Infrastructure for the life sciences: design and implementation of the UniProt website

Jain, Eric; Bairoch, Amos Marc; Duvaud, Séverine; Phan, Isabelle; Redaschi, Nicole; Süzek, Barış E.; Martin, Maria Jesus; McGarvey, Peter B.; Gasteiger, Elisabeth

doi:10.1186/1471-2105-10-136

Cited by 430 publications

(369 citation statements)

References 4 publications

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“…50 Alignment of the human metastasis-suppressor KiSS-1 preproprotein sequence (NP_002247.3) with the human catalase sequence (NP_001743.1) reveals that KiSS-1 residues 110−118 show 78% identity with catalase residues 402−410. Similar results were obtained using the UniProt database 51 with comparison of human KiSS-1 (Q15726) and human catalase (P04040) sequences, which suggested alignment between KiSS-1 residues 109−118 with catalase 401−410 ( Figure 7A). Scheme A ( Figure 7A) shows the proposed binding of Aβ, PrP, and IAPP peptides to the CAβBD based on experimental eveidence obtained with both catalase and CAβBD binding to the Aβ peptides.…”

supporting

confidence: 80%

Kisspeptin Prevention of Amyloid-β Peptide Neurotoxicityin Vitro

Milton

Chilumuri

Rocha‐Ferreira

et al. 2012

ACS Chem. Neurosci.

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Alzheimer's disease (AD) onset is associated with changes in hypothalamic-pituitary−gonadal (HPG) function. The 54 amino acid kisspeptin (KP) peptide regulates the HPG axis and alters antioxidant enzyme expression. The Alzheimer's amyloid-β (Aβ) is neurotoxic, and this action can be prevented by the antioxidant enzyme catalase. Here, we examined the effects of KP peptides on the neurotoxicity of Aβ, prion protein (PrP), and amylin (IAPP) peptides. The Aβ, PrP, and IAPP peptides stimulated the release of KP and KP 45−54. The KP peptides inhibited the neurotoxicity of Aβ, PrP, and IAPP peptides, via an action that could not be blocked by kisspeptin-receptor (GPR-54) or neuropeptide FF (NPFF) receptor antagonists. Knockdown of KiSS-1 gene, which encodes the KP peptides, in human neuronal SH-SY5Y cells with siRNA enhanced the toxicity of amyloid peptides, while KiSS-1 overexpression was neuroprotective. A comparison of the catalase and KP sequences identified a similarity between KP residues 42−51 and the region of catalase that binds Aβ. The KP peptides containing residues 45−50 bound Aβ, PrP, and IAPP, inhibited Congo red binding, and were neuroprotective. These results suggest that KP peptides are neuroprotective against Aβ, IAPP, and PrP peptides via a receptor independent action involving direct binding to the amyloid peptides. KEYWORDS: KiSS-1, kisspeptin, amyloid-β, prion protein, amylin, neuroprotection N euroendocrine hormone changes are seen in aging, and there are disease specific changes associated with Alzheimer's disease (AD). 1,2 One of the neuroendocrine systems to show profound changes with aging is the hypothalamic−pituitary−gonadal (HPG) system, and the pathology of AD, Creutzfeldt−Jakob disease (CJD), and type 2 diabetes mellitus (T2DM) is also associated with changes in the hormones of this system. 3,4 A major regulator of the HPGaxis is the 54 amino acid kisspeptin (KP) peptide, which acts on gonadotrophin-releasing hormone (GnRH) neurons to activate GnRH release. 5 The KP peptide is produced in neurons by processing of the KiSS-1 preproprotein to yield the 54 amino acid KP peptide, which corresponds to residues 68−121 of KiSS-1. 6 Shorter derivatives of KP peptide comprising the C-terminal 14 (KP 41−54), 13 (KP 42−54), and 10 (KP 45−54) amino acids have also been found in tissues and corresponding to residues 108− 121, 109−121, and 112−121 of KiSS-1. 6,7 Biological activity of KP peptides requires the KP 45−54 sequence and is mediated via a specific KP receptor (GPR-54). 6,7 Lack of KP signaling via the GPR-54 receptor is associated with reproductive system failure. 8 Cleavage of the KP 45−54 peptide between residues 51 and 52 by matrix metalloproteinases abolishes the activation of GPR-54 by the KP 45−54 peptide. 9 The KP 42−54 and KP 45−54 peptides also activate NPFF receptors, 10,11 and some of the actions of KP peptides could be mediated by NPFF receptor activation.There are profound changes in KP signaling at menopause 12 and notable sex differences in hypothalamic neurodegenera...

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supporting

confidence: 80%

Kisspeptin Prevention of Amyloid-β Peptide Neurotoxicityin Vitro

Milton

Chilumuri

Rocha‐Ferreira

et al. 2012

ACS Chem. Neurosci.

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“…Shwanavidin Gene and Plasmid Construction-The shwanavidin sequence was discovered using BLAST in the UniProtKB data base via the ExPASy web site (29) as well as the NCBI BLASTp (30,31). Shwanavidin exhibits 50 and 61% sequence similarity, 33 and 47% identity compared with streptavidin and rhizavidin, respectively.…”

Section: Methodsmentioning

confidence: 99%

Structural Adaptation of a Thermostable Biotin-binding Protein in a Psychrophilic Environment

Meir

Bayer

Livnah

2012

Journal of Biological Chemistry

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Background: Search for novel avidins with reduced oligomeric state revealed an intriguing dimeric protein.Results: Structures of shwanavidin from Shewanella denitrificans identified features accountable for high affinity and psychrophilic properties. Conclusion: Phe-43 and disulfide bridge are responsible for the high affinity compensating the lack of intermonomeric interaction in tetrameric avidins. Significance: Proteins from extremophile organisms provide excellent platforms toward the development of novel biotechnological utilizations.

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“…(3) Gene Ontology (GO) semantic similarity: GO annotations (Ashburner et al, 2000) were downloaded from UniProt ( Jain et al, 2009). Semantic similarity scores between targets were calculated according to Resnik (1999), using the csbl.go R package (Ovaska et al, 2008).…”

Section: Similarity-based Drug-target Predictionmentioning

confidence: 99%

Combining Drug and Gene Similarity Measures for Drug-Target Elucidation

Perlman¹,

Gottlieb

Atias

et al. 2011

Journal of Computational Biology

179

131

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Understanding drugs and their modes of action is a fundamental challenge in systems medicine. Key to addressing this challenge is the elucidation of drug targets, an important step in the search for new drugs or novel targets for existing drugs. Incorporating multiple biological information sources is of essence for improving the accuracy of drug target prediction. In this article, we introduce a novel framework-Similarity-based Inference of drug-TARgets (SITAR)-for incorporating multiple drug-drug and gene-gene similarity measures for drug target prediction. The framework consists of a new scoring scheme for drug-gene associations based on a given pair of drug-drug and gene-gene similarity measures, combined with a logistic regression component that integrates the scores of multiple measures to yield the final association score. We apply our framework to predict targets for hundreds of drugs using both commonly used and novel drug-drug and gene-gene similarity measures and compare our results to existing state of the art methods, markedly outperforming them. We then employ our framework to make novel target predictions for hundreds of drugs; we validate these predictions via curated databases that were not used in the learning stage. Our framework provides an extensible platform for incorporating additional emerging similarity measures among drugs and genes. Supplementary Material is available at www.liebertonline .com/cmb.

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Infrastructure for the life sciences: design and implementation of the UniProt website

Cited by 430 publications

References 4 publications

Kisspeptin Prevention of Amyloid-β Peptide Neurotoxicityin Vitro

Kisspeptin Prevention of Amyloid-β Peptide Neurotoxicityin Vitro

Structural Adaptation of a Thermostable Biotin-binding Protein in a Psychrophilic Environment

Combining Drug and Gene Similarity Measures for Drug-Target Elucidation

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