron

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Yu-Fu Zhou

2017-05-01

Full Text Available Hemin plays a key role in mediating secondary neuronal injury after intracerebral hemorrhage (ICH and the cell toxicity of hemin is thought to be due to iron that is liberated when hemin is degraded. In a recent study, we demonstrated the iron regulatory hormone hepcidin reduces brain iron in iron-overloaded rats. Therefore, we hypothesized that hepcidin might be able to reduce iron and then protect neurons from hemin or iron-mediated neurotoxicity in hemin-treated neuronal cells. Here, we tested the hypothesis and demonstrated that ad-hepcidin and hepcidin peptide both have the ability to suppress the hemin-induced increase in LDH release and apoptotic cell numbers, to reduce cell iron and ferritin contents, and to inhibit expression of transferrin receptor 1, divalent metal transporter 1, and ferroportin 1 in hemin-treated neurons. We conclude that hepcidin protects neuron from hemin-mediated injury by reducing iron via inhibition of expression of iron transport proteins.

Technical Note: Modification of the standard gain correction algorithm to compensate for the number of used reference flat frames in detector performance studies

International Nuclear Information System (INIS)

Konstantinidis, Anastasios C.; Olivo, Alessandro; Speller, Robert D.

2011-01-01

Purpose: The x-ray performance evaluation of digital x-ray detectors is based on the calculation of the modulation transfer function (MTF), the noise power spectrum (NPS), and the resultant detective quantum efficiency (DQE). The flat images used for the extraction of the NPS should not contain any fixed pattern noise (FPN) to avoid contamination from nonstochastic processes. The ''gold standard'' method used for the reduction of the FPN (i.e., the different gain between pixels) in linear x-ray detectors is based on normalization with an average reference flat-field. However, the noise in the corrected image depends on the number of flat frames used for the average flat image. The aim of this study is to modify the standard gain correction algorithm to make it independent on the used reference flat frames. Methods: Many publications suggest the use of 10-16 reference flat frames, while other studies use higher numbers (e.g., 48 frames) to reduce the propagated noise from the average flat image. This study quantifies experimentally the effect of the number of used reference flat frames on the NPS and DQE values and appropriately modifies the gain correction algorithm to compensate for this effect. Results: It is shown that using the suggested gain correction algorithm a minimum number of reference flat frames (i.e., down to one frame) can be used to eliminate the FPN from the raw flat image. This saves computer memory and time during the x-ray performance evaluation. Conclusions: The authors show that the method presented in the study (a) leads to the maximum DQE value that one would have by using the conventional method and very large number of frames and (b) has been compared to an independent gain correction method based on the subtraction of flat-field images, leading to identical DQE values. They believe this provides robust validation of the proposed method.

Miraxanthin-V, Liriodenin and Chitranone are Hepcidin Antagonist In silico for Iron Deficiency Anemia

Science.gov (United States)

Yotriana, S.; Suselo, YH; Muthmainah; Indarto, D.

2018-03-01

Anemia is one of the greatest nutrition problem in the world that is commonly found in children, pregnant women and reproductive women. This disorder is predominantly caused by iron deficiency. Hepcidin, a hepatic hormone, regulates iron metabolism and high serum levels of this hormone are detected in patients with iron deficiency anemia (IDA). Anticalin is a sintetic compound which is able to interacts with hepcidin leading to inhibition of ferroportin-hepcidin binding complexes but its therapeutic effects are still under investigation. Indonesia has various herbal plants which are potentially developed to treat some human diseases. Therefore, the purpose of this study was to identify phytochemicals derived from Indonesian plants that is able to inhibit hepcidin-ferroportin interaction. A bioinformatics study with molecular docking method was used in this study. Three-dimensional structures of human hepcidin and anticalin were obtained from the Protein Data Bank (ID: 1M4F and 4QAE respectively). Because their molecular size was big, each molecule was cut into 2 parts of its binding sites. All phytochemicals structures were obtained from HerbalDB and PubChem NCBI database. Truncated anticalin/phytochemicals were molecularly docked with truncated hepcidin by using AutoDock Vina 1.1.2. and their interactions were visualized using PyMol 1.3. Truncated Anticalin had -4.6 and -4.2 kcal/mol binding affinity to truncated human hepcidin. Truncated anticalin 1 was bound to Cys13, Cys14, Arg16 and Ser17 residues in truncated hepcidin 1 while truncated anticalin 2 was at Cy23 and Lys24 residues in truncated hepcidin 2. Miraxanthine-V, Liriodenin and Chitranone had lower binding affinity (-4.8±0.77, -4.7±0.33 and -5.01±0.30 kcal/mol respectively) than that of anticalin and occupied binding sites as same as anticalin did. There are three phytochemicals that potentially become hepcidin antagonists in silico. In vitro assays are required for verification of the antagonist

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

Science.gov (United States)

Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

2018-05-01

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

Basic mechanisms of iron metabolism regulation and their clinical significance

Directory of Open Access Journals (Sweden)

L. M. Meshсheryakova

2014-01-01

Full Text Available This article is а composition of literature and experimental data of iron metabolism. There were studied the level of DMT-1, ferroportin, hepcidin at different stages of anemia and hemochromatosis. It is clear that the level of DMT-1 regulates by the hepcidin. Increaseing of the hepcidin concentration and decreasing DMT-1 level in patients with hemochromatosis explained good results of treatment.

Basic mechanisms of iron metabolism regulation and their clinical significance

Directory of Open Access Journals (Sweden)

L. M. Meshсheryakova

2015-01-01

Full Text Available This article is а composition of literature and experimental data of iron metabolism. There were studied the level of DMT-1, ferroportin, hepcidin at different stages of anemia and hemochromatosis. It is clear that the level of DMT-1 regulates by the hepcidin. Increaseing of the hepcidin concentration and decreasing DMT-1 level in patients with hemochromatosis explained good results of treatment.

Preclinical cerebral network connectivity evidence of deficits in mild white matter lesions

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Ying eLiang

2016-02-01

Full Text Available White matter lesions (WMLs are notable for their high prevalence and have been demonstrated to be a potential neuroimaging biomarker of early diagnosis of Alzheimer’s disease. This study aimed to identify the brain functional and structural mechanisms underlying cognitive decline observed in mild WMLs. Multi-domain cognitive tests, as well as resting-state, diffusion tensor and structural images were obtained on 42 mild WMLs and 42 age/sex-matched healthy controls. For each participant, we examined the functional connectivity of three resting-state networks related to the changed cognitive domains: the default mode network (DMN and the bilateral fronto-parietal network (FPN. We also performed voxel-based morphometry analysis to compare whole-brain gray matter volume, atlas-based quantification of the white matter tracts interconnecting the RSNs, and the relationship between functional connectivity and structural connectivity. We observed functional connectivity alterations in the DMN and the right FPN combined with related white matter integrity disruption in mild WMLs. However, no significant gray matter atrophy difference was found. Furthermore, the right precuneus functional connectivity in the DMN exhibited a significantly negative correlation with the memory test scores. Our study suggests that in mild WMLs, dysfunction of RSNs might be a consequence of decreased white matter structural connectivity, which further affects cognitive performance.

A Two-Step A/D Conversion and Column Self-Calibration Technique for Low Noise CMOS Image Sensors

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Jaeyoung Bae

2014-07-01

Full Text Available In this paper, a 120 frames per second (fps low noise CMOS Image Sensor (CIS based on a Two-Step Single Slope ADC (TS SS ADC and column self-calibration technique is proposed. The TS SS ADC is suitable for high speed video systems because its conversion speed is much faster (by more than 10 times than that of the Single Slope ADC (SS ADC. However, there exist some mismatching errors between the coarse block and the fine block due to the 2-step operation of the TS SS ADC. In general, this makes it difficult to implement the TS SS ADC beyond a 10-bit resolution. In order to improve such errors, a new 4-input comparator is discussed and a high resolution TS SS ADC is proposed. Further, a feedback circuit that enables column self-calibration to reduce the Fixed Pattern Noise (FPN is also described. The proposed chip has been fabricated with 0.13 μm Samsung CIS technology and the chip satisfies the VGA resolution. The pixel is based on the 4-TR Active Pixel Sensor (APS. The high frame rate of 120 fps is achieved at the VGA resolution. The measured FPN is 0.38 LSB, and measured dynamic range is about 64.6 dB.

Protein docking prediction using predicted protein-protein interface

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Li Bin

2012-01-01

Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Protein docking prediction using predicted protein-protein interface.

Science.gov (United States)

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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Peng Liu

2015-01-01

Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

Oligomeric protein structure networks: insights into protein-protein interactions

Directory of Open Access Journals (Sweden)

Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Protein nanoparticles for therapeutic protein delivery.

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Herrera Estrada, L P; Champion, J A

2015-06-01

Therapeutic proteins can face substantial challenges to their activity, requiring protein modification or use of a delivery vehicle. Nanoparticles can significantly enhance delivery of encapsulated cargo, but traditional small molecule carriers have some limitations in their use for protein delivery. Nanoparticles made from protein have been proposed as alternative carriers and have benefits specific to therapeutic protein delivery. This review describes protein nanoparticles made by self-assembly, including protein cages, protein polymers, and charged or amphipathic peptides, and by desolvation. It presents particle fabrication and delivery characterization for a variety of therapeutic and model proteins, as well as comparison of the features of different protein nanoparticles.

Etude du faible poids de naissance associé à l'âge maternel et la ...

African Journals Online (AJOL)

Introduction: évaluer l'influence de l'âge maternel et de la parité sur la naissance d'un faible poids de naissance (FPN) à Lubumbashi. Méthodes: il s'agit d'une étude basée sur une analyse documentaire des dossiers médicaux des accouchées enregistrées dans les maternités des 10 hôpitaux généraux de référence ...

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

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Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Truly Absorbed Microbial Protein Synthesis, Rumen Bypass Protein, Endogenous Protein, and Total Metabolizable Protein from Starchy and Protein-Rich Raw Materials

NARCIS (Netherlands)

Parand, Ehsan; Vakili, Alireza; Mesgaran, Mohsen Danesh; Duinkerken, Van Gert; Yu, Peiqiang

2015-01-01

This study was carried out to measure truly absorbed microbial protein synthesis, rumen bypass protein, and endogenous protein loss, as well as total metabolizable protein, from starchy and protein-rich raw feed materials with model comparisons. Predictions by the DVE2010 system as a more

Study of Scientific Production of Community Medicines' Department Indexed in ISI Citation Databases.

Science.gov (United States)

Khademloo, Mohammad; Khaseh, Ali Akbar; Siamian, Hasan; Aligolbandi, Kobra; Latifi, Mahsoomeh; Yaminfirooz, Mousa

2016-10-01

presentation of 340(85.86%) articles had presented most of their scientific productions in the format of article, also in the field of community medicine outputs, article entitled: "Iron loading and erythrophagocytosis increase ferroportin 1 (FPN1) expression in J774 macrophages"(1) with 81 citations ranked first in cited articles. Subject areas of occupational health with 70 articles and subject areas of general medicine with 69 articles ranked the most active research areas in the Production of community medicine's department. the obtained data showed the much growth of scientific production. The Tehran University of medical Sciences ranked the first in publishing articles in community medicine's department and with most collaboration with community medicine department of England writers in this field and most writers will present their works in paper format.

Complexity of hierarchically and 1-dimensional periodically specified problems

Energy Technology Data Exchange (ETDEWEB)

Marathe, M.V.; Hunt, H.B. III; Stearns, R.E.; Radhakrishnan, V.

1995-08-23

We study the complexity of various combinatorial and satisfiability problems when instances are specified using one of the following specifications: (1) the 1-dimensional finite periodic narrow specifications of Wanke and Ford et al. (2) the 1-dimensional finite periodic narrow specifications with explicit boundary conditions of Gale (3) the 2-way infinite1-dimensional narrow periodic specifications of Orlin et al. and (4) the hierarchical specifications of Lengauer et al. we obtain three general types of results. First, we prove that there is a polynomial time algorithm that given a 1-FPN- or 1-FPN(BC)specification of a graph (or a C N F formula) constructs a level-restricted L-specification of an isomorphic graph (or formula). This theorem along with the hardness results proved here provides alternative and unified proofs of many hardness results proved in the past either by Lengauer and Wagner or by Orlin. Second, we study the complexity of generalized CNF satisfiability problems of Schaefer. Assuming P {ne} PSPACE, we characterize completely the polynomial time solvability of these problems, when instances are specified as in (1), (2),(3) or (4). As applications of our first two types of results, we obtain a number of new PSPACE-hardness and polynomial time algorithms for problems specified as in (1), (2), (3) or(4). Many of our results also hold for O(log N) bandwidth bounded planar instances.

Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

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Ruzianisra Mohamed

Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

Protein- protein interaction detection system using fluorescent protein microdomains

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Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

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Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Protein-protein interaction network-based detection of functionally similar proteins within species.

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Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Protein-Protein Docking in Drug Design and Discovery.

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Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Inflammation and ER Stress Downregulate BDH2 Expression and Dysregulate Intracellular Iron in Macrophages

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Susu M. Zughaier

2014-01-01

Full Text Available Macrophages play a very important role in host defense and in iron homeostasis by engulfing senescent red blood cells and recycling iron. Hepcidin is the master iron regulating hormone that limits dietary iron absorption from the gut and limits iron egress from macrophages. Upon infection macrophages retain iron to limit its bioavailability which limits bacterial growth. Recently, a short chain butyrate dehydrogenase type 2 (BDH2 protein was reported to contain an iron responsive element and to mediate cellular iron trafficking by catalyzing the synthesis of the mammalian siderophore that binds labile iron; therefore, BDH2 plays a crucial role in intracellular iron homeostasis. However, BDH2 expression and regulation in macrophages have not yet been described. Here we show that LPS-induced inflammation combined with ER stress led to massive BDH2 downregulation, increased the expression of ER stress markers, upregulated hepcidin expression, downregulated ferroportin expression, caused iron retention in macrophages, and dysregulated cytokine release from macrophages. We also show that ER stress combined with inflammation synergistically upregulated the expression of the iron carrier protein NGAL and the stress-inducible heme degrading enzyme heme oxygenase-1 (HO-1 leading to iron liberation. This is the first report to show that inflammation and ER stress downregulate the expression of BDH2 in human THP-1 macrophages.

Evolution of protein-protein interactions

Indian Academy of Sciences (India)

Evolution of protein-protein interactions · Our interests in protein-protein interactions · Slide 3 · Slide 4 · Slide 5 · Slide 6 · Slide 7 · Slide 8 · Slide 9 · Slide 10 · Slide 11 · Slide 12 · Slide 13 · Slide 14 · Slide 15 · Slide 16 · Slide 17 · Slide 18 · Slide 19 · Slide 20.

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Protein Structure Prediction by Protein Threading

Science.gov (United States)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

Specificity and affinity quantification of protein-protein interactions.

Science.gov (United States)

Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

2013-05-01

Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

Coarse-grain modelling of protein-protein interactions

NARCIS (Netherlands)

Baaden, Marc; Marrink, Siewert J.

2013-01-01

Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

Science.gov (United States)

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

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Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

Directory of Open Access Journals (Sweden)

Meijing Li

2015-01-01

Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

Directory of Open Access Journals (Sweden)

Raed I. Hamed

2015-04-01

Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.

Protein complex prediction in large ontology attributed protein-protein interaction networks.

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Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

Protein surface shielding agents in protein crystallization

International Nuclear Information System (INIS)

Hašek, J.

2011-01-01

The crystallization process can be controlled by protein surface shielding agents blocking undesirable competitive adhesion modes during non-equilibrium processes of deposition of protein molecules on the surface of growing crystalline blocks. The hypothesis is based on a number of experimental proofs from diffraction experiments and also retrieved from the Protein Data Bank. The molecules adhering temporarily on the surface of protein molecules change the propensity of protein molecules to deposit on the crystal surface in a definite position and orientation. The concepts of competitive adhesion modes and protein surface shielding agents acting on the surface of molecules in a non-equilibrium process of protein crystallization provide a useful platform for the control of crystallization. The desirable goal, i.e. a transient preference of a single dominating adhesion mode between protein molecules during crystallization, leads to uniform deposition of proteins in a crystal. This condition is the most important factor for diffraction quality and thus also for the accuracy of protein structure determination. The presented hypothesis is a generalization of the experimentally well proven behaviour of hydrophilic polymers on the surface of protein molecules of other compounds

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

Science.gov (United States)

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Effect of excess iron on oxidative stress and gluconeogenesis through hepcidin during mitochondrial dysfunction.

Science.gov (United States)

Lee, Hyo Jung; Choi, Joo Sun; Lee, Hye Ja; Kim, Won-Ho; Park, Sang Ick; Song, Jihyun

2015-12-01

Excessive tissue iron levels are a risk factor for insulin resistance and type 2 diabetes, which are associated with alterations in iron metabolism. However, the mechanisms underlying this association are not well understood. This study used human liver SK-HEP-1 cells to examine how excess iron induces mitochondrial dysfunction and how hepcidin controls gluconeogenesis. Excess levels of reactive oxygen species (ROS) and accumulated iron due to iron overload induced mitochondrial dysfunction, leading to a decrease in cellular adenosine triphosphate content and cytochrome c oxidase III expression, with an associated increase in gluconeogenesis. Disturbances in mitochondrial function caused excess iron deposition and unbalanced expression of iron metabolism-related proteins such as hepcidin, ferritin H and ferroportin during the activation of p38 mitogen-activated protein kinase (MAPK) and CCAAT/enhancer-binding protein alpha (C/EBPα), which are responsible for increased phosphoenolpyruvate carboxykinase expression. Desferoxamine and n-acetylcysteine ameliorated these deteriorations by inhibiting p38 MAPK and C/EBPα activity through iron chelation and ROS scavenging activity. Based on experiments using hepcidin shRNA and hepcidin overexpression, the activation of hepcidin affects ROS generation and iron deposition, which disturbs mitochondrial function and causes an imbalance in iron metabolism and increased gluconeogenesis. Repression of hepcidin activity can reverse these changes. Our results demonstrate that iron overload is associated with mitochondrial dysfunction and that together they can cause abnormal hepatic gluconeogenesis. Hepcidin expression may modulate this disorder by regulating ROS generation and iron deposition. Copyright © 2015 Elsevier Inc. All rights reserved.

Protein sequence comparison and protein evolution

Energy Technology Data Exchange (ETDEWEB)

Pearson, W.R. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Biochemistry

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. This tutorial examines how the information conserved during the evolution of a protein molecule can be used to infer reliably homology, and thus a shared proteinfold and possibly a shared active site or function. The authors start by reviewing a geological/evolutionary time scale. Next they look at the evolution of several protein families. During the tutorial, these families will be used to demonstrate that homologous protein ancestry can be inferred with confidence. They also examine different modes of protein evolution and consider some hypotheses that have been presented to explain the very earliest events in protein evolution. The next part of the tutorial will examine the technical aspects of protein sequence comparison. Both optimal and heuristic algorithms and their associated parameters that are used to characterize protein sequence similarities are discussed. Perhaps more importantly, they survey the statistics of local similarity scores, and how these statistics can both be used to improve the selectivity of a search and to evaluate the significance of a match. They them examine distantly related members of three protein families, the serine proteases, the glutathione transferases, and the G-protein-coupled receptors (GCRs). Finally, the discuss how sequence similarity can be used to examine internal repeated or mosaic structures in proteins.

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

DEFF Research Database (Denmark)

Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

Science.gov (United States)

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

The effect of protein-protein and protein-membrane interactions on membrane fouling in ultrafiltration

NARCIS (Netherlands)

Huisman, I.H.; Prádanos, P.; Hernández, A.

2000-01-01

It was studied how protein-protein and protein-membrane interactions influence the filtration performance during the ultrafiltration of protein solutions over polymeric membranes. This was done by measuring flux, streaming potential, and protein transmission during filtration of bovine serum albumin

Fluorogen-activating proteins: beyond classical fluorescent proteins

Directory of Open Access Journals (Sweden)

Shengnan Xu

2018-05-01

Full Text Available Fluorescence imaging is a powerful technique for the real-time noninvasive monitoring of protein dynamics. Recently, fluorogen activating proteins (FAPs/fluorogen probes for protein imaging were developed. Unlike the traditional fluorescent proteins (FPs, FAPs do not fluoresce unless bound to their specific small-molecule fluorogens. When using FAPs/fluorogen probes, a washing step is not required for the removal of free probes from the cells, thus allowing rapid and specific detection of proteins in living cells with high signal-to-noise ratio. Furthermore, with different fluorogens, living cell multi-color proteins labeling system was developed. In this review, we describe about the discovery of FAPs, the design strategy of FAP fluorogens, the application of the FAP technology and the advances of FAP technology in protein labeling systems. KEY WORDS: Fluorogen activating proteins, Fluorogens, Genetically encoded sensors, Fluorescence imaging, Molecular imaging

Test stand for non-uniformity correction of microbolometer focal plane arrays used in thermal cameras

Science.gov (United States)

Krupiński, Michał; Bareła, Jaroslaw; Firmanty, Krzysztof; Kastek, Mariusz

2013-10-01

Uneven response of particular detectors (pixels) to the same incident power of infrared radiation is an inherent feature of microbolometer focal plane arrays. As a result an image degradation occurs, known as Fixed Pattern Noise (FPN), which distorts the thermal representation of an observed scene and impairs the parameters of a thermal camera. In order to compensate such non-uniformity, several NUC correction methods are applied in digital data processing modules implemented in thermal cameras. Coefficients required to perform the non-uniformity correction procedure (NUC coefficients) are determined by calibrating the camera against uniform radiation sources (blackbodies). Non-uniformity correction is performed in a digital processing unit in order to remove FPN pattern in the registered thermal images. Relevant correction coefficients are calculated on the basis of recorded detector responses to several values of radiant flux emitted from reference IR radiation sources (blackbodies). The measurement of correction coefficients requires specialized setup, in which uniform, extended radiation sources with high temperature stability are one of key elements. Measurement stand for NUC correction developed in Institute of Optoelectronics, MUT, comprises two integrated extended blackbodies with the following specifications: area 200×200 mm, stabilized absolute temperature range +15 °C÷100 °C, and uniformity of temperature distribution across entire surface +/-0.014 °C. Test stand, method used for the measurement of NUC coefficients and the results obtained during the measurements conducted on a prototype thermal camera will be presented in the paper.

Protein immobilization strategies for protein biochips

NARCIS (Netherlands)

Rusmini, F.; Rusmini, Federica; Zhong, Zhiyuan; Feijen, Jan

2007-01-01

In the past few years, protein biochips have emerged as promising proteomic and diagnostic tools for obtaining information about protein functions and interactions. Important technological innovations have been made. However, considerable development is still required, especially regarding protein

Protein Molecular Structures, Protein SubFractions, and Protein Availability Affected by Heat Processing: A Review

International Nuclear Information System (INIS)

Yu, P.

2007-01-01

The utilization and availability of protein depended on the types of protein and their specific susceptibility to enzymatic hydrolysis (inhibitory activities) in the gastrointestine and was highly associated with protein molecular structures. Studying internal protein structure and protein subfraction profiles leaded to an understanding of the components that make up a whole protein. An understanding of the molecular structure of the whole protein was often vital to understanding its digestive behavior and nutritive value in animals. In this review, recently obtained information on protein molecular structural effects of heat processing was reviewed, in relation to protein characteristics affecting digestive behavior and nutrient utilization and availability. The emphasis of this review was on (1) using the newly advanced synchrotron technology (S-FTIR) as a novel approach to reveal protein molecular chemistry affected by heat processing within intact plant tissues; (2) revealing the effects of heat processing on the profile changes of protein subfractions associated with digestive behaviors and kinetics manipulated by heat processing; (3) prediction of the changes of protein availability and supply after heat processing, using the advanced DVE/OEB and NRC-2001 models, and (4) obtaining information on optimal processing conditions of protein as intestinal protein source to achieve target values for potential high net absorbable protein in the small intestine. The information described in this article may give better insight in the mechanisms involved and the intrinsic protein molecular structural changes occurring upon processing.

Information assessment on predicting protein-protein interactions

Directory of Open Access Journals (Sweden)

Gerstein Mark

2004-10-01

Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

Mapping Protein-Protein Interactions by Quantitative Proteomics

DEFF Research Database (Denmark)

Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

2010-01-01

spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...... to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions.......Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...

ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval.

Science.gov (United States)

Wang, Jingyan; Gao, Xin; Wang, Quanquan; Li, Yongping

2012-05-08

The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database. In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N(i) and N(j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N(i) and N(j).Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update the Protein Hierarchial

Biophysics of protein evolution and evolutionary protein biophysics

Science.gov (United States)

Sikosek, Tobias; Chan, Hue Sun

2014-01-01

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599

High quality protein microarray using in situ protein purification

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Fleischmann Robert D

2009-08-01

Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

Can infrared spectroscopy provide information on protein-protein interactions?

Science.gov (United States)

Haris, Parvez I

2010-08-01

For most biophysical techniques, characterization of protein-protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600-1700 cm(-1)) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with (13)C or (13)C,(15)N has been introduced as a solution to this problem, enabling the study of protein-protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm(-1) towards lower frequency) upon (13)C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein-protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein-protein interactions are provided.

Protein and protein hydrolysates in sports nutrition.

Science.gov (United States)

van Loon, Luc J C; Kies, Arie K; Saris, Wim H M

2007-08-01

With the increasing knowledge about the role of nutrition in increasing exercise performance, it has become clear over the last 2 decades that amino acids, protein, and protein hydrolysates can play an important role. Most of the attention has been focused on their effects at a muscular level. As these nutrients are ingested, however, it also means that gastrointestinal digestibility and absorption can modulate their efficacy significantly. Therefore, discussing the role of amino acids, protein, and protein hydrolysates in sports nutrition entails holding a discussion on all levels of the metabolic route. On May 28-29, 2007, a small group of researchers active in the field of exercise science and protein metabolism presented an overview of the different aspects of the application of protein and protein hydrolysates in sports nutrition. In addition, they were asked to share their opinions on the future progress in their fields of research. In this overview, an introduction to the workshop and a short summary of its outcome is provided.

ProDis-ContSHC: Learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval

KAUST Repository

Wang, Jim Jing-Yan

2012-05-08

Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database.Results: In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N (i) and N (j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N (i) and N (j). Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update

Targeting protein-protein interaction between MLL1 and reciprocal proteins for leukemia therapy.

Science.gov (United States)

Wang, Zhi-Hui; Li, Dong-Dong; Chen, Wei-Lin; You, Qi-Dong; Guo, Xiao-Ke

2018-01-15

The mixed lineage leukemia protein-1 (MLL1), as a lysine methyltransferase, predominantly regulates the methylation of histone H3 lysine 4 (H3K4) and functions in hematopoietic stem cell (HSC) self-renewal. MLL1 gene fuses with partner genes that results in the generation of MLL1 fusion proteins (MLL1-FPs), which are frequently detected in acute leukemia. In the progress of leukemogenesis, a great deal of proteins cooperate with MLL1 to form multiprotein complexes serving for the dysregulation of H3K4 methylation, the overexpression of homeobox (HOX) cluster genes, and the consequent generation of leukemia. Hence, disrupting the interactions between MLL1 and the reciprocal proteins has been considered to be a new treatment strategy for leukemia. Here, we reviewed potential protein-protein interactions (PPIs) between MLL1 and its reciprocal proteins, and summarized the inhibitors to target MLL1 PPIs. The druggability of MLL1 PPIs for leukemia were also discussed. Copyright © 2017. Published by Elsevier Ltd.

Protein kinase substrate identification on functional protein arrays

Directory of Open Access Journals (Sweden)

Zhou Fang

2008-02-01

Full Text Available Abstract Background Over the last decade, kinases have emerged as attractive therapeutic targets for a number of different diseases, and numerous high throughput screening efforts in the pharmaceutical community are directed towards discovery of compounds that regulate kinase function. The emerging utility of systems biology approaches has necessitated the development of multiplex tools suitable for proteomic-scale experiments to replace lower throughput technologies such as mass spectroscopy for the study of protein phosphorylation. Recently, a new approach for identifying substrates of protein kinases has applied the miniaturized format of functional protein arrays to characterize phosphorylation for thousands of candidate protein substrates in a single experiment. This method involves the addition of protein kinases in solution to arrays of immobilized proteins to identify substrates using highly sensitive radioactive detection and hit identification algorithms. Results To date, the factors required for optimal performance of protein array-based kinase substrate identification have not been described. In the current study, we have carried out a detailed characterization of the protein array-based method for kinase substrate identification, including an examination of the effects of time, buffer compositions, and protein concentration on the results. The protein array approach was compared to standard solution-based assays for assessing substrate phosphorylation, and a correlation of greater than 80% was observed. The results presented here demonstrate how novel substrates for protein kinases can be quickly identified from arrays containing thousands of human proteins to provide new clues to protein kinase function. In addition, a pooling-deconvolution strategy was developed and applied that enhances characterization of specific kinase-substrate relationships and decreases reagent consumption. Conclusion Functional protein microarrays are an

Protein kinesis: The dynamics of protein trafficking and stability

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-31

The purpose of this conference is to provide a multidisciplinary forum for exchange of state-of-the-art information on protein kinesis. This volume contains abstracts of papers in the following areas: protein folding and modification in the endoplasmic reticulum; protein trafficking; protein translocation and folding; protein degradation; polarity; nuclear trafficking; membrane dynamics; and protein import into organelles.

HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

Directory of Open Access Journals (Sweden)

Xiaomin Wang

2011-01-01

Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

Molecular tweezers modulate 14-3-3 protein-protein interactions

Science.gov (United States)

Bier, David; Rose, Rolf; Bravo-Rodriguez, Kenny; Bartel, Maria; Ramirez-Anguita, Juan Manuel; Dutt, Som; Wilch, Constanze; Klärner, Frank-Gerrit; Sanchez-Garcia, Elsa; Schrader, Thomas; Ottmann, Christian

2013-03-01

Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins—a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)—in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions.

Changes in protein composition and protein phosphorylation during ...

African Journals Online (AJOL)

Changes in protein profiles and protein phosphorylation were studied in various stages of germinating somatic and zygotic embryos. Many proteins, which were expressed in cotyledonary stage somatic embryos, were also present in the zygotic embryos obtained from mature dry seed. The intensity of 22 kDa protein was ...

An ontology-based search engine for protein-protein interactions.

Science.gov (United States)

Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

Water-Protein Interactions: The Secret of Protein Dynamics

Directory of Open Access Journals (Sweden)

Silvia Martini

2013-01-01

Full Text Available Water-protein interactions help to maintain flexible conformation conditions which are required for multifunctional protein recognition processes. The intimate relationship between the protein surface and hydration water can be analyzed by studying experimental water properties measured in protein systems in solution. In particular, proteins in solution modify the structure and the dynamics of the bulk water at the solute-solvent interface. The ordering effects of proteins on hydration water are extended for several angstroms. In this paper we propose a method for analyzing the dynamical properties of the water molecules present in the hydration shells of proteins. The approach is based on the analysis of the effects of protein-solvent interactions on water protons NMR relaxation parameters. NMR relaxation parameters, especially the nonselective (R1NS and selective (R1SE spin-lattice relaxation rates of water protons, are useful for investigating the solvent dynamics at the macromolecule-solvent interfaces as well as the perturbation effects caused by the water-macromolecule interactions on the solvent dynamical properties. In this paper we demonstrate that Nuclear Magnetic Resonance Spectroscopy can be used to determine the dynamical contributions of proteins to the water molecules belonging to their hydration shells.

Two Chimeric Regulators of G-protein Signaling (RGS) Proteins Differentially Modulate Soybean Heterotrimeric G-protein Cycle*

Science.gov (United States)

Roy Choudhury, Swarup; Westfall, Corey S.; Laborde, John P.; Bisht, Naveen C.; Jez, Joseph M.; Pandey, Sona

2012-01-01

Heterotrimeric G-proteins and the regulator of G-protein signaling (RGS) proteins, which accelerate the inherent GTPase activity of Gα proteins, are common in animals and encoded by large gene families; however, in plants G-protein signaling is thought to be more limited in scope. For example, Arabidopsis thaliana contains one Gα, one Gβ, three Gγ, and one RGS protein. Recent examination of the Glycine max (soybean) genome reveals a larger set of G-protein-related genes and raises the possibility of more intricate G-protein networks than previously observed in plants. Stopped-flow analysis of GTP-binding and GDP/GTP exchange for the four soybean Gα proteins (GmGα1–4) reveals differences in their kinetic properties. The soybean genome encodes two chimeric RGS proteins with an N-terminal seven transmembrane domain and a C-terminal RGS box. Both GmRGS interact with each of the four GmGα and regulate their GTPase activity. The GTPase-accelerating activities of GmRGS1 and -2 differ for each GmGα, suggesting more than one possible rate of the G-protein cycle initiated by each of the Gα proteins. The differential effects of GmRGS1 and GmRGS2 on GmGα1–4 result from a single valine versus alanine difference. The emerging picture suggests complex regulation of the G-protein cycle in soybean and in other plants with expanded G-protein networks. PMID:22474294

Alignment of non-covalent interactions at protein-protein interfaces.

Directory of Open Access Journals (Sweden)

Hongbo Zhu

Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

Science.gov (United States)

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

Directory of Open Access Journals (Sweden)

Ching-Tai Chen

Full Text Available Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins and were tested on an independent dataset (consisting of 142 proteins. The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Science.gov (United States)

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

Bioinformatic Prediction of WSSV-Host Protein-Protein Interaction

Directory of Open Access Journals (Sweden)

Zheng Sun

2014-01-01

Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.

Protein subcellular localization assays using split fluorescent proteins

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Waldo, Geoffrey S [Santa Fe, NM; Cabantous, Stephanie [Los Alamos, NM

2009-09-08

The invention provides protein subcellular localization assays using split fluorescent protein systems. The assays are conducted in living cells, do not require fixation and washing steps inherent in existing immunostaining and related techniques, and permit rapid, non-invasive, direct visualization of protein localization in living cells. The split fluorescent protein systems used in the practice of the invention generally comprise two or more self-complementing fragments of a fluorescent protein, such as GFP, wherein one or more of the fragments correspond to one or more beta-strand microdomains and are used to "tag" proteins of interest, and a complementary "assay" fragment of the fluorescent protein. Either or both of the fragments may be functionalized with a subcellular targeting sequence enabling it to be expressed in or directed to a particular subcellular compartment (i.e., the nucleus).

Human cancer protein-protein interaction network: a structural perspective.

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Gozde Kar

2009-12-01

Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

Hot-spot analysis for drug discovery targeting protein-protein interactions.

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Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Interaction between plate make and protein in protein crystallisation screening.

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Gordon J King

Full Text Available BACKGROUND: Protein crystallisation screening involves the parallel testing of large numbers of candidate conditions with the aim of identifying conditions suitable as a starting point for the production of diffraction quality crystals. Generally, condition screening is performed in 96-well plates. While previous studies have examined the effects of protein construct, protein purity, or crystallisation condition ingredients on protein crystallisation, few have examined the effect of the crystallisation plate. METHODOLOGY/PRINCIPAL FINDINGS: We performed a statistically rigorous examination of protein crystallisation, and evaluated interactions between crystallisation success and plate row/column, different plates of same make, different plate makes and different proteins. From our analysis of protein crystallisation, we found a significant interaction between plate make and the specific protein being crystallised. CONCLUSIONS/SIGNIFICANCE: Protein crystal structure determination is the principal method for determining protein structure but is limited by the need to produce crystals of the protein under study. Many important proteins are difficult to crystallize, so that identification of factors that assist crystallisation could open up the structure determination of these more challenging targets. Our findings suggest that protein crystallisation success may be improved by matching a protein with its optimal plate make.

Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

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Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

2013-01-01

We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

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Peiying Ruan

Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.

NMR Studies of Protein Hydration and Protein-Ligand Interactions

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Chong, Yuan

Water on the surface of a protein is called hydration water. Hydration water is known to play a crucial role in a variety of biological processes including protein folding, enzymatic activation, and drug binding. Although the significance of hydration water has been recognized, the underlying mechanism remains far from being understood. This dissertation employs a unique in-situ nuclear magnetic resonance (NMR) technique to study the mechanism of protein hydration and the role of hydration in alcohol-protein interactions. Water isotherms in proteins are measured at different temperatures via the in-situ NMR technique. Water is found to interact differently with hydrophilic and hydrophobic groups on the protein. Water adsorption on hydrophilic groups is hardly affected by the temperature, while water adsorption on hydrophobic groups strongly depends on the temperature around 10 C, below which the adsorption is substantially reduced. This effect is induced by the dramatic decrease in the protein flexibility below 10 C. Furthermore, nanosecond to microsecond protein dynamics and the free energy, enthalpy, and entropy of protein hydration are studied as a function of hydration level and temperature. A crossover at 10 C in protein dynamics and thermodynamics is revealed. The effect of water at hydrophilic groups on protein dynamics and thermodynamics shows little temperature dependence, whereas water at hydrophobic groups has stronger effect above 10 C. In addition, I investigate the role of water in alcohol binding to the protein using the in-situ NMR detection. The isotherms of alcohols are first measured on dry proteins, then on proteins with a series of controlled hydration levels. The free energy, enthalpy, and entropy of alcohol binding are also determined. Two distinct types of alcohol binding are identified. On the one hand, alcohols can directly bind to a few specific sites on the protein. This type of binding is independent of temperature and can be

Mapping monomeric threading to protein-protein structure prediction.

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Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

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Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

A credit-card library approach for disrupting protein-protein interactions.

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Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

2006-04-15

Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

Protein Correlation Profiles Identify Lipid Droplet Proteins with High Confidence*

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Krahmer, Natalie; Hilger, Maximiliane; Kory, Nora; Wilfling, Florian; Stoehr, Gabriele; Mann, Matthias; Farese, Robert V.; Walther, Tobias C.

2013-01-01

Lipid droplets (LDs) are important organelles in energy metabolism and lipid storage. Their cores are composed of neutral lipids that form a hydrophobic phase and are surrounded by a phospholipid monolayer that harbors specific proteins. Most well-established LD proteins perform important functions, particularly in cellular lipid metabolism. Morphological studies show LDs in close proximity to and interacting with membrane-bound cellular organelles, including the endoplasmic reticulum, mitochondria, peroxisomes, and endosomes. Because of these close associations, it is difficult to purify LDs to homogeneity. Consequently, the confident identification of bona fide LD proteins via proteomics has been challenging. Here, we report a methodology for LD protein identification based on mass spectrometry and protein correlation profiles. Using LD purification and quantitative, high-resolution mass spectrometry, we identified LD proteins by correlating their purification profiles to those of known LD proteins. Application of the protein correlation profile strategy to LDs isolated from Drosophila S2 cells led to the identification of 111 LD proteins in a cellular LD fraction in which 1481 proteins were detected. LD localization was confirmed in a subset of identified proteins via microscopy of the expressed proteins, thereby validating the approach. Among the identified LD proteins were both well-characterized LD proteins and proteins not previously known to be localized to LDs. Our method provides a high-confidence LD proteome of Drosophila cells and a novel approach that can be applied to identify LD proteins of other cell types and tissues. PMID:23319140

ProteinShop: A tool for interactive protein manipulation and steering

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Crivelli, Silvia; Kreylos, Oliver; Max, Nelson; Hamann, Bernd; Bethel, Wes

2004-05-25

We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShop's use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.

Differences in interregional brain connectivity in children with unilateral hearing loss.

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Jung, Matthew E; Colletta, Miranda; Coalson, Rebecca; Schlaggar, Bradley L; Lieu, Judith E C

2017-11-01

To identify functional network architecture differences in the brains of children with unilateral hearing loss (UHL) using resting-state functional-connectivity magnetic resonance imaging (rs-fcMRI). Prospective observational study. Children (7 to 17 years of age) with severe to profound hearing loss in one ear, along with their normal hearing (NH) siblings, were recruited and imaged using rs-fcMRI. Eleven children had right UHL; nine had left UHL; and 13 had normal hearing. Forty-one brain regions of interest culled from established brain networks such as the default mode (DMN); cingulo-opercular (CON); and frontoparietal networks (FPN); as well as regions for language, phonological, and visual processing, were analyzed using regionwise correlations and conjunction analysis to determine differences in functional connectivity between the UHL and normal hearing children. When compared to the NH group, children with UHL showed increased connectivity patterns between multiple networks, such as between the CON and visual processing centers. However, there were decreased, as well as aberrant connectivity patterns with the coactivation of the DMN and FPN, a relationship that usually is negatively correlated. Children with UHL demonstrate multiple functional connectivity differences between brain networks involved with executive function, cognition, and language comprehension that may represent adaptive as well as maladaptive changes. These findings suggest that possible interventions or habilitation, beyond amplification, might be able to affect some children's requirement for additional help at school. 3b. Laryngoscope, 127:2636-2645, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Stronger default mode network connectivity is associated with poorer clinical insight in youth at ultra high-risk for psychotic disorders.

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Clark, Sarah V; Mittal, Vijay A; Bernard, Jessica A; Ahmadi, Aral; King, Tricia Z; Turner, Jessica A

2018-03-01

Impaired clinical insight (CI) is a common symptom of psychotic disorders and a promising treatment target. However, to date, our understanding of how variability in CI is tied to underlying brain dysfunction in the clinical high-risk period is limited. Developing a stronger conception of this link will be a vital first step for efforts to determine if CI can serve as a useful prognostic indicator. The current study investigated whether variability in CI is related to major brain networks in adolescents and young adults at ultra high-risk (UHR) of developing psychosis. Thirty-five UHR youth were administered structured clinical interviews as well as an assessment for CI and underwent resting-state magnetic resonance imaging scans. Functional connectivity was calculated in the default mode network (DMN) and fronto-parietal network (FPN), two major networks that are dysfunctional in psychosis and are hypothesized to affect insight. Greater DMN connectivity between the posterior cingulate/precuneus and ventromedial prefrontal cortex (DMN) was related to poorer CI (R 2 =0.399). There were no significant relationships between insight and the FPN. This is the first study to relate a major brain network to clinical insight before the onset of psychosis. Findings are consistent with evidence if a hyperconnected DMN in schizophrenia and UHR, and similar to a previous study of insight and connectivity in schizophrenia. Results suggest that a strongly connected DMN may be related to poor self-awareness of subthreshold psychotic symptoms in UHR adolescents and young adults. Copyright © 2017 Elsevier B.V. All rights reserved.

Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

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Wan Li

Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

Modular protein switches derived from antibody mimetic proteins.

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Nicholes, N; Date, A; Beaujean, P; Hauk, P; Kanwar, M; Ostermeier, M

2016-02-01

Protein switches have potential applications as biosensors and selective protein therapeutics. Protein switches built by fusion of proteins with the prerequisite input and output functions are currently developed using an ad hoc process. A modular switch platform in which existing switches could be readily adapted to respond to any ligand would be advantageous. We investigated the feasibility of a modular protein switch platform based on fusions of the enzyme TEM-1 β-lactamase (BLA) with two different antibody mimetic proteins: designed ankyrin repeat proteins (DARPins) and monobodies. We created libraries of random insertions of the gene encoding BLA into genes encoding a DARPin or a monobody designed to bind maltose-binding protein (MBP). From these libraries, we used a genetic selection system for β-lactamase activity to identify genes that conferred MBP-dependent ampicillin resistance to Escherichia coli. Some of these selected genes encoded switch proteins whose enzymatic activity increased up to 14-fold in the presence of MBP. We next introduced mutations into the antibody mimetic domain of these switches that were known to cause binding to different ligands. To different degrees, introduction of the mutations resulted in switches with the desired specificity, illustrating the potential modularity of these platforms. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Protein-protein interactions and cancer: targeting the central dogma.

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Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

Targeting protein-protein interactions for parasite control.

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Christina M Taylor

2011-04-01

Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

ProteinHistorian: tools for the comparative analysis of eukaryote protein origin.

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John A Capra

Full Text Available The evolutionary history of a protein reflects the functional history of its ancestors. Recent phylogenetic studies identified distinct evolutionary signatures that characterize proteins involved in cancer, Mendelian disease, and different ontogenic stages. Despite the potential to yield insight into the cellular functions and interactions of proteins, such comparative phylogenetic analyses are rarely performed, because they require custom algorithms. We developed ProteinHistorian to make tools for performing analyses of protein origins widely available. Given a list of proteins of interest, ProteinHistorian estimates the phylogenetic age of each protein, quantifies enrichment for proteins of specific ages, and compares variation in protein age with other protein attributes. ProteinHistorian allows flexibility in the definition of protein age by including several algorithms for estimating ages from different databases of evolutionary relationships. We illustrate the use of ProteinHistorian with three example analyses. First, we demonstrate that proteins with high expression in human, compared to chimpanzee and rhesus macaque, are significantly younger than those with human-specific low expression. Next, we show that human proteins with annotated regulatory functions are significantly younger than proteins with catalytic functions. Finally, we compare protein length and age in many eukaryotic species and, as expected from previous studies, find a positive, though often weak, correlation between protein age and length. ProteinHistorian is available through a web server with an intuitive interface and as a set of command line tools; this allows biologists and bioinformaticians alike to integrate these approaches into their analysis pipelines. ProteinHistorian's modular, extensible design facilitates the integration of new datasets and algorithms. The ProteinHistorian web server, source code, and pre-computed ages for 32 eukaryotic genomes are

Mitochondrial nucleoid interacting proteins support mitochondrial protein synthesis.

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He, J; Cooper, H M; Reyes, A; Di Re, M; Sembongi, H; Litwin, T R; Gao, J; Neuman, K C; Fearnley, I M; Spinazzola, A; Walker, J E; Holt, I J

2012-07-01

Mitochondrial ribosomes and translation factors co-purify with mitochondrial nucleoids of human cells, based on affinity protein purification of tagged mitochondrial DNA binding proteins. Among the most frequently identified proteins were ATAD3 and prohibitin, which have been identified previously as nucleoid components, using a variety of methods. Both proteins are demonstrated to be required for mitochondrial protein synthesis in human cultured cells, and the major binding partner of ATAD3 is the mitochondrial ribosome. Altered ATAD3 expression also perturbs mtDNA maintenance and replication. These findings suggest an intimate association between nucleoids and the machinery of protein synthesis in mitochondria. ATAD3 and prohibitin are tightly associated with the mitochondrial membranes and so we propose that they support nucleic acid complexes at the inner membrane of the mitochondrion.

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

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Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

Evolutionary diversification of protein-protein interactions by interface add-ons.

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Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

2017-10-03

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

The interface of protein structure, protein biophysics, and molecular evolution

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Liberles, David A; Teichmann, Sarah A; Bahar, Ivet; Bastolla, Ugo; Bloom, Jesse; Bornberg-Bauer, Erich; Colwell, Lucy J; de Koning, A P Jason; Dokholyan, Nikolay V; Echave, Julian; Elofsson, Arne; Gerloff, Dietlind L; Goldstein, Richard A; Grahnen, Johan A; Holder, Mark T; Lakner, Clemens; Lartillot, Nicholas; Lovell, Simon C; Naylor, Gavin; Perica, Tina; Pollock, David D; Pupko, Tal; Regan, Lynne; Roger, Andrew; Rubinstein, Nimrod; Shakhnovich, Eugene; Sjölander, Kimmen; Sunyaev, Shamil; Teufel, Ashley I; Thorne, Jeffrey L; Thornton, Joseph W; Weinreich, Daniel M; Whelan, Simon

2012-01-01

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction. PMID:22528593

Racemic & quasi-racemic protein crystallography enabled by chemical protein synthesis.

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Kent, Stephen Bh

2018-04-04

A racemic protein mixture can be used to form centrosymmetric crystals for structure determination by X-ray diffraction. Both the unnatural d-protein and the corresponding natural l-protein are made by total chemical synthesis based on native chemical ligation-chemoselective condensation of unprotected synthetic peptide segments. Racemic protein crystallography is important for structure determination of the many natural protein molecules that are refractory to crystallization. Racemic mixtures facilitate the crystallization of recalcitrant proteins, and give diffraction-quality crystals. Quasi-racemic crystallization, using a single d-protein molecule, can facilitate the determination of the structures of a series of l-protein analog molecules. Copyright © 2018 Elsevier Ltd. All rights reserved.

General protein-protein cross-linking.

Science.gov (United States)

Alegria-Schaffer, Alice

2014-01-01

This protocol describes a general protein-to-protein cross-linking procedure using the water-soluble amine-reactive homobifunctional BS(3) (bis[sulfosuccinimidyl] suberate); however, the protocol can be easily adapted using other cross-linkers of similar properties. BS(3) is composed of two sulfo-NHS ester groups and an 11.4 Å linker. Sulfo-NHS ester groups react with primary amines in slightly alkaline conditions (pH 7.2-8.5) and yield stable amide bonds. The reaction releases N-hydroxysuccinimide (see an application of NHS esters on Labeling a protein with fluorophores using NHS ester derivitization). © 2014 Elsevier Inc. All rights reserved.

Quality control methodology for high-throughput protein-protein interaction screening.

Science.gov (United States)

Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

Directory of Open Access Journals (Sweden)

Vincent Vagenende

Full Text Available Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Our interests in protein-protein interactions

Indian Academy of Sciences (India)

protein interactions. Evolution of P-P partnerships. Evolution of P-P structures. Evolutionary dynamics of P-P interactions. Dynamics of P-P interaction network. Host-pathogen interactions. CryoEM mapping of gigantic protein assemblies.

A Library of Plasmodium vivax Recombinant Merozoite Proteins Reveals New Vaccine Candidates and Protein-Protein Interactions

Science.gov (United States)

Hostetler, Jessica B.; Sharma, Sumana; Bartholdson, S. Josefin; Wright, Gavin J.; Fairhurst, Rick M.; Rayner, Julian C.

2015-01-01

Background A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP) and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC), and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion. Methodology/Principal Findings We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further

[Detection of protein-protein interactions by FRET and BRET methods].

Science.gov (United States)

Matoulková, E; Vojtěšek, B

2014-01-01

Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

Protein degradation and protein synthesis in long-term memory formation

Directory of Open Access Journals (Sweden)

Timothy J Jarome

2014-06-01

Full Text Available Long-term memory (LTM formation requires transient changes in the activity of intracellular signaling cascades that are thought to regulate new gene transcription and de novo protein synthesis in the brain. Consistent with this, protein synthesis inhibitors impair LTM for a variety of behavioral tasks when infused into the brain around the time of training or following memory retrieval, suggesting that protein synthesis is a critical step in LTM storage in the brain. However, evidence suggests that protein degradation mediated by the ubiquitin-proteasome system may also be a critical regulator of LTM formation and stability following retrieval. This requirement for increased protein degradation has been shown in the same brain regions in which protein synthesis is required for LTM storage. Additionally, increases in the phosphorylation of proteins involved in translational control parallel increases in protein polyubiquitination and the increased demand for protein degradation is regulated by intracellular signaling molecules thought to regulate protein synthesis during LTM formation. In some cases inhibiting proteasome activity can rescue memory impairments that result from pharmacological blockade of protein synthesis, suggesting that protein degradation may control the requirement for protein synthesis during the memory storage process. Results such as these suggest that protein degradation and synthesis are both critical for LTM formation and may interact to properly consolidate and store memories in the brain. Here, we review the evidence implicating protein synthesis and degradation in LTM storage and highlight the areas of overlap between these two opposing processes. We also discuss evidence suggesting these two processes may interact to properly form and store memories. LTM storage likely requires a coordinated regulation between protein degradation and synthesis at multiple sites in the mammalian brain.

Evolutionary reprograming of protein-protein interaction specificity.

Science.gov (United States)

Akiva, Eyal; Babbitt, Patricia C

2015-10-22

Using mutation libraries and deep sequencing, Aakre et al. study the evolution of protein-protein interactions using a toxin-antitoxin model. The results indicate probable trajectories via "intermediate" proteins that are promiscuous, thus avoiding transitions via non-interactions. These results extend observations about other biological interactions and enzyme evolution, suggesting broadly general principles. Copyright © 2015 Elsevier Inc. All rights reserved.

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Protein supplementation with sports protein bars in renal patients.

Science.gov (United States)

Meade, Anthony

2007-05-01

Malnutrition prevalence in patients on dialysis is well established. The protein requirements for both hemodialysis and peritoneal dialysis have been documented elsewhere, including the Kidney Disease Outcomes Quality Initiative Clinical Practice Guidelines for Nutrition in Chronic Renal Failure. The clinical challenge is to assist patients in meeting these targets, especially in those with anorexia. Traditional supplements have included fluid, which is an issue for patients who are fluid restricted. The study objectives were to (1) investigate the range of sports protein supplements that may be suitable for patients on hemodialysis to use and (2) trial nonfluid protein supplements in patients on hemodialysis. Known manufacturers of sports protein bars and other sports supplements available in Australia were contacted for the nutrient breakdown of high-protein products, specifically potassium, protein, and phosphorus contents. As a result, selected high-protein sports bars (Protein FX, Aussie Bodies, Port Melbourne, Victoria, Australia) were used as an alternative to the more commonly used renal-specific fluid supplements (Nepro, Abbott Laboratories, Abbott Park, IL; Novasource Renal, Novartis Nutrition Corporation, Fremont, MI; and Renilon, Nutricia, Wiltshire, UK) in patients with poor nutritional status requiring supplementation. Patient satisfaction and clinical nutrition markers were investigated. The study took place at inpatient, in-center, and satellite hemodialysis settings in Adelaide, South Australia. A total of 32 patients (16 females and 16 males) with an average age of 62.9 years (range 32-86 years) undergoing hemodialysis (acute and maintenance) were included. Subjects were selected by the author as part of routine clinical nutrition care. Patients trialed sports protein bars as a protein supplement alone or in conjunction with other supplementary products. All patients were in favor of the trial, with 22 of 32 patients continuing with the protein

Mitochondrial Ferritin Deletion Exacerbates β-Amyloid-Induced Neurotoxicity in Mice

Directory of Open Access Journals (Sweden)

Peina Wang

2017-01-01

Full Text Available Mitochondrial ferritin (FtMt is a mitochondrial iron storage protein which protects mitochondria from iron-induced oxidative damage. Our previous studies indicate that FtMt attenuates β-amyloid- and 6-hydroxydopamine-induced neurotoxicity in SH-SY5Y cells. To explore the protective effects of FtMt on β-amyloid-induced memory impairment and neuronal apoptosis and the mechanisms involved, 10-month-old wild-type and Ftmt knockout mice were infused intracerebroventricularly (ICV with Aβ25–35 to establish an Alzheimer’s disease model. Knockout of Ftmt significantly exacerbated Aβ25–35-induced learning and memory impairment. The Bcl-2/Bax ratio in mouse hippocampi was decreased and the levels of cleaved caspase-3 and PARP were increased. The number of neuronal cells undergoing apoptosis in the hippocampus was also increased in Ftmt knockout mice. In addition, the levels of L-ferritin and FPN1 in the hippocampus were raised, and the expression of TfR1 was decreased. Increased MDA levels were also detected in Ftmt knockout mice treated with Aβ25–35. In conclusion, this study demonstrated that the neurological impairment induced by Aβ25–35 was exacerbated in Ftmt knockout mice and that this may relate to increased levels of oxidative stress.

Protein enriched pasta: structure and digestibility of its protein network.

Science.gov (United States)

Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

2016-02-01

Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

HIV protein sequence hotspots for crosstalk with host hub proteins.

Directory of Open Access Journals (Sweden)

Mahdi Sarmady

Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

Different protein-protein interface patterns predicted by different machine learning methods.

Science.gov (United States)

Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

2017-11-22

Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

Molecular simulations of lipid-mediated protein-protein interactions

NARCIS (Netherlands)

de Meyer, F.J.M.; Venturoli, M.; Smit, B.

2008-01-01

Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the

Detecting protein-protein interactions in living cells

DEFF Research Database (Denmark)

Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche

2009-01-01

to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C......-terminal of the NMDA receptor and PDZ2 of PSD-95 were fused to green fluorescent protein (GFP) and Renilla luciferase (Rluc) and expressed in COS7 cells. A robust and specific BRET signal was obtained by expression of the appropriate partner proteins and subsequently, the assay was used to evaluate a Tat......The PDZ domain mediated interaction between the NMDA receptor and its intracellular scaffolding protein, PSD-95, is a potential target for treatment of ischemic brain diseases. We have recently developed a number of peptide analogues with improved affinity for the PDZ domains of PSD-95 compared...

Personalizing Protein Nourishment

Science.gov (United States)

DALLAS, DAVID C.; SANCTUARY, MEGAN R.; QU, YUNYAO; KHAJAVI, SHABNAM HAGHIGHAT; VAN ZANDT, ALEXANDRIA E.; DYANDRA, MELISSA; FRESE, STEVEN A.; BARILE, DANIELA; GERMAN, J. BRUCE

2016-01-01

Proteins are not equally digestible—their proteolytic susceptibility varies by their source and processing method. Incomplete digestion increases colonic microbial protein fermentation (putrefaction), which produces toxic metabolites that can induce inflammation in vitro and have been associated with inflammation in vivo. Individual humans differ in protein digestive capacity based on phenotypes, particularly disease states. To avoid putrefaction-induced intestinal inflammation, protein sources and processing methods must be tailored to the consumer’s digestive capacity. This review explores how food processing techniques alter protein digestibility and examines how physiological conditions alter digestive capacity. Possible solutions to improving digestive function or matching low digestive capacity with more digestible protein sources are explored. Beyond the ileal digestibility measurements of protein digestibility, less invasive, quicker and cheaper techniques for monitoring the extent of protein digestion and fermentation are needed to personalize protein nourishment. Biomarkers of protein digestive capacity and efficiency can be identified with the toolsets of peptidomics, metabolomics, microbial sequencing and multiplexed protein analysis of fecal and urine samples. By monitoring individual protein digestive function, the protein component of diets can be tailored via protein source and processing selection to match individual needs to minimize colonic putrefaction and, thus, optimize gut health. PMID:26713355

A scored human protein-protein interaction network to catalyze genomic interpretation

DEFF Research Database (Denmark)

Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

2017-01-01

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

Transduction proteins of olfactory receptor cells: identification of guanine nucleotide binding proteins and protein kinase C

International Nuclear Information System (INIS)

Anholt, R.R.H.; Mumby, S.M.; Stoffers, D.A.; Girard, P.R.; Kuo, J.F.; Snyder, S.H.

1987-01-01

The authors have analyzed guanine nucleotide binding proteins (G-proteins) in the olfactory epithelium of Rana catesbeiana using subunit-specific antisera. The olfactory epithelium contained the α subunits of three G-proteins, migrating on polyacrylamide gels in SDS with apparent molecular weights of 45,000, 42,000, and 40,000, corresponding to G/sub s/, G/sub i/, and G/sub o/, respectively. A single β subunit with an apparent molecular weight of 36,000 was detected. An antiserum against the α subunit of retinal transducin failed to detect immunoreactive proteins in olfactory cilia detached from the epithelium. The olfactory cilia appeared to be enriched in immunoreactive G/sub sα/ relative to G/sub ichemical bond/ and G/sub ochemical bond/ when compared to membranes prepared from the olfactory epithelium after detachment of the cilia. Bound antibody was detected by autoradiography after incubation with [ 125 I]protein. Immunohistochemical studies using an antiserum against the β subunit of G-proteins revealed intense staining of the ciliary surface of the olfactory epithelium and of the axon bundles in the lamina propria. In contrast, an antiserum against a common sequence of the α subunits preferentially stained the cell membranes of the olfactory receptor cells and the acinar cells of Bowman's glands and the deep submucosal glands. In addition to G-proteins, they have identified protein kinase C in olfactory cilia via a protein kinase C specific antiserum and via phorbol ester binding. However, in contrast to the G-proteins, protein kinase C occurred also in cilia isolated from respiratory epithelium

Diffusion of Integral Membrane Proteins in Protein-Rich Membranes

DEFF Research Database (Denmark)

Javanainen, Matti; Martinez-Seara, Hector; Metzler, Ralf

2017-01-01

of being protein-poor, native cell membranes are extremely crowded with proteins. On the basis of extensive molecular simulations, we here demonstrate that protein crowding of the membrane at physiological levels leads to deviations from the SD relation and to the emergence of a stronger Stokes......-like dependence D ∝ 1/R. We propose that this 1/R law mainly arises due to geometrical factors: smaller proteins are able to avoid confinement effects much better than their larger counterparts. The results highlight that the lateral dynamics in the crowded setting found in native membranes is radically different......The lateral diffusion of embedded proteins along lipid membranes in protein-poor conditions has been successfully described in terms of the Saffman-Delbrück (SD) model, which predicts that the protein diffusion coefficient D is weakly dependent on its radius R as D ∝ ln(1/R). However, instead...

Competitive Protein Adsorption - Multilayer Adsorption and Surface Induced Protein Aggregation

DEFF Research Database (Denmark)

Holmberg, Maria; Hou, Xiaolin

2009-01-01

In this study, competitive adsorption of albumin and IgG (immunoglobulin G) from human serum solutions and protein mixtures onto polymer surfaces is studied by means of radioactive labeling. By using two different radiolabels (125I and 131I), albumin and IgG adsorption to polymer surfaces...... is monitored simultaneously and the influence from the presence of other human serum proteins on albumin and IgG adsorption, as well as their mutual influence during adsorption processes, is investigated. Exploring protein adsorption by combining analysis of competitive adsorption from complex solutions...... of high concentration with investigation of single protein adsorption and interdependent adsorption between two specific proteins enables us to map protein adsorption sequences during competitive protein adsorption. Our study shows that proteins can adsorb in a multilayer fashion onto the polymer surfaces...

Protein leverage effects of beef protein on energy intake in humans.

Science.gov (United States)

Martens, Eveline A; Tan, Sze-Yen; Dunlop, Mandy V; Mattes, Richard D; Westerterp-Plantenga, Margriet S

2014-06-01

The protein leverage hypothesis requires specific evidence that protein intake is regulated more strongly than energy intake. The objective was to determine ad libitum energy intake, body weight changes, appetite profile, and nitrogen balance in response to 3 diets with different protein-to-carbohydrate + fat ratios over 12 consecutive days, with beef as a source of protein. A 3-arm, 12-d randomized crossover study was performed in 30 men and 28 women [mean ± SD age: 33 ± 16 y; body mass index (in kg/m²): 24.4 ± 4.0] with the use of diets containing 5%, 15%, and 30% of energy (En%) from protein, predominantly from beef. Energy intake was significantly lower in the 30En%-protein condition (8.73 ± 1.93 MJ/d) than in the 5En%-protein (9.48 ± 1.67 MJ/d) and 15En%-protein (9.30 ± 1.62 MJ/d) conditions (P = 0.001), stemming largely from lower energy intake during meals (P = 0.001). Hunger (P = 0.001) and desire to eat (P = 0.001) ratings were higher and fullness ratings were lower (P = 0.001) in the 5En%-protein condition than in the 15En%-protein and 30En%-protein conditions. Nitrogen excretion was lower in the 5En%-protein condition (4.7 ± 1.5 g/24 h; P = 0.001) and was higher in the 30En%-protein condition (15.3 ± 8.7 g/24 h; P = 0.001) compared with the 15En%-protein condition (10.0 ± 5.2 g/24 h). Nitrogen balance was maintained in the 5En%-protein condition and was positive in the 15En%- and 30En%-protein conditions (P = 0.001). Complete protein leverage did not occur because subjects did not consume to a common protein amount at the expense of energy balance. Individuals did underconsume relative to energy requirements from high-protein diets. The lack of support for protein leverage effects on a low-protein diet may stem from the fact that protein intake was sufficient to maintain nitrogen balance over the 12-d trial. © 2014 American Society for Nutrition.

The clinical expression of hereditary protein C and protein S deficiency: : a relation to clinical thrombotic risk-factors and to levels of protein C and protein S

NARCIS (Netherlands)

Henkens, C. M. A.; van der Meer, J.; Hillege, J. L.; Bom, V. J. J.; Halie, M. R.; van der Schaaf, W.

We investigated 103 first-degree relatives of 13 unrelated protein C or protein S deficient patients to assess the role of additional thrombotic risk factors and of protein C and protein S levels in the clinical expression of hereditary protein C and protein S deficiency. Fifty-seven relatives were

PDZ Protein Regulation of G Protein-Coupled Receptor Trafficking and Signaling Pathways.

Science.gov (United States)

Dunn, Henry A; Ferguson, Stephen S G

2015-10-01

G protein-coupled receptors (GPCRs) contribute to the regulation of every aspect of human physiology and are therapeutic targets for the treatment of numerous diseases. As a consequence, understanding the myriad of mechanisms controlling GPCR signaling and trafficking is essential for the development of new pharmacological strategies for the treatment of human pathologies. Of the many GPCR-interacting proteins, postsynaptic density protein of 95 kilodaltons, disc large, zona occludens-1 (PDZ) domain-containing proteins appear most abundant and have similarly been implicated in disease mechanisms. PDZ proteins play an important role in regulating receptor and channel protein localization within synapses and tight junctions and function to scaffold intracellular signaling protein complexes. In the current study, we review the known functional interactions between PDZ domain-containing proteins and GPCRs and provide insight into the potential mechanisms of action. These PDZ domain-containing proteins include the membrane-associated guanylate-like kinases [postsynaptic density protein of 95 kilodaltons; synapse-associated protein of 97 kilodaltons; postsynaptic density protein of 93 kilodaltons; synapse-associated protein of 102 kilodaltons; discs, large homolog 5; caspase activation and recruitment domain and membrane-associated guanylate-like kinase domain-containing protein 3; membrane protein, palmitoylated 3; calcium/calmodulin-dependent serine protein kinase; membrane-associated guanylate kinase protein (MAGI)-1, MAGI-2, and MAGI-3], Na(+)/H(+) exchanger regulatory factor proteins (NHERFs) (NHERF1, NHERF2, PDZ domain-containing kidney protein 1, and PDZ domain-containing kidney protein 2), Golgi-associated PDZ proteins (Gα-binding protein interacting protein, C-terminus and CFTR-associated ligand), PDZ domain-containing guanine nucleotide exchange factors (GEFs) 1 and 2, regulator of G protein signaling (RGS)-homology-RhoGEFs (PDZ domain-containing RhoGEF and

Measuring protein breakdown rate in individual proteins in vivo

DEFF Research Database (Denmark)

Holm, Lars; Kjaer, Michael

2010-01-01

To outline different approaches of how protein breakdown can be quantified and to present a new approach to determine the fractional breakdown rate of individual slow turnover proteins in vivo.......To outline different approaches of how protein breakdown can be quantified and to present a new approach to determine the fractional breakdown rate of individual slow turnover proteins in vivo....

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

Directory of Open Access Journals (Sweden)

Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

Directory of Open Access Journals (Sweden)

Li Min

2012-03-01

Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.

The Proteins API: accessing key integrated protein and genome information.

Science.gov (United States)

Nightingale, Andrew; Antunes, Ricardo; Alpi, Emanuele; Bursteinas, Borisas; Gonzales, Leonardo; Liu, Wudong; Luo, Jie; Qi, Guoying; Turner, Edd; Martin, Maria

2017-07-03

The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to 'talk' to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multiple protonation equilibria in electrostatics of protein-protein binding.

Science.gov (United States)

Piłat, Zofia; Antosiewicz, Jan M

2008-11-27

All proteins contain groups capable of exchanging protons with their environment. We present here an approach, based on a rigorous thermodynamic cycle and the partition functions for energy levels characterizing protonation states of the associating proteins and their complex, to compute the electrostatic pH-dependent contribution to the free energy of protein-protein binding. The computed electrostatic binding free energies include the pH of the solution as the variable of state, mutual "polarization" of associating proteins reflected as changes in the distribution of their protonation states upon binding and fluctuations between available protonation states. The only fixed property of both proteins is the conformation; the structure of the monomers is kept in the same conformation as they have in the complex structure. As a reference, we use the electrostatic binding free energies obtained from the traditional Poisson-Boltzmann model, computed for a single macromolecular conformation fixed in a given protonation state, appropriate for given solution conditions. The new approach was tested for 12 protein-protein complexes. It is shown that explicit inclusion of protonation degrees of freedom might lead to a substantially different estimation of the electrostatic contribution to the binding free energy than that based on the traditional Poisson-Boltzmann model. This has important implications for the balancing of different contributions to the energetics of protein-protein binding and other related problems, for example, the choice of protein models for Brownian dynamics simulations of their association. Our procedure can be generalized to include conformational degrees of freedom by combining it with molecular dynamics simulations at constant pH. Unfortunately, in practice, a prohibitive factor is an enormous requirement for computer time and power. However, there may be some hope for solving this problem by combining existing constant pH molecular dynamics

Texturized dairy proteins.

Science.gov (United States)

Onwulata, Charles I; Phillips, John G; Tunick, Michael H; Qi, Phoebi X; Cooke, Peter H

2010-03-01

Dairy proteins are amenable to structural modifications induced by high temperature, shear, and moisture; in particular, whey proteins can change conformation to new unfolded states. The change in protein state is a basis for creating new foods. The dairy products, nonfat dried milk (NDM), whey protein concentrate (WPC), and whey protein isolate (WPI) were modified using a twin-screw extruder at melt temperatures of 50, 75, and 100 degrees C, and moistures ranging from 20 to 70 wt%. Viscoelasticity and solubility measurements showed that extrusion temperature was a more significant (P extruded dairy protein ranged from rigid (2500 N) to soft (2.7 N). Extruding at or above 75 degrees C resulted in increased peak force for WPC (138 to 2500 N) and WPI (2.7 to 147.1 N). NDM was marginally texturized; the presence of lactose interfered with its texturization. WPI products extruded at 50 degrees C were not texturized; their solubility values ranged from 71.8% to 92.6%. A wide possibility exists for creating new foods with texturized dairy proteins due to the extensive range of states achievable. Dairy proteins can be used to boost the protein content in puffed snacks made from corn meal, but unmodified, they bind water and form doughy pastes with starch. To minimize the water binding property of dairy proteins, WPI, or WPC, or NDM were modified by extrusion processing. Extrusion temperature conditions were adjusted to 50, 75, or 100 degrees C, sufficient to change the structure of the dairy proteins, but not destroy them. Extrusion modified the structures of these dairy proteins for ease of use in starchy foods to boost nutrient levels. Dairy proteins can be used to boost the protein content in puffed snacks made from corn meal, but unmodified, they bind water and form doughy pastes with starch. To minimize the water binding property of dairy proteins, whey protein isolate, whey protein concentrate, or nonfat dried milk were modified by extrusion processing. Extrusion

Protein annotation from protein interaction networks and Gene Ontology.

Science.gov (United States)

Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Dietary Protein Intake in Dutch Elderly People: A Focus on Protein Sources

Directory of Open Access Journals (Sweden)

Michael Tieland

2015-11-01

Full Text Available Introduction: Sufficient high quality dietary protein intake is required to prevent or treat sarcopenia in elderly people. Therefore, the intake of specific protein sources as well as their timing of intake are important to improve dietary protein intake in elderly people. Objectives: to assess the consumption of protein sources as well as the distribution of protein sources over the day in community-dwelling, frail and institutionalized elderly people. Methods: Habitual dietary intake was evaluated using 2- and 3-day food records collected from various studies involving 739 community-dwelling, 321 frail and 219 institutionalized elderly people. Results: Daily protein intake averaged 71 ± 18 g/day in community-dwelling, 71 ± 20 g/day in frail and 58 ± 16 g/day in institutionalized elderly people and accounted for 16% ± 3%, 16% ± 3% and 17% ± 3% of their energy intake, respectively. Dietary protein intake ranged from 10 to 12 g at breakfast, 15 to 23 g at lunch and 24 to 31 g at dinner contributing together over 80% of daily protein intake. The majority of dietary protein consumed originated from animal sources (≥60% with meat and dairy as dominant sources. Thus, 40% of the protein intake in community-dwelling, 37% in frail and 29% in institutionalized elderly originated from plant based protein sources with bread as the principle source. Plant based proteins contributed for >50% of protein intake at breakfast and between 34% and 37% at lunch, with bread as the main source. During dinner, >70% of the protein intake originated from animal protein, with meat as the dominant source. Conclusion: Daily protein intake in these older populations is mainly (>80% provided by the three main meals, with most protein consumed during dinner. More than 60% of daily protein intake consumed is of animal origin, with plant based protein sources representing nearly 40% of total protein consumed. During dinner, >70% of the protein intake originated from

Introduction to current and future protein therapeutics: a protein engineering perspective.

Science.gov (United States)

Carter, Paul J

2011-05-15

Protein therapeutics and its enabling sister discipline, protein engineering, have emerged since the early 1980s. The first protein therapeutics were recombinant versions of natural proteins. Proteins purposefully modified to increase their clinical potential soon followed with enhancements derived from protein or glycoengineering, Fc fusion or conjugation to polyethylene glycol. Antibody-based drugs subsequently arose as the largest and fastest growing class of protein therapeutics. The rationale for developing better protein therapeutics with enhanced efficacy, greater safety, reduced immunogenicity or improved delivery comes from the convergence of clinical, scientific, technological and commercial drivers that have identified unmet needs and provided strategies to address them. Future protein drugs seem likely to be more extensively engineered to improve their performance, e.g., antibodies and Fc fusion proteins with enhanced effector functions or extended half-life. Two old concepts for improving antibodies, namely antibody-drug conjugates and bispecific antibodies, have advanced to the cusp of clinical success. As for newer protein therapeutic platform technologies, several engineered protein scaffolds are in early clinical development and offer differences and some potential advantages over antibodies. Copyright © 2011 Elsevier Inc. All rights reserved.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

Directory of Open Access Journals (Sweden)

Eric A Yen

2014-05-01

Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

BLAST-based structural annotation of protein residues using Protein Data Bank.

Science.gov (United States)

Singh, Harinder; Raghava, Gajendra P S

2016-01-25

In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search. A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein. In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

Integral UBL domain proteins: a family of proteasome interacting proteins

DEFF Research Database (Denmark)

Hartmann-Petersen, Rasmus; Gordon, Colin

2004-01-01

The family of ubiquitin-like (UBL) domain proteins (UDPs) comprises a conserved group of proteins involved in a multitude of different cellular activities. However, recent studies on UBL-domain proteins indicate that these proteins appear to share a common property in their ability to interact...

Modulation of mitogen-activated protein kinase-activated protein kinase 3 by hepatitis C virus core protein

DEFF Research Database (Denmark)

Ngo, HT; Pham, Long; Kim, JW

2013-01-01

Hepatitis C virus (HCV) is highly dependent on cellular proteins for its own propagation. In order to identify the cellular factors involved in HCV propagation, we performed protein microarray assays using the HCV core protein as a probe. Of ~9,000 host proteins immobilized in a microarray...... inducers. Binding of HCV core to MAPKAPK3 was confirmed by in vitro pulldown assay and further verified by coimmunoprecipitation assay. HCV core protein interacted with MAPKAPK3 through amino acid residues 41 to 75 of core and the N-terminal half of kinase domain of MAPKAPK3. In addition, both RNA...... increased HCV IRES-mediated translation and MAPKAPK3-dependent HCV IRES activity was further increased by core protein. These data suggest that HCV core may modulate MAPKAPK3 to facilitate its own propagation....

Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

Directory of Open Access Journals (Sweden)

Ji'an Pan

Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

Protein engineering techniques gateways to synthetic protein universe

CERN Document Server

Poluri, Krishna Mohan

2017-01-01

This brief provides a broad overview of protein-engineering research, offering a glimpse of the most common experimental methods. It also presents various computational programs with applications that are widely used in directed evolution, computational and de novo protein design. Further, it sheds light on the advantages and pitfalls of existing methodologies and future perspectives of protein engineering techniques.

Topology-function conservation in protein-protein interaction networks.

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Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

2015-05-15

Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

Protein space: a natural method for realizing the nature of protein universe.

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Yu, Chenglong; Deng, Mo; Cheng, Shiu-Yuen; Yau, Shek-Chung; He, Rong L; Yau, Stephen S-T

2013-02-07

Current methods cannot tell us what the nature of the protein universe is concretely. They are based on different models of amino acid substitution and multiple sequence alignment which is an NP-hard problem and requires manual intervention. Protein structural analysis also gives a direction for mapping the protein universe. Unfortunately, now only a minuscule fraction of proteins' 3-dimensional structures are known. Furthermore, the phylogenetic tree representations are not unique for any existing tree construction methods. Here we develop a novel method to realize the nature of protein universe. We show the protein universe can be realized as a protein space in 60-dimensional Euclidean space using a distance based on a normalized distribution of amino acids. Every protein is in one-to-one correspondence with a point in protein space, where proteins with similar properties stay close together. Thus the distance between two points in protein space represents the biological distance of the corresponding two proteins. We also propose a natural graphical representation for inferring phylogenies. The representation is natural and unique based on the biological distances of proteins in protein space. This will solve the fundamental question of how proteins are distributed in the protein universe. Copyright © 2012 Elsevier Ltd. All rights reserved.

Protein intake does not increase vastus lateralis muscle protein synthesis during cycling

DEFF Research Database (Denmark)

Hulston, CJ; Wolsk, Emil; Grøndahl, Thomas Sahl

2011-01-01

PURPOSE: This study aimed to investigate the effect of protein ingestion on leg protein turnover and vastus lateralis muscle protein synthesis during bicycle exercise and recovery. METHODS: Eight healthy males participated in two experiments in which they ingested either a carbohydrate solution...... sampling, and blood flow measurements. Muscle protein synthesis was calculated from the incorporation of l-[ring-C6]phenylalanine into protein. RESULTS: Consuming protein during exercise increased leg protein synthesis and decreased net leg protein breakdown; however, protein ingestion did not increase...... protein synthesis within the highly active vastus lateralis muscle (0.029%·h(-1), ± 0.004%·h(-1), and 0.030%·h(-1), ± 0.003%·h(-1), in CHO and CHO + P, respectively; P = 0.88). In contrast, consuming protein, during exercise and recovery, increased postexercise vastus lateralis muscle protein synthesis...

Mitochondrial protein acetylation mediates nutrient sensing of mitochondrial protein synthesis and mitonuclear protein balance.

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Di Domenico, Antonella; Hofer, Annette; Tundo, Federica; Wenz, Tina

2014-11-01

Changes in nutrient supply require global metabolic reprogramming to optimize the utilization of the nutrients. Mitochondria as a central component of the cellular metabolism play a key role in this adaptive process. Since mitochondria harbor their own genome, which encodes essential enzymes, mitochondrial protein synthesis is a determinant of metabolic adaptation. While regulation of cytoplasmic protein synthesis in response to metabolic challenges has been studied in great detail, mechanisms which adapt mitochondrial translation in response to metabolic challenges remain elusive. Our results suggest that the mitochondrial acetylation status controlled by Sirt3 and its proposed opponent GCN5L1 is an important regulator of the metabolic adaptation of mitochondrial translation. Moreover, both proteins modulate regulators of cytoplasmic protein synthesis as well as the mitonuclear protein balance making Sirt3 and GCN5L1 key players in synchronizing mitochondrial and cytoplasmic translation. Our results thereby highlight regulation of mitochondrial translation as a novel component in the cellular nutrient sensing scheme and identify mitochondrial acetylation as a new regulatory principle for the metabolic competence of mitochondrial protein synthesis. © 2014 International Union of Biochemistry and Molecular Biology.

Understanding Protein-Protein Interactions Using Local Structural Features

DEFF Research Database (Denmark)

Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

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Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

Science.gov (United States)

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using modified soy protein to enhance foaming of egg white protein.

Science.gov (United States)

Wang, Guang; Troendle, Molly; Reitmeier, Cheryll A; Wang, Tong

2012-08-15

It is well known that the foaming properties of egg white protein are significantly reduced when a small amount of yolk is mixed in the white. To improve foaming properties of yolk-contaminated egg white protein, soy protein isolate (SPI) and egg proteins were modified to make basic proteins, and effects of these modified proteins on egg white foaming were evaluated in a model and an angel cake system. SPI and egg yolk proteins were modified to have an isoelectric point of 10, and sonication was used to increase protein dispersibility after the ethyl esterification reaction. However, only the addition of sonicated and modified SPI (SMSPI) showed improvement of foaming in the 5% egg protein model system with 0.4% yolk addition. SMSPI was then used in making angel food cake to examine whether the cake performance reduction due to yolk contamination of the white would be restored by such alkaline protein. Cake performance was improved when cream of tartar was used together with SMSPI. Basic soy protein can be made and used to improve egg white foaming properties and cake performance. Copyright © 2012 Society of Chemical Industry.

Yeast ribosomal proteins

International Nuclear Information System (INIS)

Otaka, E.; Kobata, K.

1978-01-01

The cytoplasmic 80s ribosomal proteins from the cells of yeast Saccharomyces cerevisiae were analyzed by SDS two-dimensional polyacrylamide gel electrophoresis. Seventyfour proteins were identified and consecutively numbered from 1 to 74. Upon oxidation of the 80s proteins with performic acid, ten proteins (no. 15, 20, 35, 40, 44, 46, 49, 51, 54 and 55) were dislocated on the gel without change of the total number of protein spots. Five proteins (no. 8, 14, 16, 36 and 74) were phosphorylated in vivo as seen in 32 P-labelling experiments. The large and small subunits separated in low magnesium medium were analyzed by the above gel electrophoresis. At least forty-five and twenty-eight proteins were assumed to be in the large and small subunits, respectively. All proteins found in the 80s ribosomes, except for no. 3, were detected in either subunit without appearance of new spots. The acidic protein no. 3 seems to be lost during subunit dissociation. (orig.) [de

Specificity of molecular interactions in transient protein-protein interaction interfaces.

Science.gov (United States)

Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

Protein-protein interactions in the regulation of WRKY transcription factors.

Science.gov (United States)

Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

Functional structural motifs for protein-ligand, protein-protein, and protein-nucleic acid interactions and their connection to supersecondary structures.

Science.gov (United States)

Kinjo, Akira R; Nakamura, Haruki

2013-01-01

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and efficiently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we define a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-specific SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

International Nuclear Information System (INIS)

Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

2011-01-01

The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations

Shotgun protein sequencing.

Energy Technology Data Exchange (ETDEWEB)

Faulon, Jean-Loup Michel; Heffelfinger, Grant S.

2009-06-01

A novel experimental and computational technique based on multiple enzymatic digestion of a protein or protein mixture that reconstructs protein sequences from sequences of overlapping peptides is described in this SAND report. This approach, analogous to shotgun sequencing of DNA, is to be used to sequence alternative spliced proteins, to identify post-translational modifications, and to sequence genetically engineered proteins.

Protein-protein interactions within late pre-40S ribosomes.

Directory of Open Access Journals (Sweden)

Melody G Campbell

2011-01-01

Full Text Available Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

Science.gov (United States)

Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

Racemic protein crystallography.

Science.gov (United States)

Yeates, Todd O; Kent, Stephen B H

2012-01-01

Although natural proteins are chiral and are all of one "handedness," their mirror image forms can be prepared by chemical synthesis. This opens up new opportunities for protein crystallography. A racemic mixture of the enantiomeric forms of a protein molecule can crystallize in ways that natural proteins cannot. Recent experimental data support a theoretical prediction that this should make racemic protein mixtures highly amenable to crystallization. Crystals obtained from racemic mixtures also offer advantages in structure determination strategies. The relevance of these potential advantages is heightened by advances in synthetic methods, which are extending the size limit for proteins that can be prepared by chemical synthesis. Recent ideas and results in the area of racemic protein crystallography are reviewed.

Modularity in protein structures: study on all-alpha proteins.

Science.gov (United States)

Khan, Taushif; Ghosh, Indira

2015-01-01

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

Emergence of modularity and disassortativity in protein-protein interaction networks.

Science.gov (United States)

Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

2010-12-01

In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

Science.gov (United States)

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

2017-07-03

Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Aquaporin Protein-Protein Interactions

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Jennifer Virginia Roche

2017-10-01

Full Text Available Aquaporins are tetrameric membrane-bound channels that facilitate transport of water and other small solutes across cell membranes. In eukaryotes, they are frequently regulated by gating or trafficking, allowing for the cell to control membrane permeability in a specific manner. Protein–protein interactions play crucial roles in both regulatory processes and also mediate alternative functions such as cell adhesion. In this review, we summarize recent knowledge about aquaporin protein–protein interactions; dividing the interactions into three types: (1 interactions between aquaporin tetramers; (2 interactions between aquaporin monomers within a tetramer (hetero-tetramerization; and (3 transient interactions with regulatory proteins. We particularly focus on the structural aspects of the interactions, discussing the small differences within a conserved overall fold that allow for aquaporins to be differentially regulated in an organism-, tissue- and trigger-specific manner. A deep knowledge about these differences is needed to fully understand aquaporin function and regulation in many physiological processes, and may enable design of compounds targeting specific aquaporins for treatment of human disease.

A method for investigating protein-protein interactions related to Salmonella typhimurium pathogenesis

Energy Technology Data Exchange (ETDEWEB)

Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2009-02-10

We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .

Exceptional heat stability of high protein content dispersions containing whey protein particles

NARCIS (Netherlands)

Saglam, D.; Venema, P.; Vries, de R.J.; Linden, van der E.

2014-01-01

Due to aggregation and/or gelation during thermal treatment, the amount of whey proteins that can be used in the formulation of high protein foods e.g. protein drinks, is limited. The aim of this study was to replace whey proteins with whey protein particles to increase the total protein content and

Directed Evolution of Proteins through In Vitro Protein Synthesis in Liposomes

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Takehiro Nishikawa

2012-01-01

Full Text Available Directed evolution of proteins is a technique used to modify protein functions through “Darwinian selection.” In vitro compartmentalization (IVC is an in vitro gene screening system for directed evolution of proteins. IVC establishes the link between genetic information (genotype and the protein translated from the information (phenotype, which is essential for all directed evolution methods, by encapsulating both in a nonliving microcompartment. Herein, we introduce a new liposome-based IVC system consisting of a liposome, the protein synthesis using recombinant elements (PURE system and a fluorescence-activated cell sorter (FACS used as a microcompartment, in vitro protein synthesis system, and high-throughput screen, respectively. Liposome-based IVC is characterized by in vitro protein synthesis from a single copy of a gene in a cell-sized unilamellar liposome and quantitative functional evaluation of the synthesized proteins. Examples of liposome-based IVC for screening proteins such as GFP and β-glucuronidase are described. We discuss the future directions for this method and its applications.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

Science.gov (United States)

Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

With Protein Foods, Variety Is Key: 10 Tips for Choosing Protein

Science.gov (United States)

... Dietary Guidelines Communicator’s Guide 10 Tips: Vary Your Protein Routine You are here Home 10 Tips: Vary ... Protein Routine Print Share 10 Tips: Vary Your Protein Routine Protein foods include both animal (meat, poultry, ...

Protein complex prediction based on k-connected subgraphs in protein interaction network

OpenAIRE

Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

2010-01-01

Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

Karakteristik Protein dan Nitrogen Non Protein Daging Ikan Cucut Lanyam (Charcharhinus limbatus (Characteristics of Protein and Non Protein Nitrogen in Lanyam Shark Muscle

Directory of Open Access Journals (Sweden)

Yuspihana Fitrial

2017-02-01

Based on protein solubility of Lanyam muscle at pH 1.5 to 12 obtained two points which is minimum solubility at pH 4.5 and pH 9. Based on the classification Osborn, Lanyam muscle contained albumin (28.64%, globulin (13:44%, prolamin (03.29%, glutelin (33.70%. Observation of non-protein nitrogen levels indicated that the washing process was very effective to reduce non-protein nitrogen levels up to 62.34% and urea levels up to 58% . Differential Scanning Calorimetry Study of Lanyam mince showed two types of protein that has a different stability to heat and after added 2.5% NaCl formed a peak which is a fusion of both these proteins

Impairment of Interrelated Iron- and Copper Homeostatic Mechanisms in Brain Contributes to the Pathogenesis of Neurodegenerative Disorders

Science.gov (United States)

Skjørringe, Tina; Møller, Lisbeth Birk; Moos, Torben

2012-01-01

Iron and copper are important co-factors for a number of enzymes in the brain, including enzymes involved in neurotransmitter synthesis and myelin formation. Both shortage and an excess of iron or copper will affect the brain. The transport of iron and copper into the brain from the circulation is strictly regulated, and concordantly protective barriers, i.e., the blood-brain barrier (BBB) and the blood-cerebrospinal fluid (CSF) barrier (BCB) have evolved to separate the brain environment from the circulation. The uptake mechanisms of the two metals interact. Both iron deficiency and overload lead to altered copper homeostasis in the brain. Similarly, changes in dietary copper affect the brain iron homeostasis. Moreover, the uptake routes of iron and copper overlap each other which affect the interplay between the concentrations of the two metals in the brain. The divalent metal transporter-1 (DMT1) is involved in the uptake of both iron and copper. Furthermore, copper is an essential co-factor in numerous proteins that are vital for iron homeostasis and affects the binding of iron-response proteins to iron-response elements in the mRNA of the transferrin receptor, DMT1, and ferroportin, all highly involved in iron transport. Iron and copper are mainly taken up at the BBB, but the BCB also plays a vital role in the homeostasis of the two metals, in terms of sequestering, uptake, and efflux of iron and copper from the brain. Inside the brain, iron and copper are taken up by neurons and glia cells that express various transporters. PMID:23055972

On the role of electrostatics on protein-protein interactions

Science.gov (United States)

Zhang, Zhe; Witham, Shawn; Alexov, Emil

2011-01-01

The role of electrostatics on protein-protein interactions and binding is reviewed in this article. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and basic electrostatic effects occurring upon the formation of the complex are discussed. The role of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated and indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartment. At the end, the similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity. PMID:21572182

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

Directory of Open Access Journals (Sweden)

Greenblatt Jack

2006-07-01

Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

Consumption of Milk Protein or Whey Protein Results in a Similar Increase in Muscle Protein Synthesis in Middle Aged Men.

Science.gov (United States)

Mitchell, Cameron J; McGregor, Robin A; D'Souza, Randall F; Thorstensen, Eric B; Markworth, James F; Fanning, Aaron C; Poppitt, Sally D; Cameron-Smith, David

2015-10-21

The differential ability of various milk protein fractions to stimulate muscle protein synthesis (MPS) has been previously described, with whey protein generally considered to be superior to other fractions. However, the relative ability of a whole milk protein to stimulate MPS has not been compared to whey. Sixteen healthy middle-aged males ingested either 20 g of milk protein (n = 8) or whey protein (n = 8) while undergoing a primed constant infusion of ring (13)C₆ phenylalanine. Muscle biopsies were obtained 120 min prior to consumption of the protein and 90 and 210 min afterwards. Resting myofibrillar fractional synthetic rates (FSR) were 0.019% ± 0.009% and 0.021% ± 0.018% h(-1) in the milk and whey groups respectively. For the first 90 min after protein ingestion the FSR increased (p whey groups respectively with no difference between groups (p = 0.810). FSR returned to baseline in both groups between 90 and 210 min after protein ingestion. Despite evidence of increased rate of digestion and leucine availability following the ingestion of whey protein, there was similar activation of MPS in middle-aged men with either 20 g of milk protein or whey protein.

Decreased Fronto-Parietal and Increased Default Mode Network Activation is Associated with Subtle Cognitive Deficits in Elderly Controls

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Davide Zanchi

2017-12-01

Full Text Available Background: Cognitive functions progressively deteriorate during aging and neurodegenerative diseases. The present study aims at investigating differences in working memory performance as well as functional brain changes during the earliest stages of cognitive decline in health elderly individuals. Methods: 62 elderly individuals (41 females, including 41 controls (35 females and 21 middle cognitive impairment subjects (6 females, underwent neuropsychological assessment at baseline and an fMRI examination in a N-back paradigm contrasting 2-back vs. 0-back condition. Upon a 18 months follow-up, we identified stable controls (sCON with preserved cognition and deteriorating controls (dCON with -1SD decrease of performances in at least two neuropsychological tests. Data analyses included accuracy and reaction time (RT for the 2-back condition and general linear model (GLM for the fMRI sequence. Results: At the behavioral level, sCON and dCON performed better than MCI in terms of accuracy and reaction time. At the brain level, functional differences in regions of the fronto-parietal network (FPN and of the Default Mode Network (DFM were observed. Significantly lower neural activations in the bilateral inferior and middle frontal gyri were found in MCI versus both dCON / sCON and for dCON versus sCON. Significantly increased activations in the anterior cingulate cortex and posterior cingulate cortex and bilateral insula were found in MCI versus both dCON / sCON and in dCON versus sCON. Conclusion: The present study suggests that brain functional changes in FPN and DMN anticipate differences in cognitive performance in healthy elderly individuals with subsequent subtle cognitive decline.

Constraining Phosphorus Chemistry in Carbon- and Oxygen-Rich Circumstellar Envelopes: Observations of PN, HCP, and CP

Science.gov (United States)

Milam, S. N.; Halfen, D. T.; Tenenbaum, E. D.; Apponi, A. J.; Woolf, N. J.; Ziurys, L. M.

2008-09-01

Millimeter-wave observations of PN, CP, and HCP have been carried out toward circumstellar envelopes of evolved stars using the Arizona Radio Observatory (ARO). HCP and PN have been identified in the carbon-rich source CRL 2688 via observations at 1 mm using the Submillimeter Telescope (SMT) and 2-3 mm with the Kitt Peak 12 m. An identical set of measurements were carried out toward IRC +10216, as well as observations of CP at 1 mm. PN was also observed toward VY Canis Majoris (VY CMa), an oxygen-rich supergiant star. The PN and HCP line profiles in CRL 2688 and IRC +10216 are roughly flat topped, indicating unresolved, optically thin emission; CP, in contrast, has a distinct "U" shape in IRC +10216. Modeling of the line profiles suggests abundances, relative to H2, of f(PN) ~ (3-5) × 10-9 and f(HCP) ~ 2 × 10-7 in CRL 2688, about an order of magnitude higher than in IRC +10216. In VY CMa, f(PN) is ~4 × 10-8. The data in CRL 2688 and IRC +10216 are consistent with LTE formation of HCP and PN in the inner envelope, as predicted by theoretical calculations, with CP a photodissociation product at larger radii. The observed abundance of PN in VY CMa is a factor of 100 higher than LTE predictions. In IRC +10216, the chemistry of HCP/CP mimics that of HCN/CN and suggests an N2 abundance of f ~ 1 × 10-7. The chemistry of phosphorus appears active in both carbon- and oxygen-rich envelopes of evolved stars.

A Dual-Mode Large-Arrayed CMOS ISFET Sensor for Accurate and High-Throughput pH Sensing in Biomedical Diagnosis.

Science.gov (United States)

Huang, Xiwei; Yu, Hao; Liu, Xu; Jiang, Yu; Yan, Mei; Wu, Dongping

2015-09-01

The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.

Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes.

Science.gov (United States)

Nillegoda, Nadinath B; Stank, Antonia; Malinverni, Duccio; Alberts, Niels; Szlachcic, Anna; Barducci, Alessandro; De Los Rios, Paolo; Wade, Rebecca C; Bukau, Bernd

2017-05-15

Hsp70 participates in a broad spectrum of protein folding processes extending from nascent chain folding to protein disaggregation. This versatility in function is achieved through a diverse family of J-protein cochaperones that select substrates for Hsp70. Substrate selection is further tuned by transient complexation between different classes of J-proteins, which expands the range of protein aggregates targeted by metazoan Hsp70 for disaggregation. We assessed the prevalence and evolutionary conservation of J-protein complexation and cooperation in disaggregation. We find the emergence of a eukaryote-specific signature for interclass complexation of canonical J-proteins. Consistently, complexes exist in yeast and human cells, but not in bacteria, and correlate with cooperative action in disaggregation in vitro. Signature alterations exclude some J-proteins from networking, which ensures correct J-protein pairing, functional network integrity and J-protein specialization. This fundamental change in J-protein biology during the prokaryote-to-eukaryote transition allows for increased fine-tuning and broadening of Hsp70 function in eukaryotes.

Globular and disordered-the non-identical twins in protein-protein interactions

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt

2015-01-01

as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

Neuromuscular electrical stimulation prior to presleep protein feeding stimulates the use of protein-derived amino acids for overnight muscle protein synthesis.

Science.gov (United States)

Dirks, Marlou L; Groen, Bart B L; Franssen, Rinske; van Kranenburg, Janneau; van Loon, Luc J C

2017-01-01

Short periods of muscle disuse result in substantial skeletal muscle atrophy. Recently, we showed that both neuromuscular electrical stimulation (NMES) as well as presleep dietary protein ingestion represent effective strategies to stimulate muscle protein synthesis rates. In this study, we test our hypothesis that NMES can augment the use of presleep protein-derived amino acids for overnight muscle protein synthesis in older men. Twenty healthy, older [69 ± 1 (SE) yr] men were subjected to 24 h of bed rest, starting at 8:00 AM. In the evening, volunteers were subjected to 70-min 1-legged NMES, while the other leg served as nonstimulated control (CON). Immediately following NMES, 40 g of intrinsically l-[1- 13 C]-phenylalanine labeled protein was ingested prior to sleep. Blood samples were taken throughout the night, and muscle biopsies were obtained from both legs in the evening and the following morning (8 h after protein ingestion) to assess dietary protein-derived l-[1- 13 C]-phenylalanine enrichments in myofibrillar protein. Plasma phenylalanine concentrations and plasma l-[1- 13 C]-phenylalanine enrichments increased significantly following protein ingestion and remained elevated for up to 6 h after protein ingestion (P protein-bound l-[1- 13 C]-phenylalanine enrichments (MPE) increased to a greater extent in the stimulated compared with the control leg (0.0344 ± 0.0019 vs. 0.0297 ± 0.0016 MPE, respectively; P protein-derived amino acids in the NMES compared with CON leg. In conclusion, application of NMES prior to presleep protein feeding stimulates the use of dietary protein-derived amino acids for overnight muscle protein synthesis in older men. Neuromuscular electrical stimulation (NMES) as well as presleep dietary protein ingestion represent effective strategies to stimulate muscle protein synthesis rates. Here we demonstrate that in older men after a day of bed rest, the application of NMES prior to presleep protein feeding stimulates the use of

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

Science.gov (United States)

Agrawal, Neeraj J; Helk, Bernhard; Trout, Bernhardt L

2014-01-21

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

ProDis-ContSHC: Learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin; Wang, Quanquan; Li, Yongping

2012-01-01

Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity

Current strategies for protein production and purification enabling membrane protein structural biology.

Science.gov (United States)

Pandey, Aditya; Shin, Kyungsoo; Patterson, Robin E; Liu, Xiang-Qin; Rainey, Jan K

2016-12-01

Membrane proteins are still heavily under-represented in the protein data bank (PDB), owing to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles, owing to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and (or) amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through the introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10-15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM).

Fragment-based quantum mechanical calculation of protein-protein binding affinities.

Science.gov (United States)

Wang, Yaqian; Liu, Jinfeng; Li, Jinjin; He, Xiao

2018-04-29

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

PROTEIN FRACTIONS AND IN VITRO FERMENTATION OF PROTEIN FEEDS FOR RUMINANTS

Directory of Open Access Journals (Sweden)

Angel L. Guevara-Mesa

2011-05-01

Full Text Available The objective of this study was to evaluate 20 protein feeds grouped in forages, vegetal by- products and animal by-products used for ruminant diets. Protein fractions (PF: A, non-protein nitrogen (NPN; B1, buffer-soluble protein; B2, buffer-insoluble, NDF-soluble protein; B3, NDF-insoluble, ADF-soluble protein; and C, ADF-insoluble protein, were determined for each ingredient.  Protein composition was correlated with total gas production in vitro (GP, gas production rate (S, lag time (L, DM disappearance (DMDIV and residual protein (RPIV. The completely randomised designed was analysed using mixed proc. and Tukey contrasts. Forages contained 18.29, 7.86, 66.00, 2.96, 4.89% of fractions A, B1, B2, B3 and C, respectively. Vegetable by-products contained 22.55, 4.55, 59.51, 8.84, 4.55% of each fraction, in the same order. Animal by-products contained 19.13, 4.52, 70.24, 3.74, 2.37% of each fraction, in the same order. Vetch, wheat bran and poultry litter had the greatest Vmax in each group. Vmax was correlated (P≤0.01 with total protein (r = -0.45, ADF (r = 0.27 and DMDIV (r = 0.61. In conclusion, there were differences in protein composition and kinetics of in vitro gas production among ingredients.

Selection of peptides interfering with protein-protein interaction.

Science.gov (United States)

Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

2009-01-01

Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

Phthalic Acid Chemical Probes Synthesized for Protein-Protein Interaction Analysis

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Chin-Jen Wu

2013-06-01

Full Text Available Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP. According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES was deposited on silicon dioxides (SiO2 particles and phthalate chemical probes were manufactured from phthalic acid and APTES–SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

Protein-protein docking using region-based 3D Zernike descriptors.

Science.gov (United States)

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

Science.gov (United States)

Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new

Escherichia coli cell-free protein synthesis and isotope labeling of mammalian proteins.

Science.gov (United States)

Terada, Takaho; Yokoyama, Shigeyuki

2015-01-01

This chapter describes the cell-free protein synthesis method, using an Escherichia coli cell extract. This is a cost-effective method for milligram-scale protein production and is particularly useful for the production of mammalian proteins, protein complexes, and membrane proteins that are difficult to synthesize by recombinant expression methods, using E. coli and eukaryotic cells. By adjusting the conditions of the cell-free method, zinc-binding proteins, disulfide-bonded proteins, ligand-bound proteins, etc., may also be produced. Stable isotope labeling of proteins can be accomplished by the cell-free method, simply by using stable isotope-labeled amino acid(s) in the cell-free reaction. Moreover, the cell-free protein synthesis method facilitates the avoidance of stable isotope scrambling and dilution over the recombinant expression methods and is therefore advantageous for amino acid-selective stable isotope labeling. Site-specific stable isotope labeling is also possible with a tRNA molecule specific to the UAG codon. By the cell-free protein synthesis method, coupled transcription-translation is performed from a plasmid vector or a PCR-amplified DNA fragment encoding the protein. A milligram quantity of protein can be produced with a milliliter-scale reaction solution in the dialysis mode. More than a thousand solution structures have been determined by NMR spectroscopy for uniformly labeled samples of human and mouse functional domain proteins, produced by the cell-free method. Here, we describe the practical aspects of mammalian protein production by the cell-free method for NMR spectroscopy. © 2015 Elsevier Inc. All rights reserved.

A selection that reports on protein-protein interactions within a thermophilic bacterium.

Science.gov (United States)

Nguyen, Peter Q; Silberg, Jonathan J

2010-07-01

Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions.

InSilico Proteomics System: Integration and Application of Protein and Protein-Protein Interaction Data using Microsoft .NET

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Straßer Wolfgang

2006-12-01

Full Text Available In the last decades, biological databases became the major knowledge resource for researchers in the field of molecular biology. The distribution of information among these databases is one of the major problems. An overview about the subject area of data access and representation of protein and protein-protein interaction data within public biological databases is described. For a comprehensive and consistent way of searching and analysing integrated protein and protein-protein interaction data, the InSilico Proteomics (ISP project has been initiated. Its three main objectives are (1 to provide an integrated knowledge pool for data investigation and global network analysis functions for a better understanding of a cell’s interactome, (2 employment of public data for plausibility analysis and validation of in-house experimental data and (3 testing the applicability of Microsoft’s .NET architecture for bioinformatics applications. Data integrated into the ISP database can be queried through the Web portal PRIMOS (PRotein Interaction and MOlecule Search which is freely available at http://biomis.fh-hagenberg.at/isp/primos.

Mechanisms of protein misfolding: Novel therapeutic approaches to protein-misfolding diseases

DEFF Research Database (Denmark)

Salahuddin, Parveen; Siddiqi, Mohammad Khursheed; Khan, Sanaullah

2016-01-01

’s disease (PD), Alzheimer’s disease (AD), Prion disease and Amylo lateral Sclerosis (ALS). Furthermore, tau protein shows intrinsically disorder conformation; therefore its interaction with microtubule is impaired and this protein undergoes aggregation. This is also underlying cause of Alzheimers and other......In protein misfolding, protein molecule acquires wrong tertiary structure, thereby induces protein misfolding diseases. Protein misfolding can occur through various mechanisms. For instance, changes in environmental conditions, oxidative stress, dominant negative mutations, error in post......-translational modifications, increase in degradation rate and trafficking error. All of these factors cause protein misfolding thereby leading to diseases conditions. Both in vitro and in vivo observations suggest that partially unfolded or misfolded intermediates are particularly prone to aggregation. These partially...

Detecting protein complexes based on a combination of topological and biological properties in protein-protein interaction network

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Pooja Sharma

2018-06-01

Full Text Available Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexes from raw protein protein interactions (PPIs is an important area of research. Earlier work has been limited mostly to yeast. Such protein complex identification methods, when applied to large human PPIs often give poor performance. We introduce a novel method called CSC to detect protein complexes. The method is evaluated in terms of positive predictive value, sensitivity and accuracy using the datasets of the model organism, yeast and humans. CSC outperforms several other competing algorithms for both organisms. Further, we present a framework to establish the usefulness of CSC in analyzing the influence of a given disease gene in a complex topologically as well as biologically considering eight major association factors. Keywords: Protein complex, Connectivity, Semantic similarity, Contribution

Protein complex prediction based on k-connected subgraphs in protein interaction network

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Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

Tau protein

DEFF Research Database (Denmark)

Frederiksen, Jette Lautrup Battistini; Kristensen, Kim; Bahl, Jmc

2011-01-01

Background: Tau protein has been proposed as biomarker of axonal damage leading to irreversible neurological impairment in MS. CSF concentrations may be useful when determining risk of progression from ON to MS. Objective: To investigate the association between tau protein concentration and 14......-3-3 protein in the cerebrospinal fluid (CSF) of patients with monosymptomatic optic neuritis (ON) versus patients with monosymptomatic onset who progressed to multiple sclerosis (MS). To evaluate results against data found in a complete literature review. Methods: A total of 66 patients with MS and/or ON from...... the Department of Neurology of Glostrup Hospital, University of Copenhagen, Denmark, were included. CSF samples were analysed for tau protein and 14-3-3 protein, and clinical and paraclinical information was obtained from medical records. Results: The study shows a significantly increased concentration of tau...

Globular and disordered – the non-identical twins in protein-protein interactions

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Kaare eTeilum

2015-07-01

Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.

Towards a map of the Populus biomass protein-protein interaction network

Energy Technology Data Exchange (ETDEWEB)

Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2015-07-31

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in

Imaging protein-protein interactions in living cells

NARCIS (Netherlands)

Hink, M.A.; Bisseling, T.; Visser, A.J.W.G.

2002-01-01

The complex organization of plant cells makes it likely that the molecular behaviour of proteins in the test tube and the cell is different. For this reason, it is essential though a challenge to study proteins in their natural environment. Several innovative microspectroscopic approaches provide

Protein - Which is Best?

Science.gov (United States)

Hoffman, Jay R; Falvo, Michael J

2004-09-01

Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids), whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function) are also reviewed. Key PointsHigher protein needs are seen in athletic populations.Animal proteins is an important source of protein, however potential health concerns do exist from a diet of protein

Personnel Radiation Exposure Associated With X-Rays Emanating from U.S. Coast Guard LORAN High Voltage Vacuum Tube Transmitter Units

Science.gov (United States)

2011-07-01

until LORAN was shut down at LORSTA Narrow Cape, LORSTA Shoal Cove, LORSTA Tok , and LORSTA Williams Lake. Fig. 5: 2nd IPA tube As shown in Table 1...use. Fig. 11: Vacuum switches at LORSTA Tok Antenna Coupler Room Fig. 12: Cooling Rack in AN/FPN-44/B Antenna Coupler Plenum Space...0.000 N/A 0.000 N/A Gesashi 02-10 N/A 8 2 0.000 1.722 0.000 3.444 Tok N/A 07-08 7 4 0.000 0.529 0.000 2.116 Attu N/A 07-08 10 4 0.001 0.259 0.010 1.036

Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

Science.gov (United States)

Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

2015-05-15

Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

Athoropometric measurements and plasma proteins in protein ...

African Journals Online (AJOL)

Athoropometric measurements and plasma proteins in protein energy malnutrition. MH Etukudo, EO Agbedana, OO Akinyinka, BOA Osifo. Abstract. No Abstract. Global Journal of Medical Sciences Vol. 5(1) 2006: 7-11. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD ...

Identification of membrane proteins by tandem mass spectrometry of protein ions

Science.gov (United States)

Carroll, Joe; Altman, Matthew C.; Fearnley, Ian M.; Walker, John E.

2007-01-01

The most common way of identifying proteins in proteomic analyses is to use short segments of sequence (“tags”) determined by mass spectrometric analysis of proteolytic fragments. The approach is effective with globular proteins and with membrane proteins with significant polar segments between membrane-spanning α-helices, but it is ineffective with other hydrophobic proteins where protease cleavage sites are either infrequent or absent. By developing methods to purify hydrophobic proteins in organic solvents and by fragmenting ions of these proteins by collision induced dissociation with argon, we have shown that partial sequences of many membrane proteins can be deduced easily by manual inspection. The spectra from small proteolipids (1–4 transmembrane α-helices) are dominated usually by fragment ions arising from internal amide cleavages, from which internal sequences can be obtained, whereas the spectra from larger membrane proteins (5–18 transmembrane α-helices) often contain fragment ions from N- and/or C-terminal parts yielding sequences in those regions. With these techniques, we have, for example, identified an abundant protein of unknown function from inner membranes of mitochondria that to our knowledge has escaped detection in proteomic studies, and we have produced sequences from 10 of 13 proteins encoded in mitochondrial DNA. They include the ND6 subunit of complex I, the last of its 45 subunits to be analyzed. The procedures have the potential to be developed further, for example by using newly introduced methods for protein ion dissociation to induce fragmentation of internal regions of large membrane proteins, which may remain partially folded in the gas phase. PMID:17720804

Architectures and Functional Coverage of Protein-Protein Interfaces

Science.gov (United States)

Tuncbag, Nurcan; Gursoy, Attila; Guney, Emre; Nussinov, Ruth; Keskin, Ozlem

2008-01-01

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing unique interface architecture. This dataset of protein-protein interfaces is analyzed and compared with older datasets. We observe that the number of both biological and crystal interfaces increase significantly compared to the number of PDB entries. Further, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, those are the ones which are also preferred in single chains. PMID:18620705

Inferring high-confidence human protein-protein interactions

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Yu Xueping

2012-05-01

Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

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Srinivasan Narayanaswamy

2010-06-01

Full Text Available Abstract Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

Protein degradation and protection against misfolded or damaged proteins

Science.gov (United States)

Goldberg, Alfred L.

2003-12-01

The ultimate mechanism that cells use to ensure the quality of intracellular proteins is the selective destruction of misfolded or damaged polypeptides. In eukaryotic cells, the large ATP-dependent proteolytic machine, the 26S proteasome, prevents the accumulation of non-functional, potentially toxic proteins. This process is of particular importance in protecting cells against harsh conditions (for example, heat shock or oxidative stress) and in a variety of diseases (for example, cystic fibrosis and the major neurodegenerative diseases). A full understanding of the pathogenesis of the protein-folding diseases will require greater knowledge of how misfolded proteins are recognized and selectively degraded.

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

Science.gov (United States)

Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

MicroProteins

DEFF Research Database (Denmark)

Eguen, Teinai Ebimienere; Straub, Daniel; Graeff, Moritz

2015-01-01

MicroProteins (miPs) are short, usually single-domain proteins that, in analogy to miRNAs, heterodimerize with their targets and exert a dominant-negative effect. Recent bioinformatic attempts to identify miPs have resulted in a list of potential miPs, many of which lack the defining...... characteristics of a miP. In this opinion article, we clearly state the characteristics of a miP as evidenced by known proteins that fit the definition; we explain why modulatory proteins misrepresented as miPs do not qualify as true miPs. We also discuss the evolutionary history of miPs, and how the miP concept...

Non-interacting surface solvation and dynamics in protein-protein interactions

NARCIS (Netherlands)

Visscher, Koen M.; Kastritis, Panagiotis L.|info:eu-repo/dai/nl/315886668; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238

2015-01-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo

Occurrence of protein disulfide bonds in different domains of life: a comparison of proteins from the Protein Data Bank.

Science.gov (United States)

Bošnjak, I; Bojović, V; Šegvić-Bubić, T; Bielen, A

2014-03-01

Disulfide bonds (SS bonds) are important post-translational modifications of proteins. They stabilize a three-dimensional (3D) structure (structural SS bonds) and also have the catalytic or regulatory functions (redox-active SS bonds). Although SS bonds are present in all groups of organisms, no comparative analyses of their frequency in proteins from different domains of life have been made to date. Using the Protein Data Bank, the number and subcellular locations of SS bonds in Archaea, Bacteria and Eukarya have been compared. Approximately three times higher frequency of proteins with SS bonds in eukaryotic secretory organelles (e.g. endoplasmic reticulum) than in bacterial periplasmic/secretory pathways was calculated. Protein length also affects the SS bond frequency: the average number of SS bonds is positively correlated with the length for longer proteins (>200 amino acids), while for the shorter and less stable proteins (proteins (250-350 amino acids) indicated a high number of SS bonds only in Archaea which could be explained by the need for additional protein stabilization in hyperthermophiles. The results emphasize higher capacity for the SS bond formation and isomerization in Eukarya when compared with Archaea and Bacteria.

Kinetic parameters of protein metabolism in rats during protein-free feeding

International Nuclear Information System (INIS)

Krawielitzki, K.; Schadereit, R.; Wuensche, J.

1987-01-01

16 male rats of 100 g live weight were given 50 mg of a mixture containing 15 N-labelled amino acids as a single dose within a protein-free feeding period. Following this the 15 N excretion in feces and urine as well as the development of the 15 N excess in different organs and tissues were estimated over 3 days by slaughtering the animals within given 7 time intervals. Using a 3 pool model and the computer program for the interpretation of 15 N tracer experiments by Toewe et al. (1984), kinetic parameters such as the rate of protein synthesis, protein breakdown and the rate of reutilization were calculated. Despite a negative N balance (- 41.8 mg N/d) under protein-free conditions the protein metabolism of the rat shows high dynamics characterized by a high flux rate (225 mg N/d) and a high rate of body protein synthesis (181 mg/d). The reutilization was 85 %. Depending on time the 15 N excess in the tested organs and tissues showed significant differences and seems to demonstrate that under these conditions protein synthesis mainly takes place in the most important organs (e.g. intestinal tract, liver). Under protein-free feeding conditions protein synthesis and protein breakdown of the whole body seems to be slightly increased in comparison to N balanced feeding conditions. (author)

The role of electrostatics in protein-protein interactions of a monoclonal antibody.

Science.gov (United States)

Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R

2014-07-07

Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.

Scoring functions for protein-protein interactions.

Science.gov (United States)

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Pierced Lasso Proteins

Science.gov (United States)

Jennings, Patricia

Entanglement and knots are naturally occurring, where, in the microscopic world, knots in DNA and homopolymers are well characterized. The most complex knots are observed in proteins which are harder to investigate, as proteins are heteropolymers composed of a combination of 20 different amino acids with different individual biophysical properties. As new-knotted topologies and new proteins containing knots continue to be discovered and characterized, the investigation of knots in proteins has gained intense interest. Thus far, the principle focus has been on the evolutionary origin of tying a knot, with questions of how a protein chain `self-ties' into a knot, what the mechanism(s) are that contribute to threading, and the biological relevance and functional implication of a knotted topology in vivo gaining the most insight. Efforts to study the fully untied and unfolded chain indicate that the knot is highly stable, remaining intact in the unfolded state orders of magnitude longer than first anticipated. The persistence of ``stable'' knots in the unfolded state, together with the challenge of defining an unfolded and untied chain from an unfolded and knotted chain, complicates the study of fully untied protein in vitro. Our discovery of a new class of knotted proteins, the Pierced Lassos (PL) loop topology, simplifies the knotting approach. While PLs are not easily recognizable by the naked eye, they have now been identified in many proteins in the PDB through the use of computation tools. PL topologies are diverse proteins found in all kingdoms of life, performing a large variety of biological responses such as cell signaling, immune responses, transporters and inhibitors (http://lassoprot.cent.uw.edu.pl/). Many of these PL topologies are secreted proteins, extracellular proteins, as well as, redox sensors, enzymes and metal and co-factor binding proteins; all of which provide a favorable environment for the formation of the disulphide bridge. In the PL

The E5 Proteins

OpenAIRE

DiMaio, Daniel; Petti, Lisa

2013-01-01

The E5 proteins are short transmembrane proteins encoded by many animal and human papillomaviruses. These proteins display transforming activity in cultured cells and animals, and they presumably also play a role in the productive virus life cycle. The E5 proteins are thought to act by modulating the activity of cellular proteins. Here, we describe the biological activities of the best-studied E5 proteins and discuss the evidence implicating specific protein targets and pathways in mediating ...

Analysis of the protein-protein interactions between the human acidic ribosomal P-proteins: evaluation by the two hybrid system

DEFF Research Database (Denmark)

Tchórzewski, M; Boldyreff, B; Issinger, O

2000-01-01

The surface acidic ribosomal proteins (P-proteins), together with ribosomal core protein P0 form a multimeric lateral protuberance on the 60 S ribosomal subunit. This structure, also called stalk, is important for efficient translational activity of the ribosome. In order to shed more light...... forms the 60 S ribosomal stalk: P0-(P1/P2)(2). Additionally, mutual interactions among human and yeast P-proteins were analyzed. Heterodimer formation could be observed between human P2 and yeast P1 proteins....

Protein-protein interface detection using the energy centrality relationship (ECR characteristic of proteins.

Directory of Open Access Journals (Sweden)

Sanjana Sudarshan

Full Text Available Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs, from Functionally uncorrelated Contacts (FunCs, is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations.

Variation in Protein and Calorie Consumption Following Protein Malnutrition in Rattus norvegicus

Science.gov (United States)

Jones, Donna C.; German, Rebecca Z.

2013-01-01

Simple Summary Catch-up growth following malnutrition is likely influenced by available protein and calories. We measured calorie and protein consumption following the removal of protein malnutrition after 40, 60 and 90 days, in laboratory rats. Following the transition in diet, animals self-selected fewer calories, implying elevated protein is sufficient to fuel catch-up growth, eventually resulting in body weights and bone lengths greater or equal to those of control animals. Rats rehabilitated at younger ages, had more drastic alterations in consumption. Variable responses in different ages and sex highlight the plasticity of growth and how nutrition affects body form. This work furthers our understanding of how humans and livestock can recover from protein-restriction malnutrition, which seems to employ different biological responses. Abstract Catch-up growth rates, following protein malnutrition, vary with timing and duration of insult, despite unlimited access to calories. Understanding changing patterns of post-insult consumption, relative rehabilitation timing, can provide insight into the mechanisms driving those differences. We hypothesize that higher catch-up growth rates will be correlated with increased protein consumption, while calorie consumption could remain stable. As catch-up growth rates decrease with age/malnutrition duration, we predict a dose effect in protein consumption with rehabilitation timing. We measured total and protein consumption, body mass, and long bone length, following an increase of dietary protein at 40, 60 and 90 days, with two control groups (chronic reduced protein or standard protein) for 150+ days. Immediately following rehabilitation, rats’ food consumption decreased significantly, implying that elevated protein intake is sufficient to fuel catch-up growth rates that eventually result in body weights and long bone lengths greater or equal to final measures of chronically fed standard (CT) animals. The duration of

Protein domain recurrence and order can enhance prediction of protein functions

KAUST Repository

Abdel Messih, Mario A.

2012-09-07

Motivation: Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been developed to infer the protein functions based on either the sequences or domains of proteins. The existing methods, however, ignore the recurrence and the order of the protein domains in this function inference. Results: We developed two new methods to infer protein functions based on protein domain recurrence and domain order. Our first method, DRDO, calculates the posterior probability of the Gene Ontology terms based on domain recurrence and domain order information, whereas our second method, DRDO-NB, relies on the nave Bayes methodology using the same domain architecture information. Our large-scale benchmark comparisons show strong improvements in the accuracy of the protein function inference achieved by our new methods, demonstrating that domain recurrence and order can provide important information for inference of protein functions. The Author(s) 2012. Published by Oxford University Press.

Impact of protein uptake and degradation on recombinant protein secretion in yeast

DEFF Research Database (Denmark)

Tyo, Keith E. J.; Liu, Zihe; Magnusson, Ylva

2014-01-01

Protein titers, a key bioprocessing metric, depend both on the synthesis of protein and the degradation of protein. Secreted recombinant protein production in Saccharomyces cerevisiae is an attractive platform as minimal media can be used for cultivation, thus reducing fermentation costs...... and transcriptomics, we identify metabolic and regulatory markers that are consistent with uptake of whole proteins by endocytosis, followed by intracellular degradation and catabolism of substituent amino acids. Uptake and degradation of recombinant protein products may be common in S. cerevisiae protein secretion...... and simplifying downstream purification, compared to other systems that require complex media. As such, engineering S. cerevisiae to improve titers has been then the subject of significant attention, but the majority of previous efforts have been focused on improving protein synthesis. Here, we characterize...

Polymer Directed Protein Assemblies

Directory of Open Access Journals (Sweden)

Patrick van Rijn

2013-05-01

Full Text Available Protein aggregation and protein self-assembly is an important occurrence in natural systems, and is in some form or other dictated by biopolymers. Very obvious influences of biopolymers on protein assemblies are, e.g., virus particles. Viruses are a multi-protein assembly of which the morphology is dictated by poly-nucleotides namely RNA or DNA. This “biopolymer” directs the proteins and imposes limitations on the structure like the length or diameter of the particle. Not only do these bionanoparticles use polymer-directed self-assembly, also processes like amyloid formation are in a way a result of directed protein assembly by partial unfolded/misfolded biopolymers namely, polypeptides. The combination of proteins and synthetic polymers, inspired by the natural processes, are therefore regarded as a highly promising area of research. Directed protein assembly is versatile with respect to the possible interactions which brings together the protein and polymer, e.g., electrostatic, v.d. Waals forces or covalent conjugation, and possible combinations are numerous due to the large amounts of different polymers and proteins available. The protein-polymer interacting behavior and overall morphology is envisioned to aid in clarifying protein-protein interactions and are thought to entail some interesting new functions and properties which will ultimately lead to novel bio-hybrid materials.

Nutritional geometry: gorillas prioritize non-protein energy while consuming surplus protein.

Science.gov (United States)

Rothman, Jessica M; Raubenheimer, David; Chapman, Colin A

2011-12-23

It is widely assumed that terrestrial food webs are built on a nitrogen-limited base and consequently herbivores must compensate through selection of high-protein foods and efficient nitrogen retention. Like many folivorous primates, gorillas' diet selection supports this assumption, as they apparently prefer protein-rich foods. Our study of mountain gorillas (Gorilla beringei) in Uganda revealed that, in some periods, carbohydrate-rich fruits displace a large portion of protein-rich leaves in their diet. We show that non-protein energy (NPE) intake was invariant throughout the year, whereas protein intake was substantially higher when leaves were the major portion of the diet. This pattern of macronutrient intake suggests that gorillas prioritize NPE and, to achieve this when leaves are the major dietary item, they over-eat protein. The concentrations of protein consumed in relation to energy when leaves were the major portion of the diet were close to the maximum recommended for humans and similar to high-protein human weight-loss diets. By contrast, the concentrations of protein in relation to energy when gorillas ate fruit-dominated diets were similar to those recommended for humans. Our results question the generality of nitrogen limitation in terrestrial herbivores and provide a fascinating contrast with human macronutrient intake.

Nutritional geometry: gorillas prioritize non-protein energy while consuming surplus protein

Science.gov (United States)

Rothman, Jessica M.; Raubenheimer, David; Chapman, Colin A.

2011-01-01

It is widely assumed that terrestrial food webs are built on a nitrogen-limited base and consequently herbivores must compensate through selection of high-protein foods and efficient nitrogen retention. Like many folivorous primates, gorillas' diet selection supports this assumption, as they apparently prefer protein-rich foods. Our study of mountain gorillas (Gorilla beringei) in Uganda revealed that, in some periods, carbohydrate-rich fruits displace a large portion of protein-rich leaves in their diet. We show that non-protein energy (NPE) intake was invariant throughout the year, whereas protein intake was substantially higher when leaves were the major portion of the diet. This pattern of macronutrient intake suggests that gorillas prioritize NPE and, to achieve this when leaves are the major dietary item, they over-eat protein. The concentrations of protein consumed in relation to energy when leaves were the major portion of the diet were close to the maximum recommended for humans and similar to high-protein human weight-loss diets. By contrast, the concentrations of protein in relation to energy when gorillas ate fruit-dominated diets were similar to those recommended for humans. Our results question the generality of nitrogen limitation in terrestrial herbivores and provide a fascinating contrast with human macronutrient intake. PMID:21632622

Detecting protein-protein interactions in the intact cell of Bacillus subtilis (ATCC 6633).

Science.gov (United States)

Winters, Michael S; Day, R A

2003-07-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C(2)N(2)) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins.

Hubungan antara konsumsi protein dengan produksi, protein dan laktosa susu kambing Peranakan Ettawa

Directory of Open Access Journals (Sweden)

Galuh Estu Prihatiningsih

2015-09-01

Full Text Available The study aimed to determine a correlation between crude protein intake, milk production, milk protein and milk lactose. This study used purposive sampling method. The sample used in this study were 35 Etawa crossbred goats with months of lactation 4-5 and lactation periods 2-3. Parameters observed were crude protein intake, milk production, milk protein and milk lactose. Data were analyzed using correlation analysis and simple linear regression. The result showed that crude protein intake, total milk production concentrations of milk protein and lactose were 0.77 kg/day; 0.30 kg/day; 0.196% and 3.32% respectively. There was a medium positive linear correlation between the crude protein intake with total milk production, protein and lactose content of milk. The correlation coefficient (r were 0.258; 0.254 and 0,255 respectively. It could be concluded that the higher crude protein intake would increase the amount of milk production, protein and lactose contents. Keywords: crude protein intake, total milk production, milk protein, milk lactose

Protein-losing enteropathy

Science.gov (United States)

... this page: //medlineplus.gov/ency/article/007338.htm Protein-losing enteropathy To use the sharing features on this page, please enable JavaScript. Protein-losing enteropathy is an abnormal loss of protein ...

ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

Interplay between chaperones and protein disorder promotes the evolution of protein networks.

Directory of Open Access Journals (Sweden)

Sebastian Pechmann

2014-06-01

Full Text Available Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the

Function and structure of GFP-like proteins in the protein data bank.

Science.gov (United States)

Ong, Wayne J-H; Alvarez, Samuel; Leroux, Ivan E; Shahid, Ramza S; Samma, Alex A; Peshkepija, Paola; Morgan, Alicia L; Mulcahy, Shawn; Zimmer, Marc

2011-04-01

The RCSB protein databank contains 266 crystal structures of green fluorescent proteins (GFP) and GFP-like proteins. This is the first systematic analysis of all the GFP-like structures in the pdb. We have used the pdb to examine the function of fluorescent proteins (FP) in nature, aspects of excited state proton transfer (ESPT) in FPs, deformation from planarity of the chromophore and chromophore maturation. The conclusions reached in this review are that (1) The lid residues are highly conserved, particularly those on the "top" of the β-barrel. They are important to the function of GFP-like proteins, perhaps in protecting the chromophore or in β-barrel formation. (2) The primary/ancestral function of GFP-like proteins may well be to aid in light induced electron transfer. (3) The structural prerequisites for light activated proton pumps exist in many structures and it's possible that like bioluminescence, proton pumps are secondary functions of GFP-like proteins. (4) In most GFP-like proteins the protein matrix exerts a significant strain on planar chromophores forcing most GFP-like proteins to adopt non-planar chromophores. These chromophoric deviations from planarity play an important role in determining the fluorescence quantum yield. (5) The chemospatial characteristics of the chromophore cavity determine the isomerization state of the chromophore. The cavities of highlighter proteins that can undergo cis/trans isomerization have chemospatial properties that are common to both cis and trans GFP-like proteins.

Protein-protein docking with dynamic residue protonation states.

Directory of Open Access Journals (Sweden)

Krishna Praneeth Kilambi

2014-12-01

Full Text Available Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161 the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

Protein scissors: Photocleavage of proteins at specific locations

Indian Academy of Sciences (India)

Unknown

Binding of ligands to globular proteins at hydrophobic cavities while making specific ... ched to a PTI model A1010 monochromator. UV cut-off filter ..... >1:1 stoichiometry (protein to ligand), the binding equilibrium favors the thermo- dynamically ...

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

Directory of Open Access Journals (Sweden)

Jun Ren

2014-01-01

Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

Defective Proteasome Delivery of Polyubiquitinated Proteins by Ubiquilin-2 Proteins Containing ALS Mutations.

Directory of Open Access Journals (Sweden)

Lydia Chang

Full Text Available Ubiquilin proteins facilitate delivery of ubiquitinated proteins to the proteasome for degradation. Interest in the proteins has been heightened by the discovery that gene mutations in UBQLN2 cause dominant inheritance of amyotrophic lateral sclerosis (ALS. However, the mechanisms by which the mutations cause ALS are not known. Here we report on the underlying defect of ubiquilin-2 proteins containing ALS-linked mutations in affecting proteasome-mediated degradation. We found that overexpression of ubiquilin-2 proteins containing any one of five different ALS mutations slow degradation of Myc, a prototypic proteasome substrate. Examination of coprecipitating proteins indicated that the mutant proteins are generally capable of binding polyubiquitinated proteins, but defective in binding the proteasome. GST-pulldown studies revealed that many of the mutants bind weaker to the S5a subunit of the proteasome, compared with wild type (WT ubiquilin-2 protein. The results suggest the mutant proteins are unable to deliver their captured cargo to the proteasome for degradation, which presumably leads to toxicity. Quantification of cell death is consistent with this idea. Measurement of protein turnover further indicated the mutant proteins have longer half-lives than WT ubiquilin-2. Our studies provide novel insight into the mechanism by which ALS-linked mutations in UBQLN2 interfere with protein degradation.

Analysis of protein folds using protein contact networks

Indian Academy of Sciences (India)

is a well-recognized classification system of proteins, which is based on manual in- ... can easily correspond to the information in the 2D matrix. ..... [7] U K Muppirala and Zhijun Li, Protein Engineering, Design & Selection 19, 265 (2006).

Improved segmental isotope labeling of proteins and application to a larger protein

International Nuclear Information System (INIS)

Otomo, Takanori; Teruya, Kenta; Uegaki, Koichi; Yamazaki, Toshio; Kyogoku, Yoshimasa

1999-01-01

A new isotope labeling technique for peptide segments in a protein sample was recently established using the protein splicing element intein [Yamazaki et al. (1998) J. Am. Chem. Soc., 120, 5591-5592]. This method makes it possible to observe signals of a selected amino (N-) or carboxyl (C-) terminal region along a peptide chain. However, there is a problem with the yield of the segmentally labeled protein. In this paper, we report an increase in the yield of the protein that enables the production of sufficient amounts of segmentally 13 C/ 15 N-labeled protein samples. This was achieved by improvement of the expression level of the N-terminal fragment in cells and the efficiency of refolding into the active splicing conformation. The N-terminal fragment was expressed as a fused protein with the cellulose binding domain at its N-terminus, which was expressed as an insoluble peptide in cells and the expression level was increased. Incubation with 2.5 M urea and 50% glycerol increased the efficiency of the refolding greatly, thereby raising the final yields of the ligated proteins. The feasibility of application of the method to a high-molecular-weight protein was demonstrated by the results for a maltose binding protein consisting of 370 amino acids. All four examined joints in the maltose binding protein were successfully ligated to produce segmentally labeled protein samples

Protein in diet

Science.gov (United States)

Diet - protein ... Protein foods are broken down into parts called amino acids during digestion. The human body needs a ... to eat animal products to get all the protein you need in your diet. Amino acids are ...

An analysis pipeline for the inference of protein-protein interaction networks

Energy Technology Data Exchange (ETDEWEB)

Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

2009-12-01

An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

A new protein-protein interaction sensor based on tripartite split-GFP association.

Science.gov (United States)

Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

2013-10-04

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

Prediction of protein-protein interactions between viruses and human by an SVM model

Directory of Open Access Journals (Sweden)

Cui Guangyu

2012-05-01

Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

IGSF9 Family Proteins

DEFF Research Database (Denmark)

Hansen, Maria; Walmod, Peter Schledermann

2013-01-01

The Drosophila protein Turtle and the vertebrate proteins immunoglobulin superfamily (IgSF), member 9 (IGSF9/Dasm1) and IGSF9B are members of an evolutionarily ancient protein family. A bioinformatics analysis of the protein family revealed that invertebrates contain only a single IGSF9 family gene......, the longest isoforms of the proteins have the same general organization as the neural cell adhesion molecule family of cell adhesion molecule proteins, and like this family of proteins, IGSF9 family members are expressed in the nervous system. A review of the literature revealed that Drosophila Turtle...... facilitates homophilic cell adhesion. Moreover, IGSF9 family proteins have been implicated in the outgrowth and branching of neurites, axon guidance, synapse maturation, self-avoidance, and tiling. However, despite the few published studies on IGSF9 family proteins, reports on the functions of both Turtle...

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

NARCIS (Netherlands)

Melo, Rita; Fieldhouse, Robert; Melo, André; Correia, João D G; Cordeiro, Maria Natália D S; Gümüş, Zeynep H; Costa, Joaquim; Bonvin, Alexandre M J J; de Sousa Moreira, Irina

2016-01-01

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model

Factor VII and protein C are phosphatidic acid-binding proteins.

Science.gov (United States)

Tavoosi, Narjes; Smith, Stephanie A; Davis-Harrison, Rebecca L; Morrissey, James H

2013-08-20

Seven proteins in the human blood clotting cascade bind, via their GLA (γ-carboxyglutamate-rich) domains, to membranes containing exposed phosphatidylserine (PS), although with membrane binding affinities that vary by 3 orders of magnitude. Here we employed nanodiscs of defined phospholipid composition to quantify the phospholipid binding specificities of these seven clotting proteins. All bound preferentially to nanobilayers in which PS headgroups contained l-serine versus d-serine. Surprisingly, however, nanobilayers containing phosphatidic acid (PA) bound substantially more of two of these proteins, factor VIIa and activated protein C, than did equivalent bilayers containing PS. Consistent with this finding, liposomes containing PA supported higher proteolytic activity by factor VIIa and activated protein C toward their natural substrates (factors X and Va, respectively) than did PS-containing liposomes. Moreover, treating activated human platelets with phospholipase D enhanced the rates of factor X activation by factor VIIa in the presence of soluble tissue factor. We hypothesize that factor VII and protein C bind preferentially to the monoester phosphate of PA because of its accessibility and higher negative charge compared with the diester phosphates of most other phospholipids. We further found that phosphatidylinositol 4-phosphate, which contains a monoester phosphate attached to its myo-inositol headgroup, also supported enhanced enzymatic activity of factor VIIa and activated protein C. We conclude that factor VII and protein C bind preferentially to monoester phosphates, which may have implications for the function of these proteases in vivo.

High Dietary Protein Intake and Protein-Related Acid Load on Bone Health.

Science.gov (United States)

Cao, Jay J

2017-12-01

Consumption of high-protein diets is increasingly popular due to the benefits of protein on preserving lean mass and controlling appetite and satiety. The paper is to review recent clinical research assessing dietary protein on calcium metabolism and bone health. Epidemiological studies show that long-term, high-protein intake is positively associated with bone mineral density and reduced risk of bone fracture incidence. Short-term interventional studies demonstrate that a high-protein diet does not negatively affect calcium homeostasis. Existing evidence supports that the negative effects of the acid load of protein on urinary calcium excretion are offset by the beneficial skeletal effects of high-protein intake. Future research should focus on the role and the degree of contribution of other dietary and physiological factors, such as intake of fruits and vegetables, in reducing the acid load and further enhancing the anabolic effects of protein on the musculoskeletal system.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

Directory of Open Access Journals (Sweden)

Dobbs Drena

2011-06-01

Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

Plant protein and animal proteins: do they differentially affect cardiovascular disease risk?

Science.gov (United States)

Richter, Chesney K; Skulas-Ray, Ann C; Champagne, Catherine M; Kris-Etherton, Penny M

2015-11-01

Proteins from plant-based compared with animal-based food sources may have different effects on cardiovascular disease (CVD) risk factors. Numerous epidemiologic and intervention studies have evaluated their respective health benefits; however, it is difficult to isolate the role of plant or animal protein on CVD risk. This review evaluates the current evidence from observational and intervention studies, focusing on the specific protein-providing foods and populations studied. Dietary protein is derived from many food sources, and each provides a different composite of nonprotein compounds that can also affect CVD risk factors. Increasing the consumption of protein-rich foods also typically results in lower intakes of other nutrients, which may simultaneously influence outcomes. Given these complexities, blanket statements about plant or animal protein may be too general, and greater consideration of the specific protein food sources and the background diet is required. The potential mechanisms responsible for any specific effects of plant and animal protein are similarly multifaceted and include the amino acid content of particular foods, contributions from other nonprotein compounds provided concomitantly by the whole food, and interactions with the gut microbiome. Evidence to date is inconclusive, and additional studies are needed to further advance our understanding of the complexity of plant protein vs. animal protein comparisons. Nonetheless, current evidence supports the idea that CVD risk can be reduced by a dietary pattern that provides more plant sources of protein compared with the typical American diet and also includes animal-based protein foods that are unprocessed and low in saturated fat. © 2015 American Society for Nutrition.

Poxviral Ankyrin Proteins

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Michael H. Herbert

2015-02-01

Full Text Available Multiple repeats of the ankyrin motif (ANK are ubiquitous throughout the kingdoms of life but are absent from most viruses. The main exception to this is the poxvirus family, and specifically the chordopoxviruses, with ANK repeat proteins present in all but three species from separate genera. The poxviral ANK repeat proteins belong to distinct orthologue groups spread over different species, and align well with the phylogeny of their genera. This distribution throughout the chordopoxviruses indicates these proteins were present in an ancestral vertebrate poxvirus, and have since undergone numerous duplication events. Most poxviral ANK repeat proteins contain an unusual topology of multiple ANK motifs starting at the N-terminus with a C-terminal poxviral homologue of the cellular F-box enabling interaction with the cellular SCF ubiquitin ligase complex. The subtle variations between ANK repeat proteins of individual poxviruses suggest an array of different substrates may be bound by these protein-protein interaction domains and, via the F-box, potentially directed to cellular ubiquitination pathways and possible degradation. Known interaction partners of several of these proteins indicate that the NF-κB coordinated anti-viral response is a key target, whilst some poxviral ANK repeat domains also have an F-box independent affect on viral host-range.

A high protein diet upregulated whole-body protein turnover during energy deficit

Science.gov (United States)

The effects of higher protein diets and sustained energy deficit (ED) on whole-body protein turnover (WBPTO) are not well described. This study examined whether dietary protein level influences whole-body protein breakdown (Ra), non-oxidative leucine disposal (NOLD), and oxidation (Ox) during ED. ...

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Computational Protein Design

DEFF Research Database (Denmark)

Johansson, Kristoffer Enøe

Proteins are the major functional group of molecules in biology. The impact of protein science on medicine and chemical productions is rapidly increasing. However, the greatest potential remains to be realized. The fi eld of protein design has advanced computational modeling from a tool of support...... to a central method that enables new developments. For example, novel enzymes with functions not found in natural proteins have been de novo designed to give enough activity for experimental optimization. This thesis presents the current state-of-the-art within computational design methods together...... with a novel method based on probability theory. With the aim of assembling a complete pipeline for protein design, this work touches upon several aspects of protein design. The presented work is the computational half of a design project where the other half is dedicated to the experimental part...

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Protein carbonylation and metal-catalyzed protein oxidation in a cellular perspective

DEFF Research Database (Denmark)

Møller, Ian Max; Rogowska-Wrzesinska, Adelina; Rao, R S P

2011-01-01

Proteins can become oxidatively modified in many different ways, either by direct oxidation of amino acid side chains and protein backbone or indirectly by conjugation with oxidation products of polyunsaturated fatty acids and carbohydrates. While reversible oxidative modifications are thought...... to be relevant in physiological processes, irreversible oxidative modifications are known to contribute to cellular damage and disease. The most well-studied irreversible protein oxidation is carbonylation. In this work we first examine how protein carbonylation occurs via metal-catalyzed oxidation (MCO) in vivo...... and in vitro with an emphasis on cellular metal ion homeostasis and metal binding. We then review proteomic methods currently used for identifying carbonylated proteins and their sites of modification. Finally, we discuss the identified carbonylated proteins and the pattern of carbonylation sites in relation...

Protein-protein docking using region-based 3D Zernike descriptors

Directory of Open Access Journals (Sweden)

Sael Lee

2009-12-01

Full Text Available Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for

Total protein

Science.gov (United States)

... page: //medlineplus.gov/ency/article/003483.htm Total protein To use the sharing features on this page, please enable JavaScript. The total protein test measures the total amount of two classes ...

From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

Directory of Open Access Journals (Sweden)

Mu Gao

2009-03-01

Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

Revisiting the description of Protein-Protein interfaces. Part II: Experimental study

OpenAIRE

Cazals , Frédéric; Proust , Flavien

2006-01-01

This paper provides a detailed experimental study of an interface model developed in the companion article F. Cazals and F. Proust, Revisiting the description of Protein-Protein interfaces. Part I: algorithms. Our experimental study is concerned with the usual database of protein-protein complexes, split into five families (Proteases, Immune system, Enzyme Complexes, Signal transduction, Misc.) Our findings, which bear some contradictions with usual statements are the following: (i)Connectivi...

False positive reduction in protein-protein interaction predictions using gene ontology annotations

Directory of Open Access Journals (Sweden)

Lin Yen-Han

2007-07-01

Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

Protein-anchoring therapy to target extracellular matrix proteins to their physiological destinations.

Science.gov (United States)

Ito, Mikako; Ohno, Kinji

2018-02-20

Endplate acetylcholinesterase (AChE) deficiency is a form of congenital myasthenic syndrome (CMS) caused by mutations in COLQ, which encodes collagen Q (ColQ). ColQ is an extracellular matrix (ECM) protein that anchors AChE to the synaptic basal lamina. Biglycan, encoded by BGN, is another ECM protein that binds to the dystrophin-associated protein complex (DAPC) on skeletal muscle, which links the actin cytoskeleton and ECM proteins to stabilize the sarcolemma during repeated muscle contractions. Upregulation of biglycan stabilizes the DPAC. Gene therapy can potentially ameliorate any disease that can be recapitulated in cultured cells. However, the difficulty of tissue-specific and developmental stage-specific regulated expression of transgenes, as well as the difficulty of introducing a transgene into all cells in a specific tissue, prevents us from successfully applying gene therapy to many human diseases. In contrast to intracellular proteins, an ECM protein is anchored to the target tissue via its specific binding affinity for protein(s) expressed on the cell surface within the target tissue. Exploiting this unique feature of ECM proteins, we developed protein-anchoring therapy in which a transgene product expressed even in remote tissues can be delivered and anchored to a target tissue using specific binding signals. We demonstrate the application of protein-anchoring therapy to two disease models. First, intravenous administration of adeno-associated virus (AAV) serotype 8-COLQ to Colq-deficient mice, resulting in specific anchoring of ectopically expressed ColQ-AChE at the NMJ, markedly improved motor functions, synaptic transmission, and the ultrastructure of the neuromuscular junction (NMJ). In the second example, Mdx mice, a model for Duchenne muscular dystrophy, were intravenously injected with AAV8-BGN. The treatment ameliorated motor deficits, mitigated muscle histopathologies, decreased plasma creatine kinase activities, and upregulated expression

Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Science.gov (United States)

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Directory of Open Access Journals (Sweden)

Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

Protein oxidation in aquatic foods

DEFF Research Database (Denmark)

Baron, Caroline P.

2014-01-01

The chapter discusses general considerations about protein oxidation and reviews the mechanisms involved in protein oxidation and consequences of protein oxidation on fish proteins. It presents two case studies, the first deals with protein and lipid oxidation in frozen rainbow trout......, and the second with oxidation in salted herring. The mechanisms responsible for initiation of protein oxidation are unclear, but it is generally accepted that free radical species initiating lipid oxidation can also initiate protein oxidation. The chapter focuses on interaction between protein and lipid...... oxidation. The protein carbonyl group measurement is the widely used method for estimating protein oxidation in foods and has been used in fish muscle. The chapter also talks about the impact of protein oxidation on protein functionality, fish muscle texture, and food nutritional value. Protein oxidation...

Quantification of Protein Hydration, Glass Transitions, and Structural Relaxations of Aqueous Protein and Carbohydrate-Protein Systems.

Science.gov (United States)

Roos, Yrjö H; Potes, Naritchaya

2015-06-11

Water distribution and miscibility of carbohydrate and protein components in biological materials and their structural contributions in concentrated solids are poorly understood. In the present study, structural relaxations and a glass transition of protein hydration water and antiplasticization of the hydration water at low temperatures were measured using dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC) for bovine whey protein (BWP), aqueous glucose-fructose (GF), and their mixture. Thermal transitions of α-lactalbumin and β-lactoglobulin components of BWP included water-content-dependent endothermic but reversible dehydration and denaturation, and exothermic and irreversible aggregation. An α-relaxation assigned to hydration water in BWP appeared at water-content-dependent temperatures and increased to over the range of 150-200 K at decreasing water content and in the presence of GF. Two separate glass transitions and individual fractions of unfrozen water of ternary GF-BWP-water systems contributed to uncoupled α-relaxations, suggesting different roles of protein hydration water and carbohydrate vitrification in concentrated solids during freezing and dehydration. Hydration water in the BWP fraction of GF-BWP systems was derived from equilibrium water sorption and glass transition data of the GF fraction, which gave a significant universal method to quantify (i) protein hydration water and (ii) the unfrozen water in protein-carbohydrate systems for such applications as cryopreservation, freezing, lyophilization, and dehydration of biological materials. A ternary supplemented phase diagram (state diagram) established for the GF-BWP-water system can be used for the analysis of the water distribution across carbohydrate and protein components in such applications.

Implications of protein polymorphism on protein phase behaviour

NARCIS (Netherlands)

Stegen, J.; Schoot, van der P.P.A.M.

2015-01-01

The phase behaviour of small globular proteins is often modeled by approximating them as spherical particles with fixed internal structure. However, changes in the local environment of a protein can lead to changes in its conformation rendering this approximation invalid. We present a simple

CSF total protein

Science.gov (United States)

CSF total protein is a test to determine the amount of protein in your spinal fluid, also called cerebrospinal fluid (CSF). ... The normal protein range varies from lab to lab, but is typically about 15 to 60 milligrams per deciliter (mg/dL) ...

Novel fusion protein approach for efficient high-throughput screening of small molecule-mediating protein-protein interactions in cells and living animals.

Science.gov (United States)

Paulmurugan, Ramasamy; Gambhir, Sanjiv S

2005-08-15

Networks of protein interactions execute many different intracellular pathways. Small molecules either synthesized within the cell or obtained from the external environment mediate many of these protein-protein interactions. The study of these small molecule-mediated protein-protein interactions is important in understanding abnormal signal transduction pathways in a variety of disorders, as well as in optimizing the process of drug development and validation. In this study, we evaluated the rapamycin-mediated interaction of the human proteins FK506-binding protein (FKBP12) rapamycin-binding domain (FRB) and FKBP12 by constructing a fusion of these proteins with a split-Renilla luciferase or a split enhanced green fluorescent protein (split-EGFP) such that complementation of the reporter fragments occurs in the presence of rapamycin. Different linker peptides in the fusion protein were evaluated for the efficient maintenance of complemented reporter activity. This system was studied in both cell culture and xenografts in living animals. We found that peptide linkers with two or four EAAAR repeat showed higher protein-protein interaction-mediated signal with lower background signal compared with having no linker or linkers with amino acid sequences GGGGSGGGGS, ACGSLSCGSF, and ACGSLSCGSFACGSLSCGSF. A 9 +/- 2-fold increase in signal intensity both in cell culture and in living mice was seen compared with a system that expresses both reporter fragments and the interacting proteins separately. In this fusion system, rapamycin induced heterodimerization of the FRB and FKBP12 moieties occurred rapidly even at very lower concentrations (0.00001 nmol/L) of rapamycin. For a similar fusion system employing split-EGFP, flow cytometry analysis showed significant level of rapamycin-induced complementation.

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

Science.gov (United States)

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

Split green fluorescent protein as a modular binding partner for protein crystallization

International Nuclear Information System (INIS)

Nguyen, Hau B.; Hung, Li-Wei; Yeates, Todd O.; Terwilliger, Thomas C.; Waldo, Geoffrey S.

2013-01-01

A strategy using a new split green fluorescent protein (GFP) as a modular binding partner to form stable protein complexes with a target protein is presented. The modular split GFP may open the way to rapidly creating crystallization variants. A modular strategy for protein crystallization using split green fluorescent protein (GFP) as a crystallization partner is demonstrated. Insertion of a hairpin containing GFP β-strands 10 and 11 into a surface loop of a target protein provides two chain crossings between the target and the reconstituted GFP compared with the single connection afforded by terminal GFP fusions. This strategy was tested by inserting this hairpin into a loop of another fluorescent protein, sfCherry. The crystal structure of the sfCherry-GFP(10–11) hairpin in complex with GFP(1–9) was determined at a resolution of 2.6 Å. Analysis of the complex shows that the reconstituted GFP is attached to the target protein (sfCherry) in a structurally ordered way. This work opens the way to rapidly creating crystallization variants by reconstituting a target protein bearing the GFP(10–11) hairpin with a variety of GFP(1–9) mutants engineered for favorable crystallization

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

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Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

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Vakser Ilya A

2011-07-01

Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

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Carson M Andorf

Full Text Available Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners.Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques.Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions.We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

Retinoid-binding proteins: similar protein architectures bind similar ligands via completely different ways.

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Yu-Ru Zhang

Full Text Available BACKGROUND: Retinoids are a class of compounds that are chemically related to vitamin A, which is an essential nutrient that plays a key role in vision, cell growth and differentiation. In vivo, retinoids must bind with specific proteins to perform their necessary functions. Plasma retinol-binding protein (RBP and epididymal retinoic acid binding protein (ERABP carry retinoids in bodily fluids, while cellular retinol-binding proteins (CRBPs and cellular retinoic acid-binding proteins (CRABPs carry retinoids within cells. Interestingly, although all of these transport proteins possess similar structures, the modes of binding for the different retinoid ligands with their carrier proteins are different. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we analyzed the various retinoid transport mechanisms using structure and sequence comparisons, binding site analyses and molecular dynamics simulations. Our results show that in the same family of proteins and subcellular location, the orientation of a retinoid molecule within a binding protein is same, whereas when different families of proteins are considered, the orientation of the bound retinoid is completely different. In addition, none of the amino acid residues involved in ligand binding is conserved between the transport proteins. However, for each specific binding protein, the amino acids involved in the ligand binding are conserved. The results of this study allow us to propose a possible transport model for retinoids. CONCLUSIONS/SIGNIFICANCE: Our results reveal the differences in the binding modes between the different retinoid-binding proteins.

Identification of proteins similar to AvrE type III effector proteins from ...

African Journals Online (AJOL)

Type III effector proteins are injected into host cells through type III secretion systems. Some effectors are similar to host proteins to promote pathogenicity, while others lead to the activation of disease resistance. We used partial least squares alignment-free bioinformatics methods to identify proteins similar to AvrE proteins ...

Interactions between whey proteins and salivary proteins as related to astringency of whey protein beverages at low pH.

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Ye, A; Streicher, C; Singh, H

2011-12-01

Whey protein beverages have been shown to be astringent at low pH. In the present study, the interactions between model whey proteins (β-lactoglobulin and lactoferrin) and human saliva in the pH range from 7 to 2 were investigated using particle size, turbidity, and ζ-potential measurements and sodium dodecyl sulfate-PAGE. The correlation between the sensory results of astringency and the physicochemical data was discussed. Strong interactions between β-lactoglobulin and salivary proteins led to an increase in the particle size and turbidity of mixtures of both unheated and heated β-lactoglobulin and human saliva at pH ∼3.4. However, the large particle size and high turbidity that occurred at pH 2.0 were the result of aggregation of human salivary proteins. The intense astringency in whey protein beverages may result from these increases in particle size and turbidity at these pH values and from the aggregation and precipitation of human salivary proteins alone at pH salivary proteins in the interaction is a key factor in the perception of astringency in whey protein beverages. At any pH, the increases in particle size and turbidity were much smaller in mixtures of lactoferrin and saliva, which suggests that aggregation and precipitation may not be the only mechanism linked to the perception of astringency in whey protein. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Introduction to protein blotting.

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Kurien, Biji T; Scofield, R Hal

2009-01-01

Protein blotting is a powerful and important procedure for the immunodetection of proteins following electrophoresis, particularly proteins that are of low abundance. Since the inception of the protocol for protein transfer from an electrophoresed gel to a membrane in 1979, protein blotting has evolved greatly. The scientific community is now confronted with a variety of ways and means to carry out this transfer.

Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

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Susan Khor

Full Text Available Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

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Khor, Susan

2014-01-01

Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

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Cheng-Hsien Wu

Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

Bacterial Ice Crystal Controlling Proteins

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Lorv, Janet S. H.; Rose, David R.; Glick, Bernard R.

2014-01-01

Across the world, many ice active bacteria utilize ice crystal controlling proteins for aid in freezing tolerance at subzero temperatures. Ice crystal controlling proteins include both antifreeze and ice nucleation proteins. Antifreeze proteins minimize freezing damage by inhibiting growth of large ice crystals, while ice nucleation proteins induce formation of embryonic ice crystals. Although both protein classes have differing functions, these proteins use the same ice binding mechanisms. Rather than direct binding, it is probable that these protein classes create an ice surface prior to ice crystal surface adsorption. Function is differentiated by molecular size of the protein. This paper reviews the similar and different aspects of bacterial antifreeze and ice nucleation proteins, the role of these proteins in freezing tolerance, prevalence of these proteins in psychrophiles, and current mechanisms of protein-ice interactions. PMID:24579057

Potential disruption of protein-protein interactions by graphene oxide

International Nuclear Information System (INIS)

Feng, Mei; Kang, Hongsuk; Luan, Binquan; Yang, Zaixing; Zhou, Ruhong

2016-01-01

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide

Energy Technology Data Exchange (ETDEWEB)

Feng, Mei [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Kang, Hongsuk; Luan, Binquan [Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Yang, Zaixing [Institute of Quantitative Biology and Medicine, SRMP and RAD-X, and Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou 215123 (China); Zhou, Ruhong, E-mail: ruhong@us.ibm.com [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Department of Chemistry, Columbia University, New York, New York 10027 (United States)

2016-06-14

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Effects of Whey, Caseinate, or Milk Protein Ingestion on Muscle Protein Synthesis after Exercise.

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Kanda, Atsushi; Nakayama, Kyosuke; Sanbongi, Chiaki; Nagata, Masashi; Ikegami, Shuji; Itoh, Hiroyuki

2016-06-03

Whey protein (WP) is characterized as a "fast" protein and caseinate (CA) as a "slow" protein according to their digestion and absorption rates. We hypothesized that co-ingestion of milk proteins (WP and CA) may be effective for prolonging the muscle protein synthesis response compared to either protein alone. We therefore compared the effect of ingesting milk protein (MP) to either WP or CA alone on muscle protein synthesis after exercise in rats. We also compared the effects of these milk-derived proteins to a control, soy protein (SP). Male Sprague-Dawley rats swam for two hours. Immediately after exercise, one of the following four solutions was administered: WP, CA, MP, or SP. Individual rats were euthanized at designated postprandial time points and triceps muscle samples collected for measurement of the protein fractional synthesis rate (FSR). FSR tended to increase in all groups post-ingestion, although the initial peaks of FSR occurred at different times (WP, peak time = 60 min, FSR = 7.76%/day; MP, peak time = 90 min, FSR = 8.34%/day; CA, peak time = 120 min, FSR = 7.85%/day). Milk-derived proteins caused significantly greater increases (p protein synthesis to occur at different times (WP, fast; MP, intermediate; CA, slow) and the dairy proteins have a superior effect on muscle protein synthesis after exercise compared with SP.

Aging Is Accompanied by a Blunted Muscle Protein Synthetic Response to Protein Ingestion.

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Benjamin Toby Wall

Full Text Available Progressive loss of skeletal muscle mass with aging (sarcopenia forms a global health concern. It has been suggested that an impaired capacity to increase muscle protein synthesis rates in response to protein intake is a key contributor to sarcopenia. We assessed whether differences in post-absorptive and/or post-prandial muscle protein synthesis rates exist between large cohorts of healthy young and older men.We performed a cross-sectional, retrospective study comparing in vivo post-absorptive muscle protein synthesis rates determined with stable isotope methodologies between 34 healthy young (22±1 y and 72 older (75±1 y men, and post-prandial muscle protein synthesis rates between 35 healthy young (22±1 y and 40 older (74±1 y men.Post-absorptive muscle protein synthesis rates did not differ significantly between the young and older group. Post-prandial muscle protein synthesis rates were 16% lower in the older subjects when compared with the young. Muscle protein synthesis rates were >3 fold more responsive to dietary protein ingestion in the young. Irrespective of age, there was a strong negative correlation between post-absorptive muscle protein synthesis rates and the increase in muscle protein synthesis rate following protein ingestion.Aging is associated with the development of muscle anabolic inflexibility which represents a key physiological mechanism underpinning sarcopenia.

Dietary protein restriction for renal patients: don't forget protein-free foods.

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D'Alessandro, Claudia; Rossi, Andrea; Innocenti, Maurizio; Ricchiuti, Guido; Bozzoli, Laura; Sbragia, Giulietta; Meola, Mario; Cupisti, Adamasco

2013-09-01

The treatment of chronic kidney disease (CKD) consists of pharmacological, nutritional, and psychological-social approaches. The dietary therapy of CKD, namely a low-protein low-phosphorus diet, plays a crucial role in contributing to delay the onset of end-stage renal disease (ESRD) and to protect cardiovascular and nutritional status. The protein-free food products represent a very important tool for the implementation of a low-protein diet to ensure adequate energy supply, reducing the production of nitrogenous waste products. This survey included 100 consecutive CKD patients who were asked their opinion about the use of protein-free foods. Ninety-eight patients (98%) reported a regular daily intake of protein-free pasta (as macaroni, spaghetti, etc.), which was the preferred product consumed. Actually, the taste and texture of protein-free pasta were considered as "good" or "very good" by 70% of patients. Conversely, 43% of CKD patients perceived the taste and texture of protein-free bread as "bad" or "very bad", and 30% found it "acceptable". Therefore, the main concern for the implementation of low-protein diets is the use and palatability of the protein-free products, bread in particular. The use of these products may help in reducing protein, phosphorus, and sodium intake while supplying an adequate energy intake, which represents the basis for a nutritionally safe and successful dietary treatment of advanced CKD patients. Manufacturers and food technology should make more efforts to finding new solutions to improve the taste and texture of protein-free products. Copyright © 2013 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Structural deformation upon protein-protein interaction: a structural alphabet approach.

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Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-02-28

In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Structural deformation upon protein-protein interaction: A structural alphabet approach

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Lecornet Hélène

2008-02-01

Full Text Available Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%. This proportion is even greater in the interface regions (41%. Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Convergence of Artificial Protein Polymers and Intrinsically Disordered Proteins.

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Dzuricky, Michael; Roberts, Stefan; Chilkoti, Ashutosh

2018-05-01

A flurry of research in recent years has revealed the molecular origins of many membraneless organelles to be the liquid phase separation of intrinsically disordered proteins (IDPs). Consequently, protein disorder has emerged as an important driver of intracellular compartmentalization by providing specialized microenvironments chemically distinct from the surrounding medium. Though the importance of protein disorder and its relationship to intracellular phase behavior are clear, a detailed understanding of how such phase behavior can be predicted and controlled remains elusive. While research in IDPs has largely focused on the implications of structural disorder on cellular function and disease, another field, that of artificial protein polymers, has focused on the de novo design of protein polymers with controllable material properties. A subset of these polymers, specifically those derived from structural proteins such as elastin and resilin, are also disordered sequences that undergo liquid-liquid phase separation. This phase separation has been used in a variety of biomedical applications, and researchers studying these polymers have developed methods to precisely characterize and tune their phase behavior. Despite their disparate origins, both fields are complementary as they study the phase behavior of intrinsically disordered polypeptides. This Perspective hopes to stimulate collaborative efforts by highlighting the similarities between these two fields and by providing examples of how such collaboration could be mutually beneficial.

Intercellular protein-protein interactions at synapses.

Science.gov (United States)

Yang, Xiaofei; Hou, Dongmei; Jiang, Wei; Zhang, Chen

2014-06-01

Chemical synapses are asymmetric intercellular junctions through which neurons send nerve impulses to communicate with other neurons or excitable cells. The appropriate formation of synapses, both spatially and temporally, is essential for brain function and depends on the intercellular protein-protein interactions of cell adhesion molecules (CAMs) at synaptic clefts. The CAM proteins link pre- and post-synaptic sites, and play essential roles in promoting synapse formation and maturation, maintaining synapse number and type, accumulating neurotransmitter receptors and ion channels, controlling neuronal differentiation, and even regulating synaptic plasticity directly. Alteration of the interactions of CAMs leads to structural and functional impairments, which results in many neurological disorders, such as autism, Alzheimer's disease and schizophrenia. Therefore, it is crucial to understand the functions of CAMs during development and in the mature neural system, as well as in the pathogenesis of some neurological disorders. Here, we review the function of the major classes of CAMs, and how dysfunction of CAMs relates to several neurological disorders.

Whey Protein

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... reliable information about the safety of taking whey protein if you are pregnant or breast feeding. Stay on the safe side and avoid use. Milk allergy: If you are allergic to cow's milk, avoid using whey protein.

Proteins engineering

International Nuclear Information System (INIS)

2000-01-01

At the - Departement d'Ingenierie et d'etudes de proteines (Deip) of the CEA more than seventy researchers are working hard to understand the function of proteins. For that they use the molecular labelling technique (F.M.)

Efficient cellular solid-state NMR of membrane proteins by targeted protein labeling

Energy Technology Data Exchange (ETDEWEB)

Baker, Lindsay A. [University of Oxford, Oxford Particle Imaging Centre, The Wellcome Trust Centre for Human Genetics, Division of Structural Biology, Nuffield Department of Medicine (United Kingdom); Daniëls, Mark; Cruijsen, Elwin A. W. van der; Folkers, Gert E.; Baldus, Marc, E-mail: m.baldus@uu.nl [Utrecht University, NMR Spectroscopy, Department of Chemistry, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands)

2015-06-15

Solid-state NMR spectroscopy (ssNMR) has made significant progress towards the study of membrane proteins in their native cellular membranes. However, reduced spectroscopic sensitivity and high background signal levels can complicate these experiments. Here, we describe a method for ssNMR to specifically label a single protein by repressing endogenous protein expression with rifampicin. Our results demonstrate that treatment of E. coli with rifampicin during induction of recombinant membrane protein expression reduces background signals for different expression levels and improves sensitivity in cellular membrane samples. Further, the method reduces the amount of time and resources needed to produce membrane protein samples, enabling new strategies for studying challenging membrane proteins by ssNMR.

Efficient cellular solid-state NMR of membrane proteins by targeted protein labeling

International Nuclear Information System (INIS)

Baker, Lindsay A.; Daniëls, Mark; Cruijsen, Elwin A. W. van der; Folkers, Gert E.; Baldus, Marc

2015-01-01

Solid-state NMR spectroscopy (ssNMR) has made significant progress towards the study of membrane proteins in their native cellular membranes. However, reduced spectroscopic sensitivity and high background signal levels can complicate these experiments. Here, we describe a method for ssNMR to specifically label a single protein by repressing endogenous protein expression with rifampicin. Our results demonstrate that treatment of E. coli with rifampicin during induction of recombinant membrane protein expression reduces background signals for different expression levels and improves sensitivity in cellular membrane samples. Further, the method reduces the amount of time and resources needed to produce membrane protein samples, enabling new strategies for studying challenging membrane proteins by ssNMR

Protein 4.1, a component of the erythrocyte membrane skeleton and its related homologue proteins forming the protein 4.1/FERM superfamily.

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Aleksander F Sikorski

2007-01-01

Full Text Available The review is focused on the domain structure and function of protein 4.1, one of the proteins belonging to the membrane skeleton. The protein 4.1 of the red blood cells (4.1R is a multifunctional protein that localizes to the membrane skeleton and stabilizes erythrocyte shape and membrane mechanical properties, such as deformability and stability, via lateral interactions with spectrin, actin, glycophorin C and protein p55. Protein 4.1 binding is modulated through the action of kinases and/or calmodulin-Ca2+. Non-erythroid cells express the 4.1R homologues: 4.1G (general type, 4.1B (brain type, and 4.1N (neuron type, and the whole group belongs to the protein 4.1 superfamily, which is characterized by the presence of a highly conserved FERM domain at the N-terminus of the molecule. Proteins 4.1R, 4.1G, 4.1N and 4.1B are encoded by different genes. Most of the 4.1 superfamily proteins also contain an actin-binding domain. To date, more than 40 members have been identified. They can be divided into five groups: protein 4.1 molecules, ERM proteins, talin-related molecules, protein tyrosine phosphatase (PTPH proteins and NBL4 proteins. We have focused our attention on the main, well known representatives of 4.1 superfamily and tried to choose the proteins which are close to 4.1R or which have distinct functions. 4.1 family proteins are not just linkers between the plasma membrane and membrane skeleton; they also play an important role in various processes. Some, such as focal adhesion kinase (FAK, non-receptor tyrosine kinase that localizes to focal adhesions in adherent cells, play the role in cell adhesion. The other members control or take part in tumor suppression, regulation of cell cycle progression, inhibition of cell proliferation, downstream signaling of the glutamate receptors, and establishment of cell polarity; some are also involved in cell proliferation, cell motility, and/or cell-to-cell communication.

PROTEIN - WHICH IS BEST?

Directory of Open Access Journals (Sweden)

Michael J. Falvo

2004-09-01

Full Text Available Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids, whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function are also reviewed

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

Directory of Open Access Journals (Sweden)

Jillian L Blatti

Full Text Available Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP and thioesterase (TE govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

Science.gov (United States)

Fleishman, Sarel

2012-02-01

Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

Directory of Open Access Journals (Sweden)

Barkallah Insaf

2009-04-01

Full Text Available Abstract Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R1 (Deira, resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP and the Protein Structural Interactome (PSI-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

Physics of protein folding

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Finkelstein, A. V.; Galzitskaya, O. V.

2004-04-01

Protein physics is grounded on three fundamental experimental facts: protein, this long heteropolymer, has a well defined compact three-dimensional structure; this structure can spontaneously arise from the unfolded protein chain in appropriate environment; and this structure is separated from the unfolded state of the chain by the “all-or-none” phase transition, which ensures robustness of protein structure and therefore of its action. The aim of this review is to consider modern understanding of physical principles of self-organization of protein structures and to overview such important features of this process, as finding out the unique protein structure among zillions alternatives, nucleation of the folding process and metastable folding intermediates. Towards this end we will consider the main experimental facts and simple, mostly phenomenological theoretical models. We will concentrate on relatively small (single-domain) water-soluble globular proteins (whose structure and especially folding are much better studied and understood than those of large or membrane and fibrous proteins) and consider kinetic and structural aspects of transition of initially unfolded protein chains into their final solid (“native”) 3D structures.

Graphene oxide as a protein matrix: influence on protein biophysical properties.

Science.gov (United States)

Hernández-Cancel, Griselle; Suazo-Dávila, Dámaris; Ojeda-Cruzado, Axel J; García-Torres, Desiree; Cabrera, Carlos R; Griebenow, Kai

2015-10-19

This study provides fundamental information on the influence of graphene oxide (GO) nanosheets and glycans on protein catalytic activity, dynamics, and thermal stability. We provide evidence of protein stabilization by glycans and how this strategy could be implemented when GO nanosheets is used as protein immobilization matrix. A series of bioconjugates was constructed using two different strategies: adsorbing or covalently attaching native and glycosylated bilirubin oxidase (BOD) to GO. Bioconjugate formation was followed by FT-IR, zeta-potential, and X-ray photoelectron spectroscopy measurements. Enzyme kinetic parameters (k(m) and k(cat)) revealed that the substrate binding affinity was not affected by glycosylation and immobilization on GO, but the rate of enzyme catalysis was reduced. Structural analysis by circular dichroism showed that glycosylation did not affect the tertiary or the secondary structure of BOD. However, GO produced slight changes in the secondary structure. To shed light into the biophysical consequence of protein glycosylation and protein immobilization on GO nanosheets, we studied structural protein dynamical changes by FT-IR H/D exchange and thermal inactivation. It was found that glycosylation caused a reduction in structural dynamics that resulted in an increase in thermostability and a decrease in the catalytic activity for both, glycoconjugate and immobilized enzyme. These results establish the usefulness of chemical glycosylation to modulate protein structural dynamics and stability to develop a more stable GO-protein matrix.

ProteinTracker: an application for managing protein production and purification.

Science.gov (United States)

Ponko, Stefan C; Bienvenue, David

2012-05-10

Laboratories that produce protein reagents for research and development face the challenge of deciding whether to track batch-related data using simple file based storage mechanisms (e.g. spreadsheets and notebooks), or commit the time and effort to install, configure and maintain a more complex laboratory information management system (LIMS). Managing reagent data stored in files is challenging because files are often copied, moved, and reformatted. Furthermore, there is no simple way to query the data if/when questions arise. Commercial LIMS often include additional modules that may be paid for but not actually used, and often require software expertise to truly customize them for a given environment. This web-application allows small to medium-sized protein production groups to track data related to plasmid DNA, conditioned media samples (supes), cell lines used for expression, and purified protein information, including method of purification and quality control results. In addition, a request system was added that includes a means of prioritizing requests to help manage the high demand of protein production resources at most organizations. ProteinTracker makes extensive use of existing open-source libraries and is designed to track essential data related to the production and purification of proteins. ProteinTracker is an open-source web-based application that provides organizations with the ability to track key data involved in the production and purification of proteins and may be modified to meet the specific needs of an organization. The source code and database setup script can be downloaded from http://sourceforge.net/projects/proteintracker. This site also contains installation instructions and a user guide. A demonstration version of the application can be viewed at http://www.proteintracker.org.

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

Science.gov (United States)

Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

ProteinAC: a frequency domain technique for analyzing protein dynamics

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Bozkurt Varolgunes, Yasemin; Demir, Alper

2018-03-01

It is widely believed that the interactions of proteins with ligands and other proteins are determined by their dynamic characteristics as opposed to only static, time-invariant processes. We propose a novel computational technique, called ProteinAC (PAC), that can be used to analyze small scale functional protein motions as well as interactions with ligands directly in the frequency domain. PAC was inspired by a frequency domain analysis technique that is widely used in electronic circuit design, and can be applied to both coarse-grained and all-atom models. It can be considered as a generalization of previously proposed static perturbation-response methods, where the frequency of the perturbation becomes the key. We discuss the precise relationship of PAC to static perturbation-response schemes. We show that the frequency of the perturbation may be an important factor in protein dynamics. Perturbations at different frequencies may result in completely different response behavior while magnitude and direction are kept constant. Furthermore, we introduce several novel frequency dependent metrics that can be computed via PAC in order to characterize response behavior. We present results for the ferric binding protein that demonstrate the potential utility of the proposed techniques.

The Protein Model Portal

OpenAIRE

Arnold, Konstantin; Kiefer, Florian; Kopp, J?rgen; Battey, James N. D.; Podvinec, Michael; Westbrook, John D.; Berman, Helen M.; Bordoli, Lorenza; Schwede, Torsten

2008-01-01

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploratio...

Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

Science.gov (United States)

DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The protein micro-crystallography beamlines for targeted protein research program

International Nuclear Information System (INIS)

Hirata, Kunio; Yamamoto, Masaki; Matsugaki, Naohiro; Wakatsuki, Soichi

2010-01-01

In order to collect proper diffraction data from outstanding micro-crystals, a brand-new data collection system should be designed to provide high signal-to noise ratio in diffraction images. SPring-8 and KEK-PF are currently developing two micro-beam beamlines for Targeted Proteins Research Program by MEXT of Japan. The program aims to reveal the structure and function of proteins that are difficult to solve but have great importance in both academic research and industrial application. At SPring-8, a new 1-micron beam beamline for protein micro-crystallography, RIKEN Targeted Proteins Beamline (BL32XU), is developed. At KEK-PF a new low energy micro-beam beamline, BL-1A, is dedicated for SAD micro-crystallography. The two beamlines will start operation in the end of 2010. The present status of the research and development for protein micro-crystallography will be presented. (author)

A Bacillus megaterium System for the Production of Recombinant Proteins and Protein Complexes.

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Biedendieck, Rebekka

2016-01-01

For many years the Gram-positive bacterium Bacillus megaterium has been used for the production and secretion of recombinant proteins. For this purpose it was systematically optimized. Plasmids with different inducible promoter systems, with different compatible origins, with small tags for protein purification and with various specific signals for protein secretion were combined with genetically improved host strains. Finally, the development of appropriate cultivation conditions for the production strains established this organism as a bacterial cell factory even for large proteins. Along with the overproduction of individual proteins the organism is now also used for the simultaneous coproduction of up to 14 recombinant proteins, multiple subsequently interacting or forming protein complexes. Some of these recombinant strains are successfully used for bioconversion or the biosynthesis of valuable components including vitamins. The titers in the g per liter scale for the intra- and extracellular recombinant protein production prove the high potential of B. megaterium for industrial applications. It is currently further enhanced for the production of recombinant proteins and multi-subunit protein complexes using directed genetic engineering approaches based on transcriptome, proteome, metabolome and fluxome data.

Protein-Protein Interaction Reagents | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

Directory of Open Access Journals (Sweden)

Sylvie Lalonde

2010-09-01

Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

Cell-free system for synthesizing membrane proteins cell free method for synthesizing membrane proteins

Science.gov (United States)

Laible, Philip D; Hanson, Deborah K

2013-06-04

The invention provides an in vitro method for producing proteins, membrane proteins, membrane-associated proteins, and soluble proteins that interact with membrane-associated proteins for assembly into an oligomeric complex or that require association with a membrane for proper folding. The method comprises, supplying intracytoplasmic membranes from organisms; modifying protein composition of intracytoplasmic membranes from organism by modifying DNA to delete genes encoding functions of the organism not associated with the formation of the intracytoplasmic membranes; generating appropriate DNA or RNA templates that encode the target protein; and mixing the intracytoplasmic membranes with the template and a transcription/translation-competent cellular extract to cause simultaneous production of the membrane proteins and encapsulation of the membrane proteins within the intracytoplasmic membranes.

Dephosphorylation of chicken cardiac myofibril C-protein by protein phosphatases 1 and 2A

International Nuclear Information System (INIS)

Thysseril, T.J.; Hegazy, M.G.; Schlender, K.K.

1987-01-01

C-Protein, which is a regulatory component of cardiac muscle myofibrils, is phosphorylated in response to β-adrenergic agonists by a cAMP-dependent mechanism and dephosphorylated in response to cholinergic agonists. It is believed that the cAMP-dependent phosphorylation is due to cAMP-dependent protein kinase. The protein phosphatase(s) involved in the dephosphorylation of C-protein has not been determined. In this study, chicken cardiac C-protein was phosphorylated with the cAMP-dependent protein kinase to about 3 mol phosphate/mol C-protein. Incubation of [ 32 P]C-protein with the catalytic subunit of protein phosphatase 1 or 2A rapidly removed 30-40% of 32 [P]. Phosphopeptide maps and phosphoamino acid analysis revealed that the major site(s) dephosphorylated by either phosphatase was a phosphothreonine residue(s) located on the same tryptic peptide and on the same CNBr fragment. Increasing the incubation period or the phosphatase concentration did not result in any further dephosphorylation of C-protein by phosphatase 1, but phosphatase 2A completely dephosphorylated C-protein. Preliminary studies showed that the major protein phosphatase associated with the myofibril was phosphatase 2A. These results indicate the phosphatase 2A may be important in the regulation of the phosphorylation state of C-protein

Plant Proteins Are Smaller Because They Are Encoded by Fewer Exons than Animal Proteins.

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Ramírez-Sánchez, Obed; Pérez-Rodríguez, Paulino; Delaye, Luis; Tiessen, Axel

2016-12-01

Protein size is an important biochemical feature since longer proteins can harbor more domains and therefore can display more biological functionalities than shorter proteins. We found remarkable differences in protein length, exon structure, and domain count among different phylogenetic lineages. While eukaryotic proteins have an average size of 472 amino acid residues (aa), average protein sizes in plant genomes are smaller than those of animals and fungi. Proteins unique to plants are ∼81aa shorter than plant proteins conserved among other eukaryotic lineages. The smaller average size of plant proteins could neither be explained by endosymbiosis nor subcellular compartmentation nor exon size, but rather due to exon number. Metazoan proteins are encoded on average by ∼10 exons of small size [∼176 nucleotides (nt)]. Streptophyta have on average only ∼5.7 exons of medium size (∼230nt). Multicellular species code for large proteins by increasing the exon number, while most unicellular organisms employ rather larger exons (>400nt). Among subcellular compartments, membrane proteins are the largest (∼520aa), whereas the smallest proteins correspond to the gene ontology group of ribosome (∼240aa). Plant genes are encoded by half the number of exons and also contain fewer domains than animal proteins on average. Interestingly, endosymbiotic proteins that migrated to the plant nucleus became larger than their cyanobacterial orthologs. We thus conclude that plants have proteins larger than bacteria but smaller than animals or fungi. Compared to the average of eukaryotic species, plants have ∼34% more but ∼20% smaller proteins. This suggests that photosynthetic organisms are unique and deserve therefore special attention with regard to the evolutionary forces acting on their genomes and proteomes. Copyright © 2016 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

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Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

Plant Proteins Are Smaller Because They Are Encoded by Fewer Exons than Animal Proteins

Directory of Open Access Journals (Sweden)

Obed Ramírez-Sánchez

2016-12-01

Full Text Available Protein size is an important biochemical feature since longer proteins can harbor more domains and therefore can display more biological functionalities than shorter proteins. We found remarkable differences in protein length, exon structure, and domain count among different phylogenetic lineages. While eukaryotic proteins have an average size of 472 amino acid residues (aa, average protein sizes in plant genomes are smaller than those of animals and fungi. Proteins unique to plants are ∼81 aa shorter than plant proteins conserved among other eukaryotic lineages. The smaller average size of plant proteins could neither be explained by endosymbiosis nor subcellular compartmentation nor exon size, but rather due to exon number. Metazoan proteins are encoded on average by ∼10 exons of small size [∼176 nucleotides (nt]. Streptophyta have on average only ∼5.7 exons of medium size (∼230 nt. Multicellular species code for large proteins by increasing the exon number, while most unicellular organisms employ rather larger exons (>400 nt. Among subcellular compartments, membrane proteins are the largest (∼520 aa, whereas the smallest proteins correspond to the gene ontology group of ribosome (∼240 aa. Plant genes are encoded by half the number of exons and also contain fewer domains than animal proteins on average. Interestingly, endosymbiotic proteins that migrated to the plant nucleus became larger than their cyanobacterial orthologs. We thus conclude that plants have proteins larger than bacteria but smaller than animals or fungi. Compared to the average of eukaryotic species, plants have ∼34% more but ∼20% smaller proteins. This suggests that photosynthetic organisms are unique and deserve therefore special attention with regard to the evolutionary forces acting on their genomes and proteomes.

Ultrafiltration of pegylated proteins

Science.gov (United States)

Molek, Jessica R.

There is considerable clinical interest in the use of "second-generation" therapeutics produced by conjugation of a native protein with various polymers including polyethylene glycol (PEG). PEG--protein conjugates, so-called PEGylated proteins, can exhibit enhanced stability, half-life, and bioavailability. One of the challenges in the commercial production of PEGylated proteins is the purification required to remove unreacted polymer, native protein, and in many cases PEGylated proteins with nonoptimal degrees of conjugation. The overall objective of this thesis was to examine the use of ultrafiltration for the purification of PEGylated proteins. This included: (1) analysis of size-based separation of PEGylated proteins using conventional ultrafiltration membranes, (2) use of electrically-charged membranes to exploit differences in electrostatic interactions, and (3) examination of the effects of PEGylation on protein fouling. The experimental results were analyzed using appropriate theoretical models, with the underlying physical properties of the PEGylated proteins evaluated using size exclusion chromatography, capillary electrophoresis, dynamic light scattering, and reverse phase chromatography. PEGylated proteins were produced by covalent attachment of activated PEG to a protein via primary amines on the lysine residues. A simple model was developed for the reaction kinetics, which was used to explore the effect of reaction conditions and mode of operation on the distribution of PEGylated products. The effective size of the PEGylated proteins was evaluated using size exclusion chromatography, with appropriate correlations developed for the size in terms of the molecular weight of the native protein and attached PEG. The electrophoretic mobility of the PEGylated proteins were evaluated by capillary electrophoresis with the data in good agreement with a simple model accounting for the increase in protein size and the reduction in the number of protonated amine

Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

OpenAIRE

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

Msp1 Is a Membrane Protein Dislocase for Tail-Anchored Proteins.

Science.gov (United States)

Wohlever, Matthew L; Mateja, Agnieszka; McGilvray, Philip T; Day, Kasey J; Keenan, Robert J

2017-07-20

Mislocalized tail-anchored (TA) proteins of the outer mitochondrial membrane are cleared by a newly identified quality control pathway involving the conserved eukaryotic protein Msp1 (ATAD1 in humans). Msp1 is a transmembrane AAA-ATPase, but its role in TA protein clearance is not known. Here, using purified components reconstituted into proteoliposomes, we show that Msp1 is both necessary and sufficient to drive the ATP-dependent extraction of TA proteins from the membrane. A crystal structure of the Msp1 cytosolic region modeled into a ring hexamer suggests that active Msp1 contains a conserved membrane-facing surface adjacent to a central pore. Structure-guided mutagenesis of the pore residues shows that they are critical for TA protein extraction in vitro and for functional complementation of an msp1 deletion in yeast. Together, these data provide a molecular framework for Msp1-dependent extraction of mislocalized TA proteins from the outer mitochondrial membrane. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel Biosensor of Membrane Protein Proximity Based on Fluorogen Activated Proteins.

Science.gov (United States)

Vasilev, Kalin V; Gallo, Eugenio; Shank, Nathaniel; Jarvik, Jonathan W

2016-01-01

We describe a novel biosensor system for reporting proximity between cell surface proteins in live cultured cells. The biosensor takes advantage of recently developed fluorogen-activating proteins (FAPs) that display fluorescence only when bound to otherwise-nonfluorescent fluorogen molecules. To demonstrate feasibility for the approach, two recombinant rapamycin-binding proteins were expressed as single-pass plasma membrane proteins in HeLa cells; one of the proteins (scAvd- FRB) carried an extracellular avidin tag; the other (HL1-TO1-FKBP) carried an extracellular FAP. Cells were incubated with a membrane-impermeable bivalent ligand (biotin-PEG2000-DIR) consisting of biotin joined to a dimethyl-indole red (DIR) fluorogen by a polyethylene glycol linker, thus tethering the fluorogen to the scAvd-FRB fusion protein. Addition of rapamycin, which promotes FKBP-FRB dimerization and thereby brings the FAP in close proximity to the tethered fluorogen, led to a significant increase in DIR fluorescence. We call the new proximity assay TEFLA, for tethered fluorogen assay.

Protein politics

NARCIS (Netherlands)

Vijver, Marike

2005-01-01

This study is part of the program of the interdisciplinary research group Profetas (protein foods, environment, technology and society). Profetas consists of technological, environmental and socio-economic research projects on protein food systems which result in the development of scenarios and

DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.

Science.gov (United States)

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Banchariya, Anjali; Rao, Atmakuri Ramakrishna

2017-03-24

Insecticide resistance is a major challenge for the control program of insect pests in the fields of crop protection, human and animal health etc. Resistance to different insecticides is conferred by the proteins encoded from certain class of genes of the insects. To distinguish the insecticide resistant proteins from non-resistant proteins, no computational tool is available till date. Thus, development of such a computational tool will be helpful in predicting the insecticide resistant proteins, which can be targeted for developing appropriate insecticides. Five different sets of feature viz., amino acid composition (AAC), di-peptide composition (DPC), pseudo amino acid composition (PAAC), composition-transition-distribution (CTD) and auto-correlation function (ACF) were used to map the protein sequences into numeric feature vectors. The encoded numeric vectors were then used as input in support vector machine (SVM) for classification of insecticide resistant and non-resistant proteins. Higher accuracies were obtained under RBF kernel than that of other kernels. Further, accuracies were observed to be higher for DPC feature set as compared to others. The proposed approach achieved an overall accuracy of >90% in discriminating resistant from non-resistant proteins. Further, the two classes of resistant proteins i.e., detoxification-based and target-based were discriminated from non-resistant proteins with >95% accuracy. Besides, >95% accuracy was also observed for discrimination of proteins involved in detoxification- and target-based resistance mechanisms. The proposed approach not only outperformed Blastp, PSI-Blast and Delta-Blast algorithms, but also achieved >92% accuracy while assessed using an independent dataset of 75 insecticide resistant proteins. This paper presents the first computational approach for discriminating the insecticide resistant proteins from non-resistant proteins. Based on the proposed approach, an online prediction server DIRProt has

Polymer Directed Protein Assemblies

NARCIS (Netherlands)

van Rijn, Patrick

2013-01-01

Protein aggregation and protein self-assembly is an important occurrence in natural systems, and is in some form or other dictated by biopolymers. Very obvious influences of biopolymers on protein assemblies are, e. g., virus particles. Viruses are a multi-protein assembly of which the morphology is

Amino acids and proteins

Science.gov (United States)

A balanced, safe diet with proteins is important to meet nutritional requirements. Proteins occur in animal as well as vegetable products in important quantities. In some countries, many people obtain much of their protein from animal products. In other regions, the major portion of dietary protein ...