Publications by authors named "Werner Mewes"

14 Publications

  • Page 1 of 1

Drug Development for Target Ribosomal Protein rpL35/uL29 for Repair of LAMB3R635X in Rare Skin Disease Epidermolysis Bullosa.

Skin Pharmacol Physiol 2021 6;34(4):167-182. Epub 2021 Apr 6.

Department of Life Science Engineering, Technische Hochschule Mittelhessen, Gießen, Germany.

Introduction: Epidermolysis bullosa (EB) describes a family of rare genetic blistering skin disorders. Various subtypes are clinically and genetically heterogeneous, and a lethal postpartum form of EB is the generalized severe junctional EB (gs-JEB). gs-JEB is mainly caused by premature termination codon (PTC) mutations in the skin anchor protein LAMB3 (laminin subunit beta-3) gene. The ribosome in majority of translational reads of LAMB3PTC mRNA aborts protein synthesis at the PTC signal, with production of a truncated, nonfunctional protein. This leaves an endogenous readthrough mechanism needed for production of functional full-length Lamb3 protein albeit at insufficient levels. Here, we report on the development of drugs targeting ribosomal protein L35 (rpL35), a ribosomal modifier for customized increase in production of full-length Lamb3 protein from a LAMB3PTC mRNA.

Methods: Molecular docking studies were employed to identify small molecules binding to human rpL35. Molecular determinants of small molecule binding to rpL35 were further characterized by titration of the protein with these ligands as monitored by nuclear magnetic resonance (NMR) spectroscopy in solution. Changes in NMR chemical shifts were used to map the docking sites for small molecules onto the 3D structure of the rpL35.

Results: Molecular docking studies identified 2 FDA-approved drugs, atazanavir and artesunate, as candidate small-molecule binders of rpL35. Molecular interaction studies predicted several binding clusters for both compounds scattered throughout the rpL35 structure. NMR titration studies identified the amino acids participating in the ligand interaction. Combining docking predictions for atazanavir and artesunate with rpL35 and NMR analysis of rpL35 ligand interaction, one binding cluster located near the N-terminus of rpL35 was identified. In this region, the nonidentical binding sites for atazanavir and artesunate overlap and are accessible when rpL35 is integrated in its natural ribosomal environment.

Conclusion: Atazanavir and artesunate were identified as candidate compounds binding to ribosomal protein rpL35 and may now be tested for their potential to trigger a rpL35 ribosomal switch to increase production of full-length Lamb3 protein from a LAMB3PTC mRNA for targeted systemic therapy in treating gs-JEB.
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http://dx.doi.org/10.1159/000513260DOI Listing
November 2021

MIPS: curated databases and comprehensive secondary data resources in 2010.

Nucleic Acids Res 2011 Jan 24;39(Database issue):D220-4. Epub 2010 Nov 24.

Institute for Bioinformatics and Systems Biology, MIPS, Helmholtz Center F Health and Environment, Ingolstädter Landstr 1, D-85764 Neuherberg, Germany.

The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38,000,000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de).
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http://dx.doi.org/10.1093/nar/gkq1157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013725PMC
January 2011

OREST: the online resource for EST analysis.

Nucleic Acids Res 2008 Jul 7;36(Web Server issue):W140-4. Epub 2008 May 7.

Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.

The generation of expressed sequence tag (EST) libraries offers an affordable approach to investigate organisms, if no genome sequence is available. OREST (http://mips.gsf.de/genre/proj/orest/index.html) is a server-based EST analysis pipeline, which allows the rapid analysis of large amounts of ESTs or cDNAs from mammalia and fungi. In order to assign the ESTs to genes or proteins OREST maps DNA sequences to reference datasets of gene products and in a second step to complete genome sequences. Mapping against genome sequences recovers additional 13% of EST data, which otherwise would escape further analysis. To enable functional analysis of the datasets, ESTs are functionally annotated using the hierarchical FunCat annotation scheme as well as GO annotation terms. OREST also allows to predict the association of gene products and diseases by Morbid Map (OMIM) classification. A statistical analysis of the results of the dataset is possible with the included PROMPT software, which provides information about enrichment and depletion of functional and disease annotation terms. OREST was successfully applied for the identification and functional characterization of more than 3000 EST sequences of the common marmoset monkey (Callithrix jacchus) as part of an international collaboration.
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http://dx.doi.org/10.1093/nar/gkn253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447738PMC
July 2008

SIMAP--structuring the network of protein similarities.

Nucleic Acids Res 2008 Jan 23;36(Database issue):D289-92. Epub 2007 Nov 23.

Chair of Genome Oriented Bioinformatics, Center of Life and Food Science, Technische Universität München, 85350 Freising-Weihenstephan, Germany.

Protein sequences are the most important source of evolutionary and functional information for new proteins. In order to facilitate the computationally intensive tasks of sequence analysis, the Similarity Matrix of Proteins (SIMAP) database aims to provide a comprehensive and up-to-date dataset of the pre-calculated sequence similarity matrix and sequence-based features like InterPro domains for all proteins contained in the major public sequence databases. As of September 2007, SIMAP covers approximately 17 million proteins and more than 6 million non-redundant sequences and provides a complete annotation based on InterPro 16. Novel features of SIMAP include a new, portlet-based web portal providing multiple, structured views on retrieved proteins and integration of protein clusters and a unique search method for similar domain architectures. Access to SIMAP is freely provided for academic use through the web portal for individuals at http://mips.gsf.de/simap/and through Web Services for programmatic access at http://mips.gsf.de/webservices/services/SimapService2.0?wsdl.
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http://dx.doi.org/10.1093/nar/gkm963DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2238827PMC
January 2008

CORUM: the comprehensive resource of mammalian protein complexes.

Nucleic Acids Res 2008 Jan 26;36(Database issue):D646-50. Epub 2007 Oct 26.

Institute for Bioinformatics (MIPS), German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany.

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The CORUM (http://mips.gsf.de/genre/proj/corum/index.html) database is a collection of experimentally verified mammalian protein complexes. Information is manually derived by critical reading of the scientific literature from expert annotators. Information about protein complexes includes protein complex names, subunits, literature references as well as the function of the complexes. For functional annotation, we use the FunCat catalogue that enables to organize the protein complex space into biologically meaningful subsets. The database contains more than 1750 protein complexes that are built from 2400 different genes, thus representing 12% of the protein-coding genes in human. A web-based system is available to query, view and download the data. CORUM provides a comprehensive dataset of protein complexes for discoveries in systems biology, analyses of protein networks and protein complex-associated diseases. Comparable to the MIPS reference dataset of protein complexes from yeast, CORUM intends to serve as a reference for mammalian protein complexes.
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http://dx.doi.org/10.1093/nar/gkm936DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2238909PMC
January 2008

Prediction and classification of protein functions.

Drug Discov Today Technol 2006 ;3(2):145-51

Technische Universität München, Chair of Genome Oriented Bioinformatics, Center of Life and Food Science, D-85350 Freising-Weihenstephan, Germany. Electronic

Data from large-scale genome projects, transcriptomics and proteomics experiments have provided scientists with a wealth of information establishing the basis for the investigation of cellular processes. To understand biological function beyond the single gene by the discovery and characterization of functional protein networks, bioinformatics analysis requires information about two additional attributes associated with the gene products: (i) high-level protein function prediction of experimentally uncharacterized proteins and (ii) systematic classification of protein function. This article describes the basic properties of protein classification systems and discusses examples of their implementation.:
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http://dx.doi.org/10.1016/j.ddtec.2006.06.011DOI Listing
July 2014

The Mouse Functional Genome Database (MfunGD): functional annotation of proteins in the light of their cellular context.

Nucleic Acids Res 2006 Jan;34(Database issue):D568-71

Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany.

MfunGD (http://mips.gsf.de/genre/proj/mfungd/) provides a resource for annotated mouse proteins and their occurrence in protein networks. Manual annotation concentrates on proteins which are found to interact physically with other proteins. Accordingly, manually curated information from a protein-protein interaction database (MPPI) and a database of mammalian protein complexes is interconnected with MfunGD. Protein function annotation is performed using the Functional Catalogue (FunCat) annotation scheme which is widely used for the analysis of protein networks. The dataset is also supplemented with information about the literature that was used in the annotation process as well as links to the SIMAP Fasta database, the Pedant protein analysis system and cross-references to external resources. Proteins that so far were not manually inspected are annotated automatically by a graphical probabilistic model and/or superparamagnetic clustering. The database is continuously expanding to include the rapidly growing amount of functional information about gene products from mouse. MfunGD is implemented in GenRE, a J2EE-based component-oriented multi-tier architecture following the separation of concern principle.
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http://dx.doi.org/10.1093/nar/gkj074DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1347437PMC
January 2006

SIMAP: the similarity matrix of proteins.

Nucleic Acids Res 2006 Jan;34(Database issue):D252-6

Department of Genome Oriented Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.

Similarity Matrix of Proteins (SIMAP) (http://mips.gsf.de/simap) provides a database based on a pre-computed similarity matrix covering the similarity space formed by >4 million amino acid sequences from public databases and completely sequenced genomes. The database is capable of handling very large datasets and is updated incrementally. For sequence similarity searches and pairwise alignments, we implemented a grid-enabled software system, which is based on FASTA heuristics and the Smith-Waterman algorithm. Our ProtInfo system allows querying by protein sequences covered by the SIMAP dataset as well as by fragments of these sequences, highly similar sequences and title words. Each sequence in the database is supplemented with pre-calculated features generated by detailed sequence analyses. By providing WWW interfaces as well as web-services, we offer the SIMAP resource as an efficient and comprehensive tool for sequence similarity searches.
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http://dx.doi.org/10.1093/nar/gkj106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1347468PMC
January 2006

SIMAP--the similarity matrix of proteins.

Bioinformatics 2005 Sep;21 Suppl 2:ii42-6

Institute for Bioinformatics, GSF-National Research Center for Environment and Health Ingolstädter, Neuherberg, Germany.

Motivation: Sequence similarity searches are of great importance in bioinformatics. Exhaustive searches for homologous proteins in databases are computationally expensive and can be replaced by a database of pre-calculated homologies in many cases. Retrieving similarities from an incrementally updated database instead of repeatedly recalculating them should provide homologs much faster and frees computational resources for other purposes.

Results: We have implemented SIMAP-a database containing the similarity space formed by almost all amino acid sequences from public databases and completely sequenced genomes. The database is capable of handling very large datasets and allows incremental updates. We have implemented a powerful backbone for similarity computation, which is based on FASTA heuristics. By providing WWW interfaces as well as web services, we make our data accessible to the worldwide community. We have also adapted procedures to detect putative orthologs as example applications.

Availability: The SIMAP portal page providing links to SIMAP services is publicly available: http://mips.gsf.de/services/analysis/simap/. The web services can be accessed under http://mips.gsf.de/proj/hobitws/services/RPCSimapService?wsdl and http://mips.gsf.de/proj/hobitws/services/DocSimapService?wsdl
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http://dx.doi.org/10.1093/bioinformatics/bti1107DOI Listing
September 2005

PRIME: a graphical interface for integrating genomic/proteomic databases.

Proteomics 2005 Jan;5(1):76-80

Institute for Bioinformatics, GSF Research Center, D-85764 Neuherberg, Germany.

Data mining, finding and integration of information about proteins of interest, is an essential component in modern biological and biomedical research. Even when focusing on a single organism and only on a small number of proteins, there are often dozens fo data sources containing relevant information. We are developing PRIME, a protein information environment, to serve as a virtual central database which integrates distributed heterogeneous information about proteins (linked by common identifier). PRIME has powerful capabilities to visualize all kinds of protein annotation in specialized views. These views can be displayed side by side at the same time and can be synchronized in order to show simultaneously different aspects of identical proteins. These features allow a quick and comprehensive overview of properties of single proteins or protein sets.
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http://dx.doi.org/10.1002/pmic.200400862DOI Listing
January 2005

The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes.

Nucleic Acids Res 2004 14;32(18):5539-45. Epub 2004 Oct 14.

Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany.

In this paper, we present the Functional Catalogue (FunCat), a hierarchically structured, organism-independent, flexible and scalable controlled classification system enabling the functional description of proteins from any organism. FunCat has been applied for the manual annotation of prokaryotes, fungi, plants and animals. We describe how FunCat is implemented as a highly efficient and robust tool for the manual and automatic annotation of genomic sequences. Owing to its hierarchical architecture, FunCat has also proved to be useful for many subsequent downstream bioinformatic applications. This is illustrated by the analysis of large-scale experiments from various investigations in transcriptomics and proteomics, where FunCat was used to project experimental data into functional units, as 'gold standard' for functional classification methods, and also served to compare the significance of different experimental methods. Over the last decade, the FunCat has been established as a robust and stable annotation scheme that offers both, meaningful and manageable functional classification as well as ease of perception.
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http://dx.doi.org/10.1093/nar/gkh894DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC524302PMC
February 2005

The genome sequence of the filamentous fungus Neurospora crassa.

Nature 2003 Apr;422(6934):859-68

Whitehead Institute Center for Genome Research, 320 Charles Street, Cambridge, Massachusetts 02141, USA.

Neurospora crassa is a central organism in the history of twentieth-century genetics, biochemistry and molecular biology. Here, we report a high-quality draft sequence of the N. crassa genome. The approximately 40-megabase genome encodes about 10,000 protein-coding genes--more than twice as many as in the fission yeast Schizosaccharomyces pombe and only about 25% fewer than in the fruitfly Drosophila melanogaster. Analysis of the gene set yields insights into unexpected aspects of Neurospora biology including the identification of genes potentially associated with red light photobiology, genes implicated in secondary metabolism, and important differences in Ca2+ signalling as compared with plants and animals. Neurospora possesses the widest array of genome defence mechanisms known for any eukaryotic organism, including a process unique to fungi called repeat-induced point mutation (RIP). Genome analysis suggests that RIP has had a profound impact on genome evolution, greatly slowing the creation of new genes through genomic duplication and resulting in a genome with an unusually low proportion of closely related genes.
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http://dx.doi.org/10.1038/nature01554DOI Listing
April 2003

What's in the genome of a filamentous fungus? Analysis of the Neurospora genome sequence.

Nucleic Acids Res 2003 Apr;31(7):1944-54

Technical University of Munich, Department of Genome Oriented Bioinformatics, Freising-Weihenstephan, Germany.

The German Neurospora Genome Project has assembled sequences from ordered cosmid and BAC clones of linkage groups II and V of the genome of Neurospora crassa in 13 and 12 contigs, respectively. Including additional sequences located on other linkage groups a total of 12 Mb were subjected to a manual gene extraction and annotation process. The genome comprises a small number of repetitive elements, a low degree of segmental duplications and very few paralogous genes. The analysis of the 3218 identified open reading frames provides a first overview of the protein equipment of a filamentous fungus. Significantly, N.crassa possesses a large variety of metabolic enzymes including a substantial number of enzymes involved in the degradation of complex substrates as well as secondary metabolism. While several of these enzymes are specific for filamentous fungi many are shared exclusively with prokaryotes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC152809PMC
http://dx.doi.org/10.1093/nar/gkg293DOI Listing
April 2003

Large scale analysis of sequences from Neurospora crassa.

J Biotechnol 2002 Mar;94(1):3-13

Institute of Biochemistry, Heinrich-Heine-University Düsseldorf, D-40225, Dusseldorf, Germany.

After 50 years of analysing Neurospora crassa genes one by one large scale sequence analysis has increased the number of accessible genes tremendously in the last few years. Being the only filamentous fungus for which a comprehensive genomic sequence database is publicly accessible N. crassa serves as the model for this important group of microorganisms. The MIPS N. crassa database currently holds more than 16 Mb of non-redundant data of the chromosomes II and V analysed by the German Neurospora Genome Project. This represents more than one-third of the genome. Open reading frames (ORFs) have been extracted from the sequence and the deduced proteins have been annotated extensively. They are classified according to matches in sequence databases and attributed to functional categories according to their relatives. While 41% of analysed proteins are related to known proteins, 30% are hypothetical proteins with no match to a database entry. The entire genome is expected to comprise some 13000 protein coding genes, more than twice as many as found in yeasts, and reflects the high potential of filamentous fungi to cope with various environmental conditions.
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http://dx.doi.org/10.1016/s0168-1656(01)00415-1DOI Listing
March 2002
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