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1.  Identification of flubendazole as potential anti-neuroblastoma compound in a large cell line screen 
Scientific Reports  2015;5:8202.
Flubendazole was shown to exert anti-leukaemia and anti-myeloma activity through inhibition of microtubule function. Here, flubendazole was tested for its effects on the viability of in total 461 cancer cell lines. Neuroblastoma was identified as highly flubendazole-sensitive cancer entity in a screen of 321 cell lines from 26 cancer entities. Flubendazole also reduced the viability of five primary neuroblastoma samples in nanomolar concentrations thought to be achievable in humans and inhibited vessel formation and neuroblastoma tumour growth in the chick chorioallantoic membrane assay. Resistance acquisition is a major problem in high-risk neuroblastoma. 119 cell lines from a panel of 140 neuroblastoma cell lines with acquired resistance to various anti-cancer drugs were sensitive to flubendazole in nanomolar concentrations. Tubulin-binding agent-resistant cell lines displayed the highest flubendazole IC50 and IC90 values but differences between drug classes did not reach statistical significance. Flubendazole induced p53-mediated apoptosis. The siRNA-mediated depletion of the p53 targets p21, BAX, or PUMA reduced the neuroblastoma cell sensitivity to flubendazole with PUMA depletion resulting in the most pronounced effects. The MDM2 inhibitor and p53 activator nutlin-3 increased flubendazole efficacy while RNAi-mediated p53-depletion reduced its activity. In conclusion, flubendazole represents a potential treatment option for neuroblastoma including therapy-refractory cells.
doi:10.1038/srep08202
PMCID: PMC4314641  PMID: 25644037
2.  Proteomic analysis of the Plasmodium male gamete reveals the key role for glycolysis in flagellar motility 
Malaria Journal  2014;13(1):315.
Background
Gametogenesis and fertilization play crucial roles in malaria transmission. While male gametes are thought to be amongst the simplest eukaryotic cells and are proven targets of transmission blocking immunity, little is known about their molecular organization. For example, the pathway of energy metabolism that power motility, a feature that facilitates gamete encounter and fertilization, is unknown.
Methods
Plasmodium berghei microgametes were purified and analysed by whole-cell proteomic analysis for the first time. Data are available via ProteomeXchange with identifier PXD001163.
Results
615 proteins were recovered, they included all male gamete proteins described thus far. Amongst them were the 11 enzymes of the glycolytic pathway. The hexose transporter was localized to the gamete plasma membrane and it was shown that microgamete motility can be suppressed effectively by inhibitors of this transporter and of the glycolytic pathway.
Conclusions
This study describes the first whole-cell proteomic analysis of the malaria male gamete. It identifies glycolysis as the likely exclusive source of energy for flagellar beat, and provides new insights in original features of Plasmodium flagellar organization.
Electronic supplementary material
The online version of this article (doi:10.1186/1475-2875-13-315) contains supplementary material, which is available to authorized users.
doi:10.1186/1475-2875-13-315
PMCID: PMC4150949  PMID: 25124718
Gamete; Plasmodium; Glycolysis; Flagellum; Energy metabolism
3.  The South Asian Genome 
PLoS ONE  2014;9(8):e102645.
The genetic sequence variation of people from the Indian subcontinent who comprise one-quarter of the world's population, is not well described. We carried out whole genome sequencing of 168 South Asians, along with whole-exome sequencing of 147 South Asians to provide deeper characterisation of coding regions. We identify 12,962,155 autosomal sequence variants, including 2,946,861 new SNPs and 312,738 novel indels. This catalogue of SNPs and indels amongst South Asians provides the first comprehensive map of genetic variation in this major human population, and reveals evidence for selective pressures on genes involved in skin biology, metabolism, infection and immunity. Our results will accelerate the search for the genetic variants underlying susceptibility to disorders such as type-2 diabetes and cardiovascular disease which are highly prevalent amongst South Asians.
doi:10.1371/journal.pone.0102645
PMCID: PMC4130493  PMID: 25115870
4.  VarMod: modelling the functional effects of non-synonymous variants 
Nucleic Acids Research  2014;42(Web Server issue):W331-W336.
Unravelling the genotype–phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in proteins the difficulties of the problem lie in first identifying those nsSNVs that result in a functional change in the protein among the many non-functional variants and in turn linking this functional change to phenotype. Here we present VarMod (Variant Modeller) a method that utilises both protein sequence and structural features to predict nsSNVs that alter protein function. VarMod develops recent observations that functional nsSNVs are enriched at protein–protein interfaces and protein–ligand binding sites and uses these characteristics to make predictions. In benchmarking on a set of nearly 3000 nsSNVs VarMod performance is comparable to an existing state of the art method. The VarMod web server provides extensive resources to investigate the sequence and structural features associated with the predictions including visualisation of protein models and complexes via an interactive JSmol molecular viewer. VarMod is available for use at http://www.wasslab.org/varmod.
doi:10.1093/nar/gku483
PMCID: PMC4086131  PMID: 24906884
5.  A large-scale evaluation of computational protein function prediction 
Radivojac, Predrag | Clark, Wyatt T | Ronnen Oron, Tal | Schnoes, Alexandra M | Wittkop, Tobias | Sokolov, Artem | Graim, Kiley | Funk, Christopher | Verspoor, Karin | Ben-Hur, Asa | Pandey, Gaurav | Yunes, Jeffrey M | Talwalkar, Ameet S | Repo, Susanna | Souza, Michael L | Piovesan, Damiano | Casadio, Rita | Wang, Zheng | Cheng, Jianlin | Fang, Hai | Gough, Julian | Koskinen, Patrik | Törönen, Petri | Nokso-Koivisto, Jussi | Holm, Liisa | Cozzetto, Domenico | Buchan, Daniel W A | Bryson, Kevin | Jones, David T | Limaye, Bhakti | Inamdar, Harshal | Datta, Avik | Manjari, Sunitha K | Joshi, Rajendra | Chitale, Meghana | Kihara, Daisuke | Lisewski, Andreas M | Erdin, Serkan | Venner, Eric | Lichtarge, Olivier | Rentzsch, Robert | Yang, Haixuan | Romero, Alfonso E | Bhat, Prajwal | Paccanaro, Alberto | Hamp, Tobias | Kassner, Rebecca | Seemayer, Stefan | Vicedo, Esmeralda | Schaefer, Christian | Achten, Dominik | Auer, Florian | Böhm, Ariane | Braun, Tatjana | Hecht, Maximilian | Heron, Mark | Hönigschmid, Peter | Hopf, Thomas | Kaufmann, Stefanie | Kiening, Michael | Krompass, Denis | Landerer, Cedric | Mahlich, Yannick | Roos, Manfred | Björne, Jari | Salakoski, Tapio | Wong, Andrew | Shatkay, Hagit | Gatzmann, Fanny | Sommer, Ingolf | Wass, Mark N | Sternberg, Michael J E | Škunca, Nives | Supek, Fran | Bošnjak, Matko | Panov, Panče | Džeroski, Sašo | Šmuc, Tomislav | Kourmpetis, Yiannis A I | van Dijk, Aalt D J | ter Braak, Cajo J F | Zhou, Yuanpeng | Gong, Qingtian | Dong, Xinran | Tian, Weidong | Falda, Marco | Fontana, Paolo | Lavezzo, Enrico | Di Camillo, Barbara | Toppo, Stefano | Lan, Liang | Djuric, Nemanja | Guo, Yuhong | Vucetic, Slobodan | Bairoch, Amos | Linial, Michal | Babbitt, Patricia C | Brenner, Steven E | Orengo, Christine | Rost, Burkhard | Mooney, Sean D | Friedberg, Iddo
Nature methods  2013;10(3):221-227.
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools.
doi:10.1038/nmeth.2340
PMCID: PMC3584181  PMID: 23353650
6.  Genetic loci influencing kidney function and chronic kidney disease in man 
Chambers, John C | Zhang, Weihua | Lord, Graham M | van der Harst, Pim | Lawlor, Debbie A | Sehmi, Joban S | Gale, Daniel P | Wass, Mark N | Ahmadi, Kourosh R | Bakker, Stephan JL | Beckmann, Jacqui | Bilo, Henk JG | Bochud, Murielle | Brown, Morris J | Caulfield, Mark J | Connell, John M C | Cook, Terence | Cotlarciuc, Ioana | Smith, George Davey | de Silva, Ranil | Deng, Guohong | Devuyst, Olivier | Dikkeschei, Lambert D. | Dimkovic, Nada | Dockrell, Mark | Dominiczak, Anna | Ebrahim, Shah | Eggermann, Thomas | Farrall, Martin | Ferrucci, Luigi | Floege, Jurgen | Forouhi, Nita G | Gansevoort, Ron T | Han, Xijin | Hedblad, Bo | van der Heide, Jaap J Homan | Hepkema, Bouke G | Hernandez-Fuentes, Maria | Hypponen, Elina | Johnson, Toby | de Jong, Paul E | Kleefstra, Nanne | Lagou, Vasiliki | Lapsley, Marta | Li, Yun | Loos, Ruth J F | Luan, Jian'an | Luttropp, Karin | Maréchal, Céline | Melander, Olle | Munroe, Patricia B | Nordfors, Louise | Parsa, Afshin | Penninx, Brenda W. | Perucha, Esperanza | Pouta, Anneli | Prokopenko, Inga | Roderick, Paul J | Ruokonen, Aimo | Samani, Nilesh | Sanna, Serena | Schalling, Martin | Schlessinger, David | Schlieper, Georg | Seelen, Marc AJ | Shuldiner, Alan R | Sjögren, Marketa | Smit, Johannes H. | Snieder, Harold | Soranzo, Nicole | Spector, Timothy D | Stenvinkel, Peter | Sternberg, Michael JE | Swaminathan, Ramasamyiyer | Tanaka, Toshiko | Ubink-Veltmaat, Lielith J. | Uda, Manuela | Vollenweider, Peter | Wallace, Chris | Waterworth, Dawn | Zerres, Klaus | Waeber, Gerard | Wareham, Nicholas J | Maxwell, Patrick H | McCarthy, Mark I | Jarvelin, Marjo-Riitta | Mooser, Vincent | Abecasis, Goncalo R | Lightstone, Liz | Scott, James | Navis, Gerjan | Elliott, Paul | Kooner., Jaspal S
Nature genetics  2010;42(5):373-375.
Chronic kidney disease (CKD), the result of permanent loss of kidney function, is a major global problem. We identify common genetic variants at chr2p12-p13, chr6q26, chr17q23 and chr19q13 associated with serum creatinine, a marker of kidney function (P=10−10 to 10−15). SNPs rs10206899 (near NAT8, chr2p12-p13) and rs4805834 (near SLC7A9, chr19q13) were also associated with CKD. Our findings provide new insight into metabolic, solute and drug-transport pathways underlying susceptibility to CKD.
doi:10.1038/ng.566
PMCID: PMC3748585  PMID: 20383145
7.  Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma 
Chambers, John C | Zhang, Weihua | Sehmi, Joban | Li, Xinzhong | Wass, Mark N | Van der Harst, Pim | Holm, Hilma | Sanna, Serena | Kavousi, Maryam | Baumeister, Sebastian E | Coin, Lachlan J | Deng, Guohong | Gieger, Christian | Heard-Costa, Nancy L | Hottenga, Jouke-Jan | Kühnel, Brigitte | Kumar, Vinod | Lagou, Vasiliki | Liang, Liming | Luan, Jian’an | Vidal, Pedro Marques | Leach, Irene Mateo | O’Reilly, Paul F | Peden, John F | Rahmioglu, Nilufer | Soininen, Pasi | Speliotes, Elizabeth K | Yuan, Xin | Thorleifsson, Gudmar | Alizadeh, Behrooz Z | Atwood, Larry D | Borecki, Ingrid B | Brown, Morris J | Charoen, Pimphen | Cucca, Francesco | Das, Debashish | de Geus, Eco J C | Dixon, Anna L | Döring, Angela | Ehret, Georg | Eyjolfsson, Gudmundur I | Farrall, Martin | Forouhi, Nita G | Friedrich, Nele | Goessling, Wolfram | Gudbjartsson, Daniel F | Harris, Tamara B | Hartikainen, Anna-Liisa | Heath, Simon | Hirschfield, Gideon M | Hofman, Albert | Homuth, Georg | Hyppönen, Elina | Janssen, Harry L A | Johnson, Toby | Kangas, Antti J | Kema, Ido P | Kühn, Jens P | Lai, Sandra | Lathrop, Mark | Lerch, Markus M | Li, Yun | Liang, T Jake | Lin, Jing-Ping | Loos, Ruth J F | Martin, Nicholas G | Moffatt, Miriam F | Montgomery, Grant W | Munroe, Patricia B | Musunuru, Kiran | Nakamura, Yusuke | O’Donnell, Christopher J | Olafsson, Isleifur | Penninx, Brenda W | Pouta, Anneli | Prins, Bram P | Prokopenko, Inga | Puls, Ralf | Ruokonen, Aimo | Savolainen, Markku J | Schlessinger, David | Schouten, Jeoffrey N L | Seedorf, Udo | Sen-Chowdhry, Srijita | Siminovitch, Katherine A | Smit, Johannes H | Spector, Timothy D | Tan, Wenting | Teslovich, Tanya M | Tukiainen, Taru | Uitterlinden, Andre G | Van der Klauw, Melanie M | Vasan, Ramachandran S | Wallace, Chris | Wallaschofski, Henri | Wichmann, H-Erich | Willemsen, Gonneke | Würtz, Peter | Xu, Chun | Yerges-Armstrong, Laura M | Abecasis, Goncalo R | Ahmadi, Kourosh R | Boomsma, Dorret I | Caulfield, Mark | Cookson, William O | van Duijn, Cornelia M | Froguel, Philippe | Matsuda, Koichi | McCarthy, Mark I | Meisinger, Christa | Mooser, Vincent | Pietiläinen, Kirsi H | Schumann, Gunter | Snieder, Harold | Sternberg, Michael J E | Stolk, Ronald P | Thomas, Howard C | Thorsteinsdottir, Unnur | Uda, Manuela | Waeber, Gérard | Wareham, Nicholas J | Waterworth, Dawn M | Watkins, Hugh | Whitfield, John B | Witteman, Jacqueline C M | Wolffenbuttel, Bruce H R | Fox, Caroline S | Ala-Korpela, Mika | Stefansson, Kari | Vollenweider, Peter | Völzke, Henry | Schadt, Eric E | Scott, James | Järvelin, Marjo-Riitta | Elliott, Paul | Kooner, Jaspal S
Nature genetics  2011;43(11):1131-1138.
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
doi:10.1038/ng.970
PMCID: PMC3482372  PMID: 22001757
8.  CombFunc: predicting protein function using heterogeneous data sources 
Nucleic Acids Research  2012;40(Web Server issue):W466-W470.
Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein–protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc.
doi:10.1093/nar/gks489
PMCID: PMC3394346  PMID: 22641853
9.  Genome-wide association study identifies variants in TMPRSS6 associated with hemoglobin levels 
Nature genetics  2009;41(11):1170-1172.
We carried out a genome-wide association study of hemoglobin levels in 16,001 individuals of European and Indian Asian ancestry. The most closely associated SNP (rs855791) results in nonsynonymous (V736A) change in the serine protease domain of TMPRSS6 and a blood hemoglobin concentration 0.13 (95% CI 0.09–0.17) g/dl lower per copy of allele A (P = 1.6 × 10−13). Our findings suggest that TMPRSS6, a regulator of hepcidin synthesis and iron handling, is crucial in hemoglobin level maintenance.
doi:10.1038/ng.462
PMCID: PMC3178047  PMID: 19820698
10.  3DLigandSite: predicting ligand-binding sites using similar structures 
Nucleic Acids Research  2010;38(Web Server issue):W469-W473.
3DLigandSite is a web server for the prediction of ligand-binding sites. It is based upon successful manual methods used in the eighth round of the Critical Assessment of techniques for protein Structure Prediction (CASP8). 3DLigandSite utilizes protein-structure prediction to provide structural models for proteins that have not been solved. Ligands bound to structures similar to the query are superimposed onto the model and used to predict the binding site. In benchmarking against the CASP8 targets 3DLigandSite obtains a Matthew’s correlation co-efficient (MCC) of 0.64, and coverage and accuracy of 71 and 60%, respectively, similar results to our manual performance in CASP8. In further benchmarking using a large set of protein structures, 3DLigandSite obtains an MCC of 0.68. The web server enables users to submit either a query sequence or structure. Predictions are visually displayed via an interactive Jmol applet. 3DLigandSite is available for use at http://www.sbg.bio.ic.ac.uk/3dligandsite.
doi:10.1093/nar/gkq406
PMCID: PMC2896164  PMID: 20513649
11.  Prediction of ligand binding sites using homologous structures and conservation at CASP8 
Proteins  2009;77(Suppl 9):147-151.
The Critical Assessment of protein Structure Prediction experiment (CASP) is a blind assessment of the prediction of protein structure and related topics including function prediction. We present our results in the function/binding site prediction category. Our approach to identify binding sites combined the use of the predicted structure of the targets with both residue conservation and the location of ligands bound to homologous structures. We obtained average coverage of 83% and 56% accuracy. Analysis of our predictions suggests that overprediction reduces the accuracy obtained due to large areas of conservation around the binding site that do not bind the ligand. In some proteins such conserved residues may have a functional role. A server version of our method will soon be available.
doi:10.1002/prot.22513
PMCID: PMC2814558  PMID: 19626715
bioinformatics; binding site; CASP; function prediction; structural biology

Results 1-11 (11)