Imperial College London

ProfessorMichaelSternberg

Faculty of Natural SciencesDepartment of Life Sciences

Director Centre for Bioinformatics
 
 
 
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Contact

 

+44 (0)20 7594 5212m.sternberg Website

 
 
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Location

 

306Sir Ernst Chain BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

319 results found

Alhuzimi E, Leal LG, Sternberg MJE, David Aet al., 2018, Properties of human genes guided by their enrichment in rare and common variants, HUMAN MUTATION, Vol: 39, Pages: 365-370, ISSN: 1059-7794

JOURNAL ARTICLE

Cornish AJ, David A, Sternberg MJE, 2018, PhenoRank: reducing study bias in gene prioritisation through simulation., Bioinformatics

Motivation: Genome-wide association studies have identified thousands of loci associated with human disease, but identifying the causal genes at these loci is often difficult. Several methods prioritise genes most likely to be disease causing through the integration of biological data, including protein-protein interaction and phenotypic data. Data availability is not the same for all genes however, potentially influencing the performance of these methods. Results: We demonstrate that whilst disease genes tend to be associated with greater numbers of data, this may be at least partially a result of them being better studied. With this observation we develop PhenoRank, which prioritises disease genes whilst avoiding being biased towards genes with more available data. Bias is avoided by comparing gene scores generated for the query disease against gene scores generated using simulated sets of phenotype terms, which ensures that differences in data availability do not affect the ranking of genes. We demonstrate that whilst existing prioritisation methods are biased by data availability, PhenoRank is not similarly biased. Avoiding this bias allows PhenoRank to effectively prioritise genes with fewer available data and improves its overall performance. PhenoRank outperforms three available prioritisation methods in cross-validation (PhenoRank area under receiver operating characteristic curve [AUC]=0.89, DADA AUC=0.87, EXOMISER AUC=0.71, PRINCE AUC=0.83, P < 2.2 × 10-16). Availability: PhenoRank is freely available for download at https://github.com/alexjcornish/PhenoRank. Contact: m.sternberg@imperial.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

JOURNAL ARTICLE

Reynolds CR, Islam SA, Sternberg MJE, 2018, EzMol: A Web Server Wizard for the Rapid Visualization and Image Production of Protein and Nucleic Acid Structures., J Mol Biol

EzMol is a molecular visualization Web server in the form of a software wizard, located at http://www.sbg.bio.ic.ac.uk/ezmol/. It is designed for easy and rapid image manipulation and display of protein molecules, and is intended for users who need to quickly produce high-resolution images of protein molecules but do not have the time or inclination to use a software molecular visualization system. EzMol allows the upload of molecular structure files in PDB format to generate a Web page including a representation of the structure that the user can manipulate. EzMol provides intuitive options for chain display, adjusting the color/transparency of residues, side chains and protein surfaces, and for adding labels to residues. The final adjusted protein image can then be downloaded as a high-resolution image. There are a range of applications for rapid protein display, including the illustration of specific areas of a protein structure and the rapid prototyping of images.

JOURNAL ARTICLE

Ainsworth D, Sternberg MJE, Raczy C, Butcher SAet al., 2017, k-SLAM: accurate and ultra-fast taxonomic classification and gene identification for large metagenomic data sets, NUCLEIC ACIDS RESEARCH, Vol: 45, Pages: 1649-1656, ISSN: 0305-1048

JOURNAL ARTICLE

Bryant WA, Stentz R, Le Gall G, Sternberg MJE, Carding SR, Wilhelm Tet al., 2017, In Silico Analysis of the Small Molecule Content of Outer Membrane Vesicles Produced by Bacteroides thetaiotaomicron Indicates an Extensive Metabolic Link between Microbe and Host, FRONTIERS IN MICROBIOLOGY, Vol: 8, ISSN: 1664-302X

JOURNAL ARTICLE

Greener JG, Filippis I, Sternberg MJE, 2017, Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints, STRUCTURE, Vol: 25, Pages: 546-558, ISSN: 0969-2126

JOURNAL ARTICLE

Greener JG, Sternberg MJ, 2017, Structure-based prediction of protein allostery., Curr Opin Struct Biol, Vol: 50, Pages: 1-8

Allostery is the functional change at one site on a protein caused by a change at a distant site. In order for the benefits of allostery to be taken advantage of, both for basic understanding of proteins and to develop new classes of drugs, the structure-based prediction of allosteric binding sites, modulators and communication pathways is necessary. Here we review the recently emerging field of allosteric prediction, focusing mainly on computational methods. We also describe the search for cryptic binding pockets and attempts to design allostery into proteins. The development and adoption of such methods is essential or the long-preached potential of allostery will remain elusive.

JOURNAL ARTICLE

Ittisoponpisan S, Alhuzimi E, Sternberg MJE, David Aet al., 2017, Landscape of Pleiotropic Proteins Causing Human Disease: Structural and System Biology Insights, HUMAN MUTATION, Vol: 38, Pages: 289-296, ISSN: 1059-7794

JOURNAL ARTICLE

Ostankovitch MI, Sternberg MJE, 2017, Computation Resources for Molecular Biology: Special Issue 2017, JOURNAL OF MOLECULAR BIOLOGY, Vol: 429, Pages: 345-347, ISSN: 0022-2836

JOURNAL ARTICLE

Scales M, Chubb D, Dobbins SE, Johnson DC, Li N, Sternberg MJ, Weinhold N, Stein C, Jackson G, Davies FE, Walker BA, Wardell CP, Houlston RS, Morgan GJet al., 2017, Search for rare protein altering variants influencing susceptibility to multiple myeloma, ONCOTARGET, Vol: 8, Pages: 36203-36210, ISSN: 1949-2553

JOURNAL ARTICLE

Sundriyal S, Moniot S, Mahmud Z, Yao S, Di Fruscia P, Reynolds CR, Dexter DT, Sternberg MJE, Lam EW-F, Steegborn C, Fuchter MJet al., 2017, Thienopyrimidinone Based Sirtuin-2 (SIRT2)-Selective Inhibitors Bind in the Ligand Induced Selectivity Pocket, JOURNAL OF MEDICINAL CHEMISTRY, Vol: 60, Pages: 1928-1945, ISSN: 0022-2623

JOURNAL ARTICLE

Waese J, Fan J, Pasha A, Yu H, Fucile G, Shi R, Cumming M, Kelley LA, Sternberg MJ, Krishnakumar V, Ferlanti E, Miller J, Town C, Stuerzlinger W, Provart NJet al., 2017, ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology, PLANT CELL, Vol: 29, Pages: 1806-1821, ISSN: 1040-4651

JOURNAL ARTICLE

Howard SR, Guasti L, Ruiz-Babot G, Mancini A, David A, Storr H, Metherell LA, Sternberg MJE, Cabrera CP, Warren HR, Barnes MR, Quinton R, de Roux N, Young J, Guiochon-Mantel A, Wehkalampi K, Andre V, Gothilf Y, Cariboni A, Dunkel Let al., 2016, IGSF10 mutations dysregulate gonadotropin-releasing hormone neuronal migration resulting in delayed puberty, EMBO MOLECULAR MEDICINE, Vol: 8, Pages: 626-642, ISSN: 1757-4676

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Jiang Y, Oron TR, Clark WT, Bankapur AR, D'Andrea D, Lepore R, Funk CS, Kahanda I, Verspoor KM, Ben-Hur A, Koo DCE, Penfold-Brown D, Shasha D, Youngs N, Bonneau R, Lin A, Sahraeian SME, Martelli PL, Profiti G, Casadio R, Cao R, Zhong Z, Cheng J, Altenhoff A, Skunca N, Dessimoz C, Dogan T, Hakala K, Kaewphan S, Mehryary F, Salakoski T, Ginter F, Fang H, Smithers B, Oates M, Gough J, Toronen P, Koskinen P, Holm L, Chen C-T, Hsu W-L, Bryson K, Cozzetto D, Minneci F, Jones DT, Chapman S, Dukka BKC, Khan IK, Kihara D, Ofer D, Rappoport N, Stern A, Cibrian-Uhalte E, Denny P, Foulger RE, Hieta R, Legge D, Lovering RC, Magrane M, Melidoni AN, Mutowo-Meullenet P, Pichler K, Shypitsyna A, Li B, Zakeri P, ElShal S, Tranchevent L-C, Das S, Dawson NL, Lee D, Lees JG, Sillitoe I, Bhat P, Nepusz T, Romero AE, Sasidharan R, Yang H, Paccanaro A, Gillis J, Sedeno-Cortes AE, Pavlidis P, Feng S, Cejuela JM, Goldberg T, Hamp T, Richter L, Salamov A, Gabaldon T, Marcet-Houben M, Supek F, Gong Q, Ning W, Zhou Y, Tian W, Falda M, Fontana P, Lavezzo E, Toppo S, Ferrari C, Giollo M, Piovesan D, Tosatto SCE, del Pozo A, Fernandez JM, Maietta P, Valencia A, Tress ML, Benso A, Di Carlo S, Politano G, Savino A, Rehman HU, Re M, Mesiti M, Valentini G, Bargsten JW, van Dijk ADJ, Gemovic B, Glisic S, Perovic V, Veljkovic V, Veljkovic N, Almeida-e-Silva DC, Vencio RZN, Sharan M, Vogel J, Kansakar L, Zhang S, Vucetic S, Wang Z, Sternberg MJE, Wass MN, Huntley RP, Martin MJ, O'Donovan C, Robinson PN, Moreau Y, Tramontano A, Babbitt PC, Brenner SE, Linial M, Orengo CA, Rost B, Greene CS, Mooney SD, Friedberg I, Radivojac Pet al., 2016, An expanded evaluation of protein function prediction methods shows an improvement in accuracy, GENOME BIOLOGY, Vol: 17, ISSN: 1474-760X

JOURNAL ARTICLE

Metherell LA, Guerra-Assuncao JA, Sternberg MJ, David Aet al., 2016, Three-Dimensional Model of Human Nicotinamide Nucleotide Transhydrogenase (NNT) and Sequence-Structure Analysis of its Disease-Causing Variations, HUMAN MUTATION, Vol: 37, Pages: 1074-1084, ISSN: 1059-7794

JOURNAL ARTICLE

Mezulis S, Sternberg MJE, Kelley LA, 2016, PhyreStorm: A Web Server for Fast Structural Searches Against the PDB, JOURNAL OF MOLECULAR BIOLOGY, Vol: 428, Pages: 702-708, ISSN: 0022-2836

JOURNAL ARTICLE

Sternberg MJE, Ostankovitch MI, 2016, Computation Resources for Molecular Biology: A Special Issue, JOURNAL OF MOLECULAR BIOLOGY, Vol: 428, Pages: 669-670, ISSN: 0022-2836

JOURNAL ARTICLE

Cornish AJ, Filippis I, David A, Sternberg MJEet al., 2015, Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types, GENOME MEDICINE, Vol: 7, ISSN: 1756-994X

JOURNAL ARTICLE

David A, Sternberg MJ, 2015, The contribution of missense mutations in core and rim residues of protein-protein interfaces to human disease., Journal of Molecular Biology, Vol: 427, Pages: 2886-2898, ISSN: 1089-8638

Missense mutations at protein-protein interaction (PPIs) sites, called interfaces, are important contributors to human disease. Interfaces are non-uniform surface areas characterized by two main regions, 'core' and 'rim', which differ in terms of evolutionary conservation and physico-chemical properties. Moreover, within interfaces, only a small subset of residues ('hot spots') is crucial for the binding free energy of the protein-protein complex. We performed a large-scale structural analysis of human single amino acid variations (SAVs) and demonstrated that disease-causing mutations are preferentially located within the interface core, as opposed to the rim (p< 0.01). In contrast, the interface rim is significantly enriched in polymorphisms, similar to the remaining non-interacting surface. Energetic hot spots tend to be enriched in disease-causing mutations compared to non-hot spots (p=0.05), regardless of their occurrence in core or rim residues. For individual amino acids, the frequency of substitution into a polymorphism or disease-causing mutation differed to other amino acids and was related to its structural location, as was the type of physico-chemical change introduced by the SAV. In conclusion, this study demonstrated the different distribution and properties of disease-causing SAVs and polymorphisms within different structural regions and in relation to the energetic contribution of amino acid in protein-protein interfaces, thus highlighting the importance of a structural system biology approach for predicting the effect of SAVs.

JOURNAL ARTICLE

Di Fruscia P, Zacharioudakis E, Liu C, Moniot S, Laohasinnarong S, Khongkow M, Harrison IF, Koltsida K, Reynolds CR, Schmidtkunz K, Jung M, Chapman KL, Steegborn C, Dexter DT, Sternberg MJE, Lam EW-F, Fuchter MJet al., 2015, The Discovery of a Highly Selective 5,6,7,8-Tetrahydrobenzo[4,5]thieno[ 2,3-d] pyrimidin-4(3H)-one SIRT2 Inhibitor that is Neuroprotective in an in vitro Parkinson's Disease Model, CHEMMEDCHEM, Vol: 10, Pages: 69-82, ISSN: 1860-7179

JOURNAL ARTICLE

Greener JG, Sternberg MJE, 2015, AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis, BMC BIOINFORMATICS, Vol: 16, ISSN: 1471-2105

JOURNAL ARTICLE

Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJet al., 2015, The Phyre2 web portal for protein modeling, prediction and analysis., Nature Protocols, Vol: 10, Pages: 845-858, ISSN: 1754-2189

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

JOURNAL ARTICLE

Kelley LA, Sternberg MJ, 2015, Partial protein domains: evolutionary insights and bioinformatics challenges., Genome Biology, Vol: 16, Pages: 100-100, ISSN: 1474-760X

Protein domains are generally thought to correspond to units of evolution. New research raises questions about how such domains are defined with bioinformatics tools and sheds light on how evolution has enabled partial domains to be viable.

JOURNAL ARTICLE

Lewis TE, Sillitoe I, Andreeva A, Blundell TL, Buchan DWA, Chothia C, Cozzetto D, Dana JM, Filippis I, Gough J, Jones DT, Kelley LA, Kleywegt GJ, Minneci F, Mistry J, Murzin AG, Ochoa-Montano B, Oates ME, Punta M, Rackham OJL, Stahlhacke J, Sternberg MJE, Velankar S, Orengo Cet al., 2015, Genome3D: exploiting structure to help users understand their sequences, NUCLEIC ACIDS RESEARCH, Vol: 43, Pages: D382-D386, ISSN: 0305-1048

JOURNAL ARTICLE

Reynolds CR, Muggleton SH, Sternberg MJE, 2015, Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads, MOLECULAR INFORMATICS, Vol: 34, Pages: 615-625, ISSN: 1868-1743

JOURNAL ARTICLE

Irimia M, Weatheritt RJ, Ellis JD, Parikshak NN, Gonatopoulos-Pournatzis T, Babor M, Quesnel-Vallieres M, Tapial J, Raj B, O'Hanlon D, Barrios-Rodiles M, Sternberg MJE, Cordes SP, Roth FP, Wrana JL, Geschwind DH, Blencowe BJet al., 2014, A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains, Cell, Vol: 159, Pages: 1511-1523, ISSN: 0092-8674

Alternative splicing (AS) generates vast transcriptomicand proteomic complexity. However, whichof the myriad of detected AS events provide importantbiological functions is not well understood.Here, we define the largest program of functionallycoordinated, neural-regulated AS described to datein mammals. Relative to all other types of AS withinthis program, 3-15 nucleotide ‘‘microexons’’ displaythe most striking evolutionary conservation andswitch-like regulation. These microexons modulatethe function of interaction domains of proteinsinvolved in neurogenesis. Most neural microexonsare regulated by the neuronal-specific splicing factornSR100/SRRM4, through its binding to adjacentintronic enhancer motifs. Neural microexons arefrequently misregulated in the brains of individualswith autism spectrum disorder, and this misregulationis associated with reduced levels of nSR100.The results thus reveal a highly conserved programof dynamic microexon regulation associated withthe remodeling of protein-interaction networks duringneurogenesis, the misregulation of which islinked to autism.

JOURNAL ARTICLE

Talman AM, Prieto JH, Marques S, Ubaida-Mohien C, Lawniczak M, Wass MN, Xu T, Frank R, Ecker A, Stanway RS, Krishna S, Sternberg MJE, Christophides GK, Graham DR, Dinglasan RR, Yates JR, Sinden REet al., 2014, Proteomic analysis of the Plasmodium male gamete reveals the key role for glycolysis in flagellar motility, MALARIA JOURNAL, Vol: 13, ISSN: 1475-2875

JOURNAL ARTICLE

Yates CM, Filippis I, Kelley LA, Sternberg MJEet al., 2014, SuSPect: Enhanced Prediction of Single Amino Acid Variant (SAV) Phenotype Using Network Features, JOURNAL OF MOLECULAR BIOLOGY, Vol: 426, Pages: 2692-2701, ISSN: 0022-2836

JOURNAL ARTICLE

Adzhubei AA, Sternberg MJE, Makarov AA, 2013, Polyproline-II Helix in Proteins: Structure and Function, JOURNAL OF MOLECULAR BIOLOGY, Vol: 425, Pages: 2100-2132, ISSN: 0022-2836

JOURNAL ARTICLE

Alexov E, Sternberg M, 2013, Understanding molecular effects of naturally occurring genetic differences., J Mol Biol, Vol: 425, Pages: 3911-3913

JOURNAL ARTICLE

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