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Find video protocols related to scientific articles indexed in Pubmed.
Following the Digestion of Milk Proteins from Mother to Baby.
J. Proteome Res.
PUBLISHED: 11-12-2014
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Little is known about the digestive process in infants. In particular, the chronological activity of enzymes across the course of digestion in the infant remains largely unknown. To create a temporal picture of how milk proteins are digested, enzyme activity was compared between intact human milk samples from three mothers and the gastric samples from each of their 4-12 day postpartum infants, 2 h after breast milk ingestion. The activities of 7 distinct enzymes are predicted in the infant stomach based on their observed cleavage pattern in peptidomics data. We found that the same patterns of cleavage were evident in both intact human milk and gastric milk samples, demonstrating that the enzyme activities that begin in milk persist in the infant stomach. However, the extent of enzyme activity is found to vary greatly between the intact milk and gastric samples. Overall, we observe that milk-specific proteins are cleaved at higher levels in the stomach compared to human milk. Notably, the enzymes we predict here only explain 78% of the cleavages uniquely observed in the gastric samples, highlighting that further investigation of the specific enzyme activities associated with digestion in infants is warranted.
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Cadherin juxtamembrane region derived peptides inhibit TGF?1 induced gene expression.
Bioarchitecture
PUBLISHED: 08-09-2014
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Bioactive peptides in the juxtamembrane regions of proteins are involved in many signaling events. The juxtamembrane regions of cadherins were examined for the identification of bioactive regions. Several peptides spanning the cytoplasmic juxtamembrane regions of E- and N-cadherin were synthesized and assessed for the ability to influence TGF? responses in epithelial cells at the gene expression and protein levels. Peptides from regions closer to the membrane appeared more potent inhibitors of TGF? signaling, blocking Smad3 phosphorylation. Thus inhibiting nuclear translocation of phosphorylated Smad complexes and subsequent transcriptional activation of TGF? signal propagating genes. The peptides demonstrated a peptide-specific potential to inhibit other TGF? superfamily members, such as BMP4.
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Predicting the important enzymes in human breast milk digestion.
J. Agric. Food Chem.
PUBLISHED: 07-10-2014
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Human milk is known to contain several proteases, but little is known about whether these enzymes are active, which proteins they cleave, and their relative contribution to milk protein digestion in vivo. This study analyzed the mass spectrometry-identified protein fragments found in pooled human milk by comparing their cleavage sites with the enzyme specificity patterns of an array of enzymes. The results indicate that several enzymes are actively taking part in the digestion of human milk proteins within the mammary gland, including plasmin and/or trypsin, elastase, cathepsin D, pepsin, chymotrypsin, a glutamyl endopeptidase-like enzyme, and proline endopeptidase. Two proteins were most affected by enzyme hydrolysis: ?-casein and polymeric immunoglobulin receptor. In contrast, other highly abundant milk proteins such as ?-lactalbumin and lactoferrin appear to have undergone no proteolytic cleavage. A peptide sequence containing a known antimicrobial peptide is released in breast milk by elastase and cathepsin D.
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Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.
Iris Postmus, Stella Trompet, Harshal A Deshmukh, Michael R Barnes, Xiaohui Li, Helen R Warren, Daniel I Chasman, Kaixin Zhou, Benoit J Arsenault, Louise A Donnelly, Kerri L Wiggins, Christy L Avery, Paula Griffin, QiPing Feng, Kent D Taylor, Guo Li, Daniel S Evans, Albert V Smith, Catherine E de Keyser, Andrew D Johnson, Anton J M de Craen, David J Stott, Brendan M Buckley, Ian Ford, Rudi G J Westendorp, P Eline Slagboom, Naveed Sattar, Patricia B Munroe, Peter Sever, Neil Poulter, Alice Stanton, Denis C Shields, Eoin O'Brien, Sue Shaw-Hawkins, Y-D Ida Chen, Deborah A Nickerson, Joshua D Smith, Marie Pierre Dubé, S Matthijs Boekholdt, G Kees Hovingh, John J P Kastelein, Paul M McKeigue, John Betteridge, Andrew Neil, Paul N Durrington, Alex Doney, Fiona Carr, Andrew Morris, Mark I McCarthy, Leif Groop, Emma Ahlqvist, , Joshua C Bis, Kenneth Rice, Nicholas L Smith, Thomas Lumley, Eric A Whitsel, Til Stürmer, Eric Boerwinkle, Julius S Ngwa, Christopher J O'Donnell, Ramachandran S Vasan, Wei-Qi Wei, Russell A Wilke, Ching-Ti Liu, Fangui Sun, Xiuqing Guo, Susan R Heckbert, Wendy Post, Nona Sotoodehnia, Alice M Arnold, Jeanette M Stafford, Jingzhong Ding, David M Herrington, Stephen B Kritchevsky, Gudny Eiriksdottir, Leonore J Launer, Tamara B Harris, Audrey Y Chu, Franco Giulianini, Jean G MacFadyen, Bryan J Barratt, Fredrik Nyberg, Bruno H Stricker, André G Uitterlinden, Albert Hofman, Fernando Rivadeneira, Valur Emilsson, Oscar H Franco, Paul M Ridker, Vilmundur Gudnason, Yongmei Liu, Joshua C Denny, Christie M Ballantyne, Jerome I Rotter, L Adrienne Cupples, Bruce M Psaty, Colin N A Palmer, Jean-Claude Tardif, Helen M Colhoun, Graham Hitman, Ronald M Krauss, J Wouter Jukema, Mark J Caulfield.
Nat Commun
PUBLISHED: 02-27-2014
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Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.
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In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors.
Peptides
PUBLISHED: 02-14-2014
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Molecular docking of a library of all 8000 possible tripeptides to the active site of DPP-IV was used to determine their binding potential. A number of tripeptides were selected for experimental testing, however, there was no direct correlation between the Vina score and their in vitro DPP-IV inhibitory properties. While Trp-Trp-Trp, the peptide with the best docking score, was a moderate DPP-IV inhibitor (IC50 216?M), Lineweaver and Burk analysis revealed its action to be non-competitive. This suggested that it may not bind to the active site of DPP-IV as assumed in the docking prediction. Furthermore, there was no significant link between DPP-IV inhibition and the physicochemical properties of the peptides (molecular mass, hydrophobicity, hydrophobic moment (?H), isoelectric point (pI) and charge). LIGPLOTs indicated that competitive inhibitory peptides were predicted to have both hydrophobic and hydrogen bond interactions with the active site of DPP-IV. DPP-IV inhibitory peptides generally had a hydrophobic or aromatic amino acid at the N-terminus, preferentially a Trp for non-competitive inhibitors and a broader range of residues for competitive inhibitors (Ile, Leu, Val, Phe, Trp or Tyr). Two of the potent DPP-IV inhibitors, Ile-Pro-Ile and Trp-Pro (IC50 values of 3.5 and 44.2?M, respectively), were predicted to be gastrointestinally/intestinally stable. This work highlights the needs to test the assumptions (i.e. competitive binding) of any integrated strategy of computational and experimental screening, in optimizing screening. Future strategies targeting allosteric mechanisms may need to rely more on structure-activity relationship modeling, rather than on docking, in computationally selecting peptides for screening.
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Amino acid enrichment and compositional changes among mammalian milk proteins and the resulting nutritional consequences.
J. Dairy Sci.
PUBLISHED: 01-25-2014
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Milk is a hallmark of mammalian evolution: a unique food that has evolved with mammals. Despite the importance of this food, it is not known if variation in AA composition between different species is important to milk proteins or how it might affect the nutritional value of milk. As milk is the only food source for newborn mammals, it has long been speculated that milk proteins should be enriched in essential AA. However, no systematic analysis supports this assumption. Although many factors influence the overall nutritional value of milk, including total protein concentration, we focused here on the AA composition of milk proteins and investigated the possibility that selection drives compositional changes. We identified 9 major milk proteins present in 13 mammalian species and compared them with a large group of nonmilk proteins. Our results indicate heterogeneity in the AA composition of milk proteins, showing significant enrichment and depletion of certain AA in milk-specific proteins. Although high levels of particular AA appear to be consistently maintained, orthologous milk proteins display significant differences in AA composition across species, most notably among the caseins. Interspecies variation of milk composition is thought to be indicative of nutritional optimization to the requirements of the species. In accordance with this, our observations indicate that milk proteins may have adapted to the species-specific nutritional needs of the neonate.
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Computational survey of peptides derived from disulphide-bonded protein loops that may serve as mediators of protein-protein interactions.
BMC Bioinformatics
PUBLISHED: 01-03-2014
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Bioactive cyclic peptides derived from natural sources are well studied, particularly those derived from non-ribosomal synthetases in fungi or bacteria. Ribosomally synthesised bioactive disulphide-bonded loops represent a large, naturally enriched library of potential bioactive compounds, worthy of systematic investigation.
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Potential of known and short prokaryotic protein motifs as a basis for novel peptide-based antibacterial therapeutics: a computational survey.
Front Microbiol
PUBLISHED: 01-01-2014
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Short linear motifs (SLiMs) are functional stretches of protein sequence that are of crucial importance for numerous biological processes by mediating protein-protein interactions. These motifs often comprise peptides of less than 10 amino acids that modulate protein-protein interactions. While well-characterized in eukaryotic intracellular signaling, their role in prokaryotic signaling is less well-understood. We surveyed the distribution of known motifs in prokaryotic extracellular and virulence proteins across a range of bacterial species and conducted searches for novel motifs in virulence proteins. Many known motifs in virulence effector proteins mimic eukaryotic motifs and enable the pathogen to control the intracellular processes of their hosts. Novel motifs were detected by finding those that had evolved independently in three or more unrelated virulence proteins. The search returned several significantly over-represented linear motifs of which some were known motifs and others are novel candidates with potential roles in bacterial pathogenesis. A putative C-terminal G[AG].$ motif found in type IV secretion system proteins was among the most significant detected. A KK$ motif that has been previously identified in a plasminogen-binding protein, was demonstrated to be enriched across a number of adhesion and lipoproteins. While there is some potential to develop peptide drugs against bacterial infection based on bacterial peptides that mimic host components, this could have unwanted effects on host signaling. Thus, novel SLiMs in virulence factors that do not mimic host components but are crucial for bacterial pathogenesis, such as the type IV secretion system, may be more useful to develop as leads for anti-microbial peptides or drugs.
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CPPpred: prediction of cell penetrating peptides.
Bioinformatics
PUBLISHED: 09-23-2013
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Cell penetrating peptides (CPPs) are attracting much attention as a means of overcoming the inherently poor cellular uptake of various bioactive molecules. Here, we introduce CPPpred, a web server for the prediction of CPPs using a N-to-1 neural network. The server takes one or more peptide sequences, between 5 and 30 amino acids in length, as input and returns a prediction of how likely each peptide is to be cell penetrating. CPPpred was developed with redundancy reduced training and test sets, offering an advantage over the only other currently available CPP prediction method. Availability and Implementation: CPPpred is freely available to non-commercial users at http://bioware.ucd.ie/cpppred.
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Genome-wide analysis of blood pressure variability and ischemic stroke.
Stroke
PUBLISHED: 08-08-2013
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Visit-to-visit variability in blood pressure (vBP) is associated with ischemic stroke. We sought to determine whether such variability has genetic causes and whether genetic variants associated with BP variability are also associated with ischemic stroke.
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SLiMScape: a protein short linear motif analysis plugin for Cytoscape.
BMC Bioinformatics
PUBLISHED: 04-11-2013
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Computational protein short linear motif discovery can use protein interaction information to search for motifs among proteins which share a common interactor. Cytoscape provides a visual interface for protein networks but there is no streamlined way to rapidly visualize motifs in a network of proteins, or to integrate computational discovery with such visualizations.
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SCL-Epred: a generalised de novo eukaryotic protein subcellular localisation predictor.
Amino Acids
PUBLISHED: 03-26-2013
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Knowledge of the subcellular location of a protein provides valuable information about its function, possible interaction with other proteins and drug targetability, among other things. The experimental determination of a proteins location in the cell is expensive, time consuming and open to human error. Fast and accurate predictors of subcellular location have an important role to play if the abundance of sequence data which is now available is to be fully exploited. In the post-genomic era, genomes in many diverse organisms are available. Many of these organisms are important in human and veterinary disease and fall outside of the well-studied plant, animal and fungi groups. We have developed a general eukaryotic subcellular localisation predictor (SCL-Epred) which predicts the location of eukaryotic proteins into three classes which are important, in particular, for determining the drug targetability of a protein-secreted proteins, membrane proteins and proteins that are neither secreted nor membrane. The algorithm powering SCL-Epred is a N-to-1 neural network and is trained on very large non-redundant sets of protein sequences. SCL-Epred performs well on training data achieving a Q of 86 % and a generalised correlation of 0.75 when tested in tenfold cross-validation on a set of 15,202 redundancy reduced protein sequences. The three class accuracy of SCL-Epred and LocTree2, and in particular a consensus predictor comprising both methods, surpasses that of other widely used predictors when benchmarked using a large redundancy reduced independent test set of 562 proteins. SCL-Epred is publicly available at http://distillf.ucd.ie/distill/ .
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Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders.
Marcel den Hoed, Mark Eijgelsheim, Tonu Esko, Bianca J J M Brundel, David S Peal, David M Evans, Ilja M Nolte, Ayellet V Segrè, Hilma Holm, Robert E Handsaker, Harm-Jan Westra, Toby Johnson, Aaron Isaacs, Jian Yang, Alicia Lundby, Jing Hua Zhao, Young Jin Kim, Min Jin Go, Peter Almgren, Murielle Bochud, Gabrielle Boucher, Marilyn C Cornelis, Daniel Gudbjartsson, David Hadley, Pim van der Harst, Caroline Hayward, Martin den Heijer, Wilmar Igl, Anne U Jackson, Zoltan Kutalik, Jian'an Luan, John P Kemp, Kati Kristiansson, Claes Ladenvall, Mattias Lorentzon, May E Montasser, Omer T Njajou, Paul F O'Reilly, Sandosh Padmanabhan, Beate St Pourcain, Tuomo Rankinen, Perttu Salo, Toshiko Tanaka, Nicholas J Timpson, Veronique Vitart, Lindsay Waite, William Wheeler, Weihua Zhang, Harmen H M Draisma, Mary F Feitosa, Kathleen F Kerr, Penelope A Lind, Evelin Mihailov, N Charlotte Onland-Moret, Ci Song, Michael N Weedon, Weijia Xie, Loïc Yengo, Devin Absher, Christine M Albert, Alvaro Alonso, Dan E Arking, Paul I W de Bakker, Beverley Balkau, Cristina Barlassina, Paola Benaglio, Joshua C Bis, Nabila Bouatia-Naji, Søren Brage, Stephen J Chanock, Peter S Chines, Mina Chung, Dawood Darbar, Christian Dina, Marcus Dörr, Paul Elliott, Stephan B Felix, Krista Fischer, Christian Fuchsberger, Eco J C de Geus, Philippe Goyette, Vilmundur Gudnason, Tamara B Harris, Anna-Liisa Hartikainen, Aki S Havulinna, Susan R Heckbert, Andrew A Hicks, Albert Hofman, Suzanne Holewijn, Femke Hoogstra-Berends, Jouke-Jan Hottenga, Majken K Jensen, Asa Johansson, Juhani Junttila, Stefan Kääb, Bart Kanon, Shamika Ketkar, Kay-Tee Khaw, Joshua W Knowles, Angrad S Kooner, Jan A Kors, Meena Kumari, Lili Milani, Päivi Laiho, Edward G Lakatta, Claudia Langenberg, Maarten Leusink, Yongmei Liu, Robert N Luben, Kathryn L Lunetta, Stacey N Lynch, Marcello R P Markus, Pedro Marques-Vidal, Irene Mateo Leach, Wendy L McArdle, Steven A McCarroll, Sarah E Medland, Kathryn A Miller, Grant W Montgomery, Alanna C Morrison, Martina Müller-Nurasyid, Pau Navarro, Mari Nelis, Jeffrey R O'Connell, Christopher J O'Donnell, Ken K Ong, Anne B Newman, Annette Peters, Ozren Polašek, Anneli Pouta, Peter P Pramstaller, Bruce M Psaty, Dabeeru C Rao, Susan M Ring, Elizabeth J Rossin, Diana Rudan, Serena Sanna, Robert A Scott, Jaban S Sehmi, Stephen Sharp, Jordan T Shin, Andrew B Singleton, Albert V Smith, Nicole Soranzo, Tim D Spector, Chip Stewart, Heather M Stringham, Kirill V Tarasov, André G Uitterlinden, Liesbeth Vandenput, Shih-Jen Hwang, John B Whitfield, Cisca Wijmenga, Sarah H Wild, Gonneke Willemsen, James F Wilson, Jacqueline C M Witteman, Andrew Wong, Quenna Wong, Yalda Jamshidi, Paavo Zitting, Jolanda M A Boer, Dorret I Boomsma, Ingrid B Borecki, Cornelia M van Duijn, Ulf Ekelund, Nita G Forouhi, Philippe Froguel, Aroon Hingorani, Erik Ingelsson, Mika Kivimäki, Richard A Kronmal, Diana Kuh, Lars Lind, Nicholas G Martin, Ben A Oostra, Nancy L Pedersen, Thomas Quertermous, Jerome I Rotter, Yvonne T van der Schouw, W M Monique Verschuren, Mark Walker, Demetrius Albanes, David O Arnar, Themistocles L Assimes, Stefania Bandinelli, Michael Boehnke, Rudolf A de Boer, Claude Bouchard, W L Mark Caulfield, John C Chambers, Gary Curhan, Daniele Cusi, Johan Eriksson, Luigi Ferrucci, Wiek H van Gilst, Nicola Glorioso, Jacqueline de Graaf, Leif Groop, Ulf Gyllensten, Wen-Chi Hsueh, Frank B Hu, Heikki V Huikuri, David J Hunter, Carlos Iribarren, Bo Isomaa, Marjo-Riitta Järvelin, Antti Jula, Mika Kähönen, Lambertus A Kiemeney, Melanie M van der Klauw, Jaspal S Kooner, Peter Kraft, Licia Iacoviello, Terho Lehtimäki, Marja-Liisa L Lokki, Braxton D Mitchell, Gerjan Navis, Markku S Nieminen, Claes Ohlsson, Neil R Poulter, Lu Qi, Olli T Raitakari, Eric B Rimm, John D Rioux, Federica Rizzi, Igor Rudan, Veikko Salomaa, Peter S Sever, Denis C Shields, Alan R Shuldiner, Juha Sinisalo, Alice V Stanton, Ronald P Stolk, David P Strachan, Jean-Claude Tardif, Unnur Thorsteinsdottir, Jaako Tuomilehto, Dirk J van Veldhuisen, Jarmo Virtamo, Jorma Viikari, Peter Vollenweider, Gérard Waeber, Elisabeth Widén, Yoon Shin Cho, Jesper V Olsen, Peter M Visscher, Cristen Willer, Lude Franke, , Jeanette Erdmann, John R Thompson, Arne Pfeufer, Nona Sotoodehnia, Christopher Newton-Cheh, Patrick T Ellinor, Bruno H Ch Stricker, Andres Metspalu, Markus Perola, Jacques S Beckmann, George Davey Smith, Kari Stefansson, Nicholas J Wareham, Patricia B Munroe, Ody C M Sibon, David J Milan, Harold Snieder, Nilesh J Samani, Ruth J F Loos.
Nat. Genet.
PUBLISHED: 03-21-2013
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Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
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PeptideLocator: prediction of bioactive peptides in protein sequences.
Bioinformatics
PUBLISHED: 03-16-2013
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Peptides play important roles in signalling, regulation and immunity within an organism. Many have successfully been used as therapeutic products often mimicking naturally occurring peptides. Here we present PeptideLocator for the automated prediction of functional peptides in a protein sequence.
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A genome-wide association study of recipient genotype and medium-term kidney allograft function.
Clin Transplant
PUBLISHED: 02-21-2013
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We examined, through genome-wide association studies (GWAS), the correlation between recipient genetic variation and renal function at five yr.
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Inhibition of dipeptidyl peptidase IV and xanthine oxidase by amino acids and dipeptides.
Food Chem
PUBLISHED: 01-11-2013
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Xanthine oxidase (XO) and dipeptidyl peptidase IV (DPP-IV) inhibition by amino acids and dipeptides was studied. Trp and Trp-containing dipeptides (Arg-Trp, Trp-Val, Val-Trp, Lys-Trp and Ile-Trp) inhibited XO. Three amino acids (Met, Leu and Trp) and eight dipeptides (Phe-Leu, Trp-Val, His-Leu, Glu-Lys, Ala-Leu, Val-Ala, Ser-Leu and Gly-Leu) inhibited DPP-IV. Trp and Trp-Val were multifunctional inhibitors of XO and DPP-IV. Lineweaver and Burk analysis showed that Trp was a non-competitive inhibitor of XO and a competitive inhibitor of DPP-IV. Molecular docking with Autodock Vina was used to better understand the interaction of the peptides with the active site of the enzyme. Because of the non-competitive inhibition observed, docking of Trp-Val to the secondary binding sites of XO and DPP-IV is required. Trp-Val was predicted to be intestinally neutral (between 25% and 75% peptide remaining after 60 min simulated intestinal digestion). These results are of significance for the reduction of reactive oxygen species (ROS) and the increase of the half-life of incretins by food-derived peptides.
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Predicting binding within disordered protein regions to structurally characterised peptide-binding domains.
PLoS ONE
PUBLISHED: 01-01-2013
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Disordered regions of proteins often bind to structured domains, mediating interactions within and between proteins. However, it is difficult to identify a priori the short disordered regions involved in binding. We set out to determine if docking such peptide regions to peptide binding domains would assist in these predictions.We assembled a redundancy reduced dataset of SLiM (Short Linear Motif) containing proteins from the ELM database. We selected 84 sequences which had an associated PDB structures showing the SLiM bound to a protein receptor, where the SLiM was found within a 50 residue region of the protein sequence which was predicted to be disordered. First, we investigated the Vina docking scores of overlapping tripeptides from the 50 residue SLiM containing disordered regions of the protein sequence to the corresponding PDB domain. We found only weak discrimination of docking scores between peptides involved in binding and adjacent non-binding peptides in this context (AUC 0.58).Next, we trained a bidirectional recurrent neural network (BRNN) using as input the protein sequence, predicted secondary structure, Vina docking score and predicted disorder score. The results were very promising (AUC 0.72) showing that multiple sources of information can be combined to produce results which are clearly superior to any single source.We conclude that the Vina docking score alone has only modest power to define the location of a peptide within a larger protein region known to contain it. However, combining this information with other knowledge (using machine learning methods) clearly improves the identification of peptide binding regions within a protein sequence. This approach combining docking with machine learning is primarily a predictor of binding to peptide-binding sites, and is not intended as a predictor of specificity of binding to particular receptors.
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Marked variability in the extent of protein disorder within and between viral families.
PLoS ONE
PUBLISHED: 01-01-2013
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Intrinsically disordered regions in eukaryotic proteomes contain key signaling and regulatory modules and mediate interactions with many proteins. Many viral proteomes encode disordered proteins and modulate host factors through the use of short linear motifs (SLiMs) embedded within disordered regions. However, the degree of viral protein disorder across different viruses is not well understood, so we set out to establish the constraints acting on viruses, in terms of their use of disordered protein regions. We surveyed predicted disorder across 2,278 available viral genomes in 41 families, and correlated the extent of disorder with genome size and other factors. Protein disorder varies strikingly between viral families (from 2.9% to 23.1% of residues), and also within families. However, this substantial variation did not follow the established trend among their hosts, with increasing disorder seen across eubacterial, archaebacterial, protists, and multicellular eukaryotes. For example, among large mammalian viruses, poxviruses and herpesviruses showed markedly differing disorder (5.6% and 17.9%, respectively). Viral families with smaller genome sizes have more disorder within each of five main viral types (ssDNA, dsDNA, ssRNA+, dsRNA, retroviruses), except for negative single-stranded RNA viruses, where disorder increased with genome size. However, surveying over all viruses, which compares tiny and enormous viruses over a much bigger range of genome sizes, there is no strong association of genome size with protein disorder. We conclude that there is extensive variation in the disorder content of viral proteomes. While a proportion of this may relate to base composition, to extent of gene overlap, and to genome size within viral types, there remain important additional family and virus-specific effects. Differing disorder strategies are likely to impact on how different viruses modulate host factors, and on how rapidly viruses can evolve novel instances of SLiMs subverting host functions, such as innate and acquired immunity.
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Platelet signalling networks: pathway perturbation demonstrates differential sensitivity of ADP secretion and fibrinogen binding.
Platelets
PUBLISHED: 11-30-2011
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Platelet signalling responses to single agonists have been identified previously. However, a model of the total platelet signalling network is still lacking. In order to gain insights into this network, we explored the effects of a range of platelet-function inhibitors in two independent assays of platelet function, namely fibrinogen binding and ADP secretion. In this study, we targeted the intracellular signalling molecules targeted intracellular signalling molecules, Syk and PI3K and targeted intracellular signalling molecules, Syk and PI3K, the prostaglandin synthesis enzyme cyclooxygenase, surface receptors for TxA(2) and ADP (P2Y1 and P2Y12) and the integrin cell adhesion molecule, ?IIb?3. We demonstrate that the platelet responses of fibrinogen binding and secretion can be differentially affected by the individual inhibitors permitting the generation of a model delineating novel regulatory links in the platelet signalling network. Importantly, the model illustrates the interconnections among portions that are traditionally studied as separate modules, promoting a more integrated view of the platelet.
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Correlation of disorder between S. cerevisiae interacting proteins.
Mol Biosyst
PUBLISHED: 11-23-2011
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Protein disorder has been frequently associated with protein-protein interaction. However, our knowledge of how protein disorder evolves within a network is limited. It is expected that physically interacting proteins evolve in a coordinated manner. This has so far been shown in their evolutionary rate, and in their gene expression levels. Here we examine the percentage of predicted disorder residues within binary and complex interacting proteins (physical and functional interactions respectively) to investigate how the disorder of a protein relates to that of its interacting partners. We show that the level of disorder of interacting proteins are correlated, with a greater correlation seen among proteins that are co-members of the same complex, and a lesser correlation between proteins that are documented as binary interactors of each other. There is a striking variation among complexes not only in their disorder, but in the extent to which the proteins within the complex differ in their levels of disorder, with RNA processes and protein binding complexes showing more variation in the disorder of their proteins, whilst other complexes show very little variation in the overall disorder of their constituent proteins. There is likely to be a stronger selection for complex subunits to have similar disorder, than is seen for proteins involved in binary interactions. Thus, binary interactions may be more resilient to changes in disorder than are complex interactions. These results add a new dimension to the role of disorder in protein networks, and highlight the potential importance of maintaining similar disorder in the members of a complex.
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Interactome-wide prediction of short, disordered protein interaction motifs in humans.
Mol Biosyst
PUBLISHED: 08-30-2011
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Many of the specific functions of intrinsically disordered protein segments are mediated by Short Linear Motifs (SLiMs) interacting with other proteins. Well known examples include SLiMs that interact with 14-3-3, PDZ, SH2, SH3, and WW domains but the true extent and diversity of SLiM-mediated interactions is largely unknown. Here, we attempt to expand our knowledge of human SLiMs by applying in silico SLiM prediction to the human interactome. Combining data from seven different interaction databases, we analysed approximately 6000 protein-centred and 1600 domain-centred human interaction datasets of 3+ unrelated proteins that interact with a common partner. Results were placed in context through comparison to randomised datasets of similar size and composition. The search returned thousands of evolutionarily conserved, intrinsically disordered occurrences of hundreds of significantly enriched recurring motifs, including many that have never been previously identified (). In addition to True Positive results for at least 25 different known SLiMs, a striking number of "off-target" proteins/domains also returned significantly enriched known motifs. Often, this was due to the non-independence of the datasets, with many proteins sharing interaction partners or contributing interactions to multiple domain datasets. The majority of these motif classes, however, were also found to be significantly enriched in one or more randomised datasets. This highlights the need for care when interpreting motif predictions of this nature but also raises the possibility that SLiM occurrences may be successfully identified independently of interaction data. Although not as compositionally biased as previous studies, patterns matching known SLiMs tended to cluster into a few large groups of similar sequence, while novel predictions tended to be more distinctive and less abundant. Whether this is due to ascertainment bias or a true functional composition bias of SLiMs is not clear and warrants further investigation.
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Shift in the isoelectric-point of milk proteins as a consequence of adaptive divergence between the milks of mammalian species.
Biol. Direct
PUBLISHED: 07-29-2011
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Milk proteins are required to proceed through a variety of conditions of radically varying pH, which are not identical across mammalian digestive systems. We wished to investigate if the shifts in these requirements have resulted in marked changes in the isoelectric point and charge of milk proteins during evolution.
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In silico protein motif discovery and structural analysis.
Methods Mol. Biol.
PUBLISHED: 07-23-2011
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A wealth of in silico tools is available for protein motif discovery and structural analysis. The aim of this chapter is to collect some of the most common and useful tools and to guide the biologist in their use. A detailed explanation is provided for the use of Distill, a suite of web servers for the prediction of protein structural features and the prediction of full-atom 3D models from a protein sequence. Besides this, we also provide pointers to many other tools available for motif discovery and secondary and tertiary structure prediction from a primary amino acid sequence. The prediction of protein intrinsic disorder and the prediction of functional sites and SLiMs are also briefly discussed. Given that user queries vary greatly in size, scope and character, the trade-offs in speed, accuracy and scale need to be considered when choosing which methods to adopt.
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Prediction of short linear protein binding regions.
J. Mol. Biol.
PUBLISHED: 06-20-2011
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Short linear motifs in proteins (typically 3-12 residues in length) play key roles in protein-protein interactions by frequently binding specifically to peptide binding domains within interacting proteins. Their tendency to be found in disordered segments of proteins has meant that they have often been overlooked. Here we present SLiMPred (short linear motif predictor), the first general de novo method designed to computationally predict such regions in protein primary sequences independent of experimentally defined homologs and interactors. The method applies machine learning techniques to predict new motifs based on annotated instances from the Eukaryotic Linear Motif database, as well as structural, biophysical, and biochemical features derived from the protein primary sequence. We have integrated these data sources and benchmarked the predictive accuracy of the method, and found that it performs equivalently to a predictor of protein binding regions in disordered regions, in addition to having predictive power for other classes of motif sites such as polyproline II helix motifs and short linear motifs lying in ordered regions. It will be useful in predicting peptides involved in potential protein associations and will aid in the functional characterization of proteins, especially of proteins lacking experimental information on structures and interactions. We conclude that, despite the diversity of motif sequences and structures, SLiMPred is a valuable tool for prioritizing potential interaction motifs in proteins.
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Blood pressure loci identified with a gene-centric array.
Toby Johnson, Tom R Gaunt, Stephen J Newhouse, Sandosh Padmanabhan, Maciej Tomaszewski, Meena Kumari, Richard W Morris, Ioanna Tzoulaki, Eoin T O'Brien, Neil R Poulter, Peter Sever, Denis C Shields, Simon Thom, Sasiwarang G Wannamethee, Peter H Whincup, Morris J Brown, John M Connell, Richard J Dobson, Philip J Howard, Charles A Mein, Abiodun Onipinla, Sue Shaw-Hawkins, Yun Zhang, George Davey Smith, Ian N M Day, Debbie A Lawlor, Alison H Goodall, , F Gerald Fowkes, Gonçalo R Abecasis, Paul Elliott, Vesela Gateva, Peter S Braund, Paul R Burton, Christopher P Nelson, Martin D Tobin, Pim van der Harst, Nicola Glorioso, Hani Neuvrith, Erika Salvi, Jan A Staessen, Andrea Stucchi, Nabila Devos, Xavier Jeunemaitre, Pierre-Francois Plouin, Jean Tichet, Peeter Juhanson, Elin Org, Margus Putku, Siim Sõber, Gudrun Veldre, Margus Viigimaa, Anna Levinsson, Annika Rosengren, Dag S Thelle, Claire E Hastie, Thomas Hedner, Wai K Lee, Olle Melander, Björn Wahlstrand, Rebecca Hardy, Andrew Wong, Jackie A Cooper, Jutta Palmen, Li Chen, Alexandre F R Stewart, George A Wells, Harm-Jan Westra, Marcel G M Wolfs, Robert Clarke, Maria Grazia Franzosi, Anuj Goel, Anders Hamsten, Mark Lathrop, John F Peden, Udo Seedorf, Hugh Watkins, Willem H Ouwehand, Jennifer Sambrook, Jonathan Stephens, Juan-Pablo Casas, Fotios Drenos, Michael V Holmes, Mika Kivimäki, Sonia Shah, Tina Shah, Philippa J Talmud, John Whittaker, Chris Wallace, Christian Delles, Maris Laan, Diana Kuh, Steve E Humphries, Fredrik Nyberg, Daniele Cusi, Robert Roberts, Christopher Newton-Cheh, Lude Franke, Alice V Stanton, Anna F Dominiczak, Martin Farrall, Aroon D Hingorani, Nilesh J Samani, Mark J Caulfield, Patricia B Munroe.
Am. J. Hum. Genet.
PUBLISHED: 06-15-2011
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Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.
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SLiMSearch 2.0: biological context for short linear motifs in proteins.
Nucleic Acids Res.
PUBLISHED: 05-26-2011
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Short, linear motifs (SLiMs) play a critical role in many biological processes. The SLiMSearch 2.0 (Short, Linear Motif Search) web server allows researchers to identify occurrences of a user-defined SLiM in a proteome, using conservation and protein disorder context statistics to rank occurrences. User-friendly output and visualizations of motif context allow the user to quickly gain insight into the validity of a putatively functional motif occurrence. For each motif occurrence, overlapping UniProt features and annotated SLiMs are displayed. Visualization also includes annotated multiple sequence alignments surrounding each occurrence, showing conservation and protein disorder statistics in addition to known and predicted SLiMs, protein domains and known post-translational modifications. In addition, enrichment of Gene Ontology terms and protein interaction partners are provided as indicators of possible motif function. All web server results are available for download. Users can search motifs against the human proteome or a subset thereof defined by Uniprot accession numbers or GO term. The SLiMSearch server is available at: http://bioware.ucd.ie/slimsearch2.html.
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Differences in the number of intrinsically disordered regions between yeast duplicated proteins, and their relationship with functional divergence.
PLoS ONE
PUBLISHED: 05-24-2011
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Intrinsically disordered regions are enriched in short interaction motifs that play a critical role in many protein-protein interactions. Since new short interaction motifs may easily evolve, they have the potential to rapidly change protein interactions and cellular signaling. In this work we examined the dynamics of gain and loss of intrinsically disordered regions in duplicated proteins to inspect if changes after genome duplication can create functional divergence. For this purpose we used Saccharomyces cerevisiae and the outgroup species Lachancea kluyveri.
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A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder.
Jillian P Casey, Tiago Magalhaes, Judith M Conroy, Regina Regan, Naisha Shah, Richard Anney, Denis C Shields, Brett S Abrahams, Joana Almeida, Elena Bacchelli, Anthony J Bailey, Gillian Baird, Agatino Battaglia, Tom Berney, Nadia Bolshakova, Patrick F Bolton, Thomas Bourgeron, Sean Brennan, Phil Cali, Catarina Correia, Christina Corsello, Marc Coutanche, Geraldine Dawson, Maretha de Jonge, Richard Delorme, Eftichia Duketis, Frederico Duque, Annette Estes, Penny Farrar, Bridget A Fernandez, Susan E Folstein, Suzanne Foley, Eric Fombonne, Christine M Freitag, John Gilbert, Christopher Gillberg, Joseph T Glessner, Jonathan Green, Stephen J Guter, Hakon Hakonarson, Richard Holt, Gillian Hughes, Vanessa Hus, Roberta Igliozzi, Cecilia Kim, Sabine M Klauck, Alexander Kolevzon, Janine A Lamb, Marion Leboyer, Ann Le Couteur, Bennett L Leventhal, Catherine Lord, Sabata C Lund, Elena Maestrini, Carine Mantoulan, Christian R Marshall, Helen McConachie, Christopher J McDougle, Jane McGrath, William M McMahon, Alison Merikangas, Judith Miller, Fiorella Minopoli, Ghazala K Mirza, Jeff Munson, Stanley F Nelson, Gudrun Nygren, Guiomar Oliveira, Alistair T Pagnamenta, Katerina Papanikolaou, Jeremy R Parr, Barbara Parrini, Andrew Pickles, Dalila Pinto, Joseph Piven, David J Posey, Annemarie Poustka, Fritz Poustka, Jiannis Ragoussis, Bernadette Rogé, Michael L Rutter, Ana F Sequeira, Latha Soorya, Inês Sousa, Nuala Sykes, Vera Stoppioni, Raffaella Tancredi, Maïté Tauber, Ann P Thompson, Susanne Thomson, John Tsiantis, Herman van Engeland, John B Vincent, Fred Volkmar, Jacob A S Vorstman, Simon Wallace, Kai Wang, Thomas H Wassink, Kathy White, Kirsty Wing, Kerstin Wittemeyer, Brian L Yaspan, Lonnie Zwaigenbaum, Catalina Betancur, Joseph D Buxbaum, Rita M Cantor, Edwin H Cook, Hilary Coon, Michael L Cuccaro, Daniel H Geschwind, Jonathan L Haines, Joachim Hallmayer, Anthony P Monaco, John I Nurnberger, Margaret A Pericak-Vance, Gerard D Schellenberg, Stephen W Scherer, James S Sutcliffe, Peter Szatmari, Veronica J Vieland, Ellen M Wijsman, Andrew Green, Michael Gill, Louise Gallagher, Astrid Vicente, Sean Ennis.
Hum. Genet.
PUBLISHED: 05-12-2011
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Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
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A polymorphism in ACE2 is associated with a lower risk for fatal cardiovascular events in females: the MORGAM project.
J Renin Angiotensin Aldosterone Syst
PUBLISHED: 04-13-2011
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Angiotensin II, a vasoconstrictor and the main effector molecule of the renin-angiotensin system, is known to influence inflammation, thrombosis, low-density lipoprotein oxidation and growth factors, all of which contribute to cardiovascular disease. The associations of polymorphisms in the angiotensin-converting enzyme 2 (ACE2) gene with cardiovascular risk have not been fully determined. Single nucleotide polymorphisms (SNPs) in ACE2 were genotyped in participants of the prospective MORGAM study (n = 5092) from five cohorts: ATBC, FINRISK, Northern Sweden, PRIME/Belfast and PRIME/France. Using a case-cohort design, associations were sought between SNPs and haplotypes with cardiovascular events during follow-up (Cox proportional hazards model). The comparison group were a subset of all MORGAM participants who were selected to ensure similar age and sex distributions among the cases and controls. The A allele of the rs2285666 SNP (HR = 0.3, p = 0.04) was significantly associated with the risk of cardiovascular death in female subjects. These findings complement those found in other studies of SNPs in the ACE2 gene in relation to cardiovascular disease risk. As females carry two copies of the ACE2 gene, and given its plausible biological role in cardiovascular disease risk, further studies of ACE2 should be prioritized.
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CycloPs: generating virtual libraries of cyclized and constrained peptides including nonnatural amino acids.
J Chem Inf Model
PUBLISHED: 03-24-2011
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We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie .
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Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs.
BMC Syst Biol
PUBLISHED: 03-20-2011
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Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks.
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Evolution of the isoelectric point of mammalian proteins as a consequence of indels and adaptive evolution.
Proteins
PUBLISHED: 01-04-2011
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Although important shifts in the isoelectric point of prokaryotic proteins, mainly due to adaptation to environmental pH, have been widely reported, such studies have not covered mammalian proteins, where pH changes may relate to changes in subcellular or tissue compartmentalization. We explored the isoelectric point of the proteome of 13 mammalian species. We detected proteins that have shifted their pI the most among 13 mammalian species, and investigated if these differences reflect adaptations of the orthologous proteins to different conditions. We find that proteins exhibiting a high isoelectric point change are enriched in certain GO terms, including immune defense, and mitochondrial proteins. We show that the shift in pI between orthologous proteins is not strongly associated with the overall rate of protein evolution, nor with protein length. Our results reveal that insertions/deletions are the main reason behind the shift of pI. However, for some proteins we find evidence of selection shifting the pI of the protein through amino acid replacement. Finally, we argue that shifts in pI might relate to the gain of additional activities, such as new interacting partners, in one ortholog as opposed to the other, and may potentially relate to functional differences between mammals.
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Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height.
Matthew B Lanktree, Yiran Guo, Muhammed Murtaza, Joseph T Glessner, Swneke D Bailey, N Charlotte Onland-Moret, Guillaume Lettre, Halit Ongen, Ramakrishnan Rajagopalan, Toby Johnson, Haiqing Shen, Christopher P Nelson, Norman Klopp, Jens Baumert, Sandosh Padmanabhan, Nathan Pankratz, James S Pankow, Sonia Shah, Kira Taylor, John Barnard, Bas J Peters, Cliona M Maloney, Maximilian T Lobmeyer, Alice Stanton, M Hadi Zafarmand, Simon P R Romaine, Amar Mehta, Erik P A van Iperen, Yan Gong, Tom S Price, Erin N Smith, Cecilia E Kim, Yun R Li, Folkert W Asselbergs, Larry D Atwood, Kristian M Bailey, Deepak Bhatt, Florianne Bauer, Elijah R Behr, Tushar Bhangale, Jolanda M A Boer, Bernhard O Boehm, Jonathan P Bradfield, Morris Brown, Peter S Braund, Paul R Burton, Cara Carty, Hareesh R Chandrupatla, Wei Chen, John Connell, Chrysoula Dalgeorgou, Anthonius de Boer, Fotios Drenos, Clara C Elbers, James C Fang, Caroline S Fox, Edward C Frackelton, Barry Fuchs, Clement E Furlong, Quince Gibson, Christian Gieger, Anuj Goel, Diederik E Grobbee, Claire Hastie, Philip J Howard, Guan-Hua Huang, W Craig Johnson, Qing Li, Marcus E Kleber, Barbara E K Klein, Ronald Klein, Charles Kooperberg, Bonnie Ky, Andrea LaCroix, Paul Lanken, Mark Lathrop, Mingyao Li, Vanessa Marshall, Olle Melander, Frank D Mentch, Nuala J Meyer, Keri L Monda, Alexandre Montpetit, Gurunathan Murugesan, Karen Nakayama, Dave Nondahl, Abiodun Onipinla, Suzanne Rafelt, Stephen J Newhouse, F George Otieno, Sanjey R Patel, Mary E Putt, Santiago Rodriguez, Radwan N Safa, Douglas B Sawyer, Pamela J Schreiner, Claire Simpson, Suthesh Sivapalaratnam, Sathanur R Srinivasan, Christine Suver, Gary Swergold, Nancy K Sweitzer, Kelly A Thomas, Barbara Thorand, Nicholas J Timpson, Sam Tischfield, Martin Tobin, Maciej Tomaszewski, Maciej Tomaszweski, W M Monique Verschuren, Chris Wallace, Bernhard Winkelmann, Haitao Zhang, Dongling Zheng, Li Zhang, Joseph M Zmuda, Robert Clarke, Anthony J Balmforth, John Danesh, Ian N Day, Nicholas J Schork, Paul I W de Bakker, Christian Delles, David Duggan, Aroon D Hingorani, Joel N Hirschhorn, Marten H Hofker, Steve E Humphries, Mika Kivimäki, Debbie A Lawlor, Kandice Kottke-Marchant, Jessica L Mega, Braxton D Mitchell, David A Morrow, Jutta Palmen, Susan Redline, Denis C Shields, Alan R Shuldiner, Patrick M Sleiman, George Davey Smith, Martin Farrall, Yalda Jamshidi, David C Christiani, Juan P Casas, Alistair S Hall, Pieter A Doevendans, Jason D Christie, Gerald S Berenson, Sarah S Murray, Thomas Illig, Gerald W Dorn, Thomas P Cappola, Eric Boerwinkle, Peter Sever, Daniel J Rader, Muredach P Reilly, Mark Caulfield, Philippa J Talmud, Eric Topol, James C Engert, Kai Wang, Anna Dominiczak, Anders Hamsten, Sean P Curtis, Roy L Silverstein, Leslie A Lange, Marc S Sabatine, Mieke Trip, Danish Saleheen, John F Peden, Karen J Cruickshanks, Winfried März, Jeffrey R O'Connell, Olaf H Klungel, Cisca Wijmenga, Anke Hilse Maitland-van der Zee, Eric E Schadt, Julie A Johnson, Gail P Jarvik, George J Papanicolaou, , Struan F A Grant, Patricia B Munroe, Kari E North, Nilesh J Samani, Wolfgang Koenig, Tom R Gaunt, Sonia S Anand, Yvonne T van der Schouw, Nicole Soranzo, Garret A FitzGerald, Alex Reiner, Robert A Hegele, Hakon Hakonarson, Brendan J Keating.
Am. J. Hum. Genet.
PUBLISHED: 09-14-2010
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Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.
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Computational identification and analysis of protein short linear motifs.
Front Biosci (Landmark Ed)
PUBLISHED: 06-03-2010
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Short linear motifs (SLiMs) in proteins can act as targets for proteolytic cleavage, sites of post-translational modification, determinants of sub-cellular localization, and mediators of protein-protein interactions. Computational discovery of SLiMs involves assembling a group of proteins postulated to share a potential motif, masking out residues less likely to contain such a motif, down-weighting shared motifs arising through common evolutionary descent, and calculation of statistical probabilities allowing for the multiple testing of all possible motifs. Much of the challenge for motif discovery lies in the assembly and masking of datasets of proteins likely to share motifs, since the motifs are typically short (between 3 and 10 amino acids in length), so that potential signals can be easily swamped by the noise of stochastically recurring motifs. Focusing on disordered regions of proteins, where SLiMs are predominantly found, and masking out non-conserved residues can reduce the level of noise but more work is required to improve the quality of high-throughput experimental datasets (e.g. of physical protein interactions) as input for computational discovery.
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Genome-wide association study of blood pressure extremes identifies variant near UMOD associated with hypertension.
PLoS Genet.
PUBLISHED: 05-25-2010
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Hypertension is a heritable and major contributor to the global burden of disease. The sum of rare and common genetic variants robustly identified so far explain only 1%-2% of the population variation in BP and hypertension. This suggests the existence of more undiscovered common variants. We conducted a genome-wide association study in 1,621 hypertensive cases and 1,699 controls and follow-up validation analyses in 19,845 cases and 16,541 controls using an extreme case-control design. We identified a locus on chromosome 16 in the 5 region of Uromodulin (UMOD; rs13333226, combined P value of 3.6 × 10?¹¹). The minor G allele is associated with a lower risk of hypertension (OR [95%CI]: 0.87 [0.84-0.91]), reduced urinary uromodulin excretion, better renal function; and each copy of the G allele is associated with a 7.7% reduction in risk of CVD events after adjusting for age, sex, BMI, and smoking status (H.R.?=?0.923, 95% CI 0.860-0.991; p?=?0.027). In a subset of 13,446 individuals with estimated glomerular filtration rate (eGFR) measurements, we show that rs13333226 is independently associated with hypertension (unadjusted for eGFR: 0.89 [0.83-0.96], p?=?0.004; after eGFR adjustment: 0.89 [0.83-0.96], p?=?0.003). In clinical functional studies, we also consistently show the minor G allele is associated with lower urinary uromodulin excretion. The exclusive expression of uromodulin in the thick portion of the ascending limb of Henle suggests a putative role of this variant in hypertension through an effect on sodium homeostasis. The newly discovered UMOD locus for hypertension has the potential to give new insights into the role of uromodulin in BP regulation and to identify novel drugable targets for reducing cardiovascular risk.
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SLiMFinder: a web server to find novel, significantly over-represented, short protein motifs.
Nucleic Acids Res.
PUBLISHED: 05-23-2010
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Short, linear motifs (SLiMs) play a critical role in many biological processes, particularly in protein-protein interactions. The Short, Linear Motif Finder (SLiMFinder) web server is a de novo motif discovery tool that identifies statistically over-represented motifs in a set of protein sequences, accounting for the evolutionary relationships between them. Motifs are returned with an intuitive P-value that greatly reduces the problem of false positives and is accessible to biologists of all disciplines. Input can be uploaded by the user or extracted directly from UniProt. Numerous masking options give the user great control over the contextual information to be included in the analyses. The SLiMFinder server combines these with user-friendly output and visualizations of motif context to allow the user to quickly gain insight into the validity of a putatively functional motif. These visualizations include alignments of motif occurrences, alignments of motifs and their homologues and a visual schematic of the top-ranked motifs. Returned motifs can also be compared with known SLiMs from the literature using CompariMotif. All results are available for download. The SLiMFinder server is available at: http://bioware.ucd.ie/slimfinder.html.
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Meta-analysis to test the association of HIV-1 nef amino acid differences and deletions with disease progression.
J. Virol.
PUBLISHED: 01-13-2010
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Previous relatively small studies have associated particular amino acid replacements and deletions in the HIV-1 nef gene with differences in the rate of HIV disease progression. We tested more rigorously whether particular nef amino acid differences and deletions are associated with HIV disease progression. Amino acid replacements and deletions in patients consensus sequences were investigated for 153 progressor (P), 615 long-term nonprogressor (LTNP), and 2,311 unknown progressor sequences from 582 subtype B HIV-infected patients. LTNPs had more defective nefs (interrupted by frameshifts or stop codons), but on a per-patient basis there was no excess of LTNP patients with one or more defective nef sequences compared to the Ps (P = 0.47). The high frequency of amino acid replacement at residues S(8), V(10), I(11), A(15), V(85), V(133), N(157), S(163), V(168), D(174), R(178), E(182), and R(188) in LTNPs was also seen in permuted datasets, implying that these are simply rapidly evolving residues. Permutation testing revealed that residues showing the greatest excess over expectation (A(15), V(85), N(157), S(163), V(168), D(174), R(178), and R(188)) were not significant (P = 0.77). Exploratory analysis suggested a hypothetical excess of frameshifting in the regions (9)SVIG and (118)QGYF among LTNPs. The regions V(10) and (152)KVEEA of nef were commonly deleted in LTNPs. However, permutation testing indicated that none of the regions displayed significantly excessive deletion in LTNPs. In conclusion, meta-analysis of HIV-1 nef sequences provides no clear evidence of whether defective nef sequences or particular regions of the protein play a significant role in disease progression.
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Estimation and efficient computation of the true probability of recurrence of short linear protein sequence motifs in unrelated proteins.
BMC Bioinformatics
PUBLISHED: 01-07-2010
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Large datasets of protein interactions provide a rich resource for the discovery of Short Linear Motifs (SLiMs) that recur in unrelated proteins. However, existing methods for estimating the probability of motif recurrence may be biased by the size and composition of the search dataset, such that p-value estimates from different datasets, or from motifs containing different numbers of non-wildcard positions, are not strictly comparable. Here, we develop more exact methods and explore the potential biases of computationally efficient approximations.
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Discovery of small molecule inhibitors of protein-protein interactions using combined ligand and target score normalization.
J Chem Inf Model
PUBLISHED: 12-10-2009
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Docking experiments of multiple compounds typically focus on a single protein. However, other targets provide information about relative binding efficiencies that is otherwise lacking. We developed a docking strategy that normalized results in both the ligand and target dimensions. This was applied to dock 287 approved small drugs with 35 peptide-binding proteins, including 15 true positives. The combined docking score was normalized by drug and protein and by incorporating information on contact similarity to the template protein-peptide contacts. The 20 top ranking hits included 6 true positives, and three matches with suggestive evidence in the literature: the cardiac glycoside digitoxin may inhibit WW domain interactions, the 14-3-3 zeta protein may bind negatively charged ligands, and the nuclear receptor coactivator site may bind nuclear receptor agonists. Additionally, the Bcl-2 antiapoptotic protein is predicted to bind pargyline, and the antiapoptic p53 interacting protein MDM2 is suggested to bind clofazimine. These predictions represent starting points for the experimental development of PPI inhibitors based on an existing database of approved drugs and demonstrate that two-dimensional normalization improves docking efficiency.
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Insider access: pepducin symposium explores a new approach to GPCR modulation.
Ann. N. Y. Acad. Sci.
PUBLISHED: 11-21-2009
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The inaugural Pepducin Science Symposium convened in Cambridge, Massachusetts on March 8-9, 2009 provided the opportunity for an international group of distinguished scientists to present and discuss research regarding G protein-coupled receptor-related research. G protein-coupled receptors (GPCRs) are, arguably, one of the most important molecular targets in drug discovery and pharmaceutical development today. This superfamily of membrane receptors is central to nearly every signaling pathway in the human body and has been the focus of intense research for decades. However, as scientists discover additional properties of GPCRs, it has become clear that much is yet to be understood about how these receptors function. Everyone agrees, however, that tremendous potential remains if specific GPCR signaling pathways can be modulated to correct pathological states. One exciting new approach to this challenge involves pepducins: novel, synthetic lipopeptide pharmacophores that modulate heptahelical GPCR activity from inside the cell membrane.
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Gene-centric association signals for lipids and apolipoproteins identified via the HumanCVD BeadChip.
Am. J. Hum. Genet.
PUBLISHED: 07-23-2009
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Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n=5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p<10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HMGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZ1B, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p<10(-4) in Whitehall II, in silico analysis including the British Womens Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n>12,500) revealed previously unreported associations of SH2B3 (p<2.2x10(-6)), BMPR2 (p<2.3x10(-7)), BCL3/PVRL2 (flanking APOE; p<4.4x10(-8)), and SMARCA4 (flanking LDLR; p<2.5x10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., >1 mmol/L in LDL cholesterol [approximately 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically.
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Ligand switching in cell-permeable peptides: manipulation of the alpha-integrin signature motif.
ACS Chem. Biol.
PUBLISHED: 04-18-2009
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A synthetic cell-permeable peptide corresponding to the highly conserved alpha-integrin signature motif, Palmityl-K(989)VGFFKR(995) (Pal-FF), induces integrin activation and aggregation in human platelets. Systematic replacement of the F(992)-F(993) with amino acids of greater or lesser hydrophobicity to create Pal-KVGxxKR peptides demonstrate that hydrophobic amino acids (isoleucine, phenylalanine, tyrosine, tryptophan) are essential for agonist potency. In marked contrast, substitution with small and/or hydrophilic amino acids (glycine, alanine, serine) causes a switch in the biological activity resulting in inhibition of platelet aggregation, adhesion, ADP secretion, and thromboxane synthesis. These substituted, hydrophilic peptides are not true pharmacological antagonists, as they actively induce a phosphotyrosine signaling cascade in platelets. Singly substituted peptides (Pal-AF and Pal-FA) cause preferential retention of pro- or anti-thrombotic properties, respectively. Because the alpha-integrin signature motif is an established docking site for a number of diverse cytoplasmic proteins, we conclude that eliminating critical protein-protein interactions mediated through the hydrophobic amino acids, especially F(993), favors an anti-thrombotic pathway in platelets. Agents derived from the inhibitory peptides described in this study may represent a new therapeutic strategy for anti-platelet or anti-integrin drug development.
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Masking residues using context-specific evolutionary conservation significantly improves short linear motif discovery.
Bioinformatics
PUBLISHED: 01-09-2009
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Short linear motifs (SLiMs) are important mediators of protein-protein interactions. Their short and degenerate nature presents a challenge for computational discovery. We sought to improve SLiM discovery by incorporating evolutionary information, since SLiMs are more conserved than surrounding residues.
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EnzymePredictor: a tool for predicting and visualizing enzymatic cleavages of digested proteins.
J. Proteome Res.
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Mass spectrometric analysis of peptides contained in enzymatically digested hydrolysates of proteins is increasingly being used to characterize potentially bioactive or otherwise interesting hydrolysates. However, when preparations containing mixtures of enzymes are used, from either biological or experimental sources, it is unclear which of these enzymes have been most important in hydrolyzing the sample. We have developed a tool to rapidly evaluate the evidence for which enzymes are most likely to have cleaved the sample. EnzymePredictor, a web-based software, has been developed to (i) identify the protein sources of fragments found in the hydrolysates and map them back on it, (ii) identify enzymes that could yield such cleavages, and (iii) generate a colored visualization of the hydrolysate, the source proteins, the fragments, and the predicted enzymes. It tabulates the enzymes ranked according to their cleavage counts. The provision of odds ratio and standard error in the table permits users to evaluate how distinctively particular enzymes may be favored over other enzymes as the most likely cleavers of the samples. Finally, the method displays the cleavage not only according to peptides, but also according to proteins, permitting evaluation of whether the cleavage pattern is general across all proteins, or specific to a subset. We illustrate the application of this method using milk hydrolysates, and show how it can rapidly identify the enzymes or enzyme combinations used in generating the peptides. The approach developed here will accelerate the identification of enzymes most likely to have been used in hydrolyzing a set of mass spectrometrically identified peptides derived from proteins. This has utility not only in understanding the results of mass spectrometry experiments, but also in choosing enzymes likely to yield similar cleavage patterns. EnzymePredictor can be found at http://bioware.ucd.ie/?enzpred/Enzpred.php.
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Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.
Folkert W Asselbergs, Yiran Guo, Erik P A van Iperen, Suthesh Sivapalaratnam, Vinicius Tragante, Matthew B Lanktree, Leslie A Lange, Berta Almoguera, Yolande E Appelman, John Barnard, Jens Baumert, Amber L Beitelshees, Tushar R Bhangale, Yii-Der Ida Chen, Tom R Gaunt, Yan Gong, Jemma C Hopewell, Toby Johnson, Marcus E Kleber, Taimour Y Langaee, Mingyao Li, Yun R Li, Kiang Liu, Caitrin W McDonough, Matthijs F L Meijs, Rita P S Middelberg, Kiran Musunuru, Christopher P Nelson, Jeffery R O'Connell, Sandosh Padmanabhan, James S Pankow, Nathan Pankratz, Suzanne Rafelt, Ramakrishnan Rajagopalan, Simon P R Romaine, Nicholas J Schork, Jonathan Shaffer, Haiqing Shen, Erin N Smith, Sam E Tischfield, Peter J van der Most, Jana V van Vliet-Ostaptchouk, Niek Verweij, Kelly A Volcik, Li Zhang, Kent R Bailey, Kristian M Bailey, Florianne Bauer, Jolanda M A Boer, Peter S Braund, Amber Burt, Paul R Burton, Sarah G Buxbaum, Wei Chen, Rhonda M Cooper-DeHoff, L Adrienne Cupples, Jonas S deJong, Christian Delles, David Duggan, Myriam Fornage, Clement E Furlong, Nicole Glazer, John G Gums, Claire Hastie, Michael V Holmes, Thomas Illig, Susan A Kirkland, Mika Kivimäki, Ronald Klein, Barbara E Klein, Charles Kooperberg, Kandice Kottke-Marchant, Meena Kumari, Andrea Z LaCroix, Laya Mallela, Gurunathan Murugesan, Jose Ordovas, Willem H Ouwehand, Wendy S Post, Richa Saxena, Hubert Scharnagl, Pamela J Schreiner, Tina Shah, Denis C Shields, Daichi Shimbo, Sathanur R Srinivasan, Ronald P Stolk, Daniel I Swerdlow, Herman A Taylor, Eric J Topol, Elina Toskala, Joost L van Pelt, Jessica van Setten, Salim Yusuf, John C Whittaker, A H Zwinderman, , Sonia S Anand, Anthony J Balmforth, Gerald S Berenson, Connie R Bezzina, Bernhard O Boehm, Eric Boerwinkle, Juan P Casas, Mark J Caulfield, Robert Clarke, John M Connell, Karen J Cruickshanks, Karina W Davidson, Ian N M Day, Paul I W de Bakker, Pieter A Doevendans, Anna F Dominiczak, Alistair S Hall, Catharina A Hartman, Christian Hengstenberg, Hans L Hillege, Marten H Hofker, Steve E Humphries, Gail P Jarvik, Julie A Johnson, Bernhard M Kaess, Sekar Kathiresan, Wolfgang Koenig, Debbie A Lawlor, Winfried März, Olle Melander, Braxton D Mitchell, Grant W Montgomery, Patricia B Munroe, Sarah S Murray, Stephen J Newhouse, N Charlotte Onland-Moret, Neil Poulter, Bruce Psaty, Susan Redline, Stephen S Rich, Jerome I Rotter, Heribert Schunkert, Peter Sever, Alan R Shuldiner, Roy L Silverstein, Alice Stanton, Barbara Thorand, Mieke D Trip, Michael Y Tsai, Pim van der Harst, Ellen van der Schoot, Yvonne T van der Schouw, W M Monique Verschuren, Hugh Watkins, Arthur A M Wilde, Bruce H R Wolffenbuttel, John B Whitfield, G Kees Hovingh, Christie M Ballantyne, Cisca Wijmenga, Muredach P Reilly, Nicholas G Martin, James G Wilson, Daniel J Rader, Nilesh J Samani, Alex P Reiner, Robert A Hegele, John J P Kastelein, Aroon D Hingorani, Philippa J Talmud, Hakon Hakonarson, Clara C Elbers, Brendan J Keating, Fotios Drenos.
Am. J. Hum. Genet.
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Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ?50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ?2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity.
PLoS ONE
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The conventional wisdom is that certain classes of bioactive peptides have specific structural features that endow their particular functions. Accordingly, predictions of bioactivity have focused on particular subgroups, such as antimicrobial peptides. We hypothesized that bioactive peptides may share more general features, and assessed this by contrasting the predictive power of existing antimicrobial predictors as well as a novel general predictor, PeptideRanker, across different classes of peptides.We observed that existing antimicrobial predictors had reasonable predictive power to identify peptides of certain other classes i.e. toxin and venom peptides. We trained two general predictors of peptide bioactivity, one focused on short peptides (4-20 amino acids) and one focused on long peptides (> 20 amino acids). These general predictors had performance that was typically as good as, or better than, that of specific predictors. We noted some striking differences in the features of short peptide and long peptide predictions, in particular, high scoring short peptides favour phenylalanine. This is consistent with the hypothesis that short and long peptides have different functional constraints, perhaps reflecting the difficulty for typical short peptides in supporting independent tertiary structure.We conclude that there are general shared features of bioactive peptides across different functional classes, indicating that computational prediction may accelerate the discovery of novel bioactive peptides and aid in the improved design of existing peptides, across many functional classes. An implementation of the predictive method, PeptideRanker, may be used to identify among a set of peptides those that may be more likely to be bioactive.
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Peptide-binding domains: are limp handshakes safest?
Sci Signal
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Interactions between short peptides within proteins and peptide-binding domains can trigger many important cell signaling processes, and their interactions are typically of modest affinity. A study showed that this modest affinity appears to be favored by evolution. They used phage display selection to discover "superbinder" Src Homology 2 (SH2) domains, which bound peptides with much stronger affinity than naturally occurring SH2 domains. These superbinder domains had strong biological effects, such as blocking cell signaling. Although the superbinders had higher affinity, this did not appear to reduce their specificity. In contrast, SH2-binding peptides from bacterial pathogens have evolved to exhibit promiscuity of binding to multiple SH2 domains, carried within effector proteins that subvert signaling upon entry into the mammalian cell. Because there are many potential peptide binders of the SH2 domain found in numerous human proteins, modest affinity not only may optimize transient signaling mediated by reversible interactions but also may minimize off-target deleterious binding effects. The stage is set for a more thorough evaluation of the specificity and off-target impact of both naturally occurring and artificial domains and peptides. This may help define both targets and reagents for therapeutic intervention in key signaling processes mediated by short peptides.
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SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions.
Nucleic Acids Res.
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Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E.
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Protein disorder and short conserved motifs in disordered regions are enriched near the cytoplasmic side of single-pass transmembrane proteins.
PLoS ONE
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Intracellular juxtamembrane regions of transmembrane proteins play pivotal roles in cell signalling, mediated by protein-protein interactions. Disordered protein regions, and short conserved motifs within them, are emerging as key determinants of many such interactions. Here, we investigated whether disorder and conserved motifs are enriched in the juxtamembrane area of human single-pass transmembrane proteins. Conserved motifs were defined as short disordered regions that were much more conserved than the adjacent disordered residues. Human single-pass proteins had higher mean disorder in their cytoplasmic segments than their extracellular parts. Some, but not all, of this effect reflected the shorter length of the cytoplasmic tail. A peak of cytoplasmic disorder was seen at around 30 residues from the membrane. We noted a significant increase in the incidence of conserved motifs within the disordered regions at the same location, even after correcting for the extent of disorder. We conclude that elevated disorder within the cytoplasmic tail of many transmembrane proteins is likely to be associated with enrichment for signalling interactions mediated by conserved short motifs.
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Structures of YAP protein domains reveal promising targets for development of new cancer drugs.
Semin. Cell Dev. Biol.
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YAP (Yes-associated protein) is a potent oncogene and a major effector of the mammalian Hippo tumor suppressor pathway. In this review, our emphasis is on the structural basis of how YAP recognizes its various cellular partners. In particular, we discuss the role of LATS kinase and AMOTL1 junction protein, two key cellular partners of YAP that bind to its WW domain, in mediating cytoplasmic localization of YAP and thereby playing a key role in the regulation of its transcriptional activity. Importantly, the crystal structure of an amino-terminal domain of YAP in complex with the carboxy-terminal domain of TEAD transcription factor was only recently solved at atomic resolution, while the structure of WW domain of YAP in complex with a peptide containing the PPxY motif has been available for more than a decade. We discuss how such structural information may be exploited for the rational development of novel anti-cancer therapeutics harboring greater efficacy coupled with low toxicity. We also embark on a brief discussion of how recent in silico studies led to identification of the cardiac glycoside digitoxin as a potential modulator of WW domain-ligand interactions. Conversely, dobutamine was identified in a screen of known drugs as a compound that promotes cytoplasmic localization of YAP, thereby resulting in growth suppressing activity. Finally, we discuss how a recent study on the dynamics of WW domain folding on a biologically critical time scale may provide a tool to generate repertoires of WW domain variants for regulation of the Hippo pathway toward desired, non-oncogenic outputs.
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Profile-based short linear protein motif discovery.
BMC Bioinformatics
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Short linear protein motifs are attracting increasing attention as functionally independent sites, typically 3-10 amino acids in length that are enriched in disordered regions of proteins. Multiple methods have recently been proposed to discover over-represented motifs within a set of proteins based on simple regular expressions. Here, we extend these approaches to profile-based methods, which provide a richer motif representation.
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Genome-wide association study of genetic determinants of LDL-c response to atorvastatin therapy: importance of Lp(a).
J. Lipid Res.
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We carried out a genome-wide association study (GWAS) of LDL-c response to statin using data from participants in the Collaborative Atorvastatin Diabetes Study (CARDS; n = 1,156), the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT; n = 895), and the observational phase of ASCOT (n = 651), all of whom were prescribed atorvastatin 10 mg. Following genome-wide imputation, we combined data from the three studies in a meta-analysis. We found associations of LDL-c response to atorvastatin that reached genome-wide significance at rs10455872 (P = 6.13 × 10(-9)) within the LPA gene and at two single nucleotide polymorphisms (SNP) within the APOE region (rs445925; P = 2.22 × 10(-16) and rs4420638; P = 1.01 × 10(-11)) that are proxies for the ?2 and ?4 variants, respectively, in APOE. The novel association with the LPA SNP was replicated in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial (P = 0.009). Using CARDS data, we further showed that atorvastatin therapy did not alter lipoprotein(a) [Lp(a)] and that Lp(a) levels accounted for all of the associations of SNPs in the LPA gene and the apparent LDL-c response levels. However, statin therapy had a similar effect in reducing cardiovascular disease (CVD) in patients in the top quartile for serum Lp(a) levels (HR = 0.60) compared with those in the lower three quartiles (HR = 0.66; P = 0.8 for interaction). The data emphasize that high Lp(a) levels affect the measurement of LDL-c and the clinical estimation of LDL-c response. Therefore, an apparently lower LDL-c response to statin therapy may indicate a need for measurement of Lp(a). However, statin therapy seems beneficial even in those with high Lp(a).
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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.
Richa Saxena, Clara C Elbers, Yiran Guo, Inga Peter, Tom R Gaunt, Jessica L Mega, Matthew B Lanktree, Archana Tare, Berta Almoguera Castillo, Yun R Li, Toby Johnson, Marcel Bruinenberg, Diane Gilbert-Diamond, Ramakrishnan Rajagopalan, Benjamin F Voight, Ashok Balasubramanyam, John Barnard, Florianne Bauer, Jens Baumert, Tushar Bhangale, Bernhard O Böhm, Peter S Braund, Paul R Burton, Hareesh R Chandrupatla, Robert Clarke, Rhonda M Cooper-DeHoff, Errol D Crook, George Davey-Smith, Ian N Day, Anthonius de Boer, Mark C H de Groot, Fotios Drenos, Jane Ferguson, Caroline S Fox, Clement E Furlong, Quince Gibson, Christian Gieger, Lisa A Gilhuijs-Pederson, Joseph T Glessner, Anuj Goel, Yan Gong, Struan F A Grant, Diederick E Grobbee, Claire Hastie, Steve E Humphries, Cecilia E Kim, Mika Kivimäki, Marcus Kleber, Christa Meisinger, Meena Kumari, Taimour Y Langaee, Debbie A Lawlor, Mingyao Li, Maximilian T Lobmeyer, Anke-Hilse Maitland-van der Zee, Matthijs F L Meijs, Cliona M Molony, David A Morrow, Gurunathan Murugesan, Solomon K Musani, Christopher P Nelson, Stephen J Newhouse, Jeffery R O'Connell, Sandosh Padmanabhan, Jutta Palmen, Sanjey R Patel, Carl J Pepine, Mary Pettinger, Thomas S Price, Suzanne Rafelt, Jane Ranchalis, Asif Rasheed, Elisabeth Rosenthal, Ingo Ruczinski, Sonia Shah, Haiqing Shen, Günther Silbernagel, Erin N Smith, Annemieke W M Spijkerman, Alice Stanton, Michael W Steffes, Barbara Thorand, Mieke Trip, Pim van der Harst, Daphne L van der A, Erik P A van Iperen, Jessica van Setten, Jana V van Vliet-Ostaptchouk, Niek Verweij, Bruce H R Wolffenbuttel, Taylor Young, M Hadi Zafarmand, Joseph M Zmuda, , Michael Boehnke, David Altshuler, Mark McCarthy, W H Linda Kao, James S Pankow, Thomas P Cappola, Peter Sever, Neil Poulter, Mark Caulfield, Anna Dominiczak, Denis C Shields, Deepak L Bhatt, Deepak Bhatt, Li Zhang, Sean P Curtis, John Danesh, Juan P Casas, Yvonne T van der Schouw, N Charlotte Onland-Moret, Pieter A Doevendans, Gerald W Dorn, Martin Farrall, Garret A FitzGerald, Anders Hamsten, Robert Hegele, Aroon D Hingorani, Marten H Hofker, Gordon S Huggins, Thomas Illig, Gail P Jarvik, Julie A Johnson, Olaf H Klungel, William C Knowler, Wolfgang Koenig, Winfried März, James B Meigs, Olle Melander, Patricia B Munroe, Braxton D Mitchell, Susan J Bielinski, Daniel J Rader, Muredach P Reilly, Stephen S Rich, Jerome I Rotter, Danish Saleheen, Nilesh J Samani, Eric E Schadt, Alan R Shuldiner, Roy Silverstein, Kandice Kottke-Marchant, Philippa J Talmud, Hugh Watkins, Folkert W Asselbergs, Folkert Asselbergs, Paul I W de Bakker, Jeanne McCaffery, Cisca Wijmenga, Marc S Sabatine, James G Wilson, Alex Reiner, Donald W Bowden, Hakon Hakonarson, David S Siscovick, Brendan J Keating.
Am. J. Hum. Genet.
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To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ?50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ?2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.
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