Enzymes are extremely powerful natural catalysts able to perform almost any type of chemical reaction while being mild by nature and highly specific. In fact, the delicate functioning of enzymes forms the basis of every living creature. The catalytic potential of enzymes is more and more appreciated by the industry as many industrial processes rely on these sophisticated catalysts. However, the number of reactions catalyzed by enzymes is restricted as enzymes only have evolved to catalyze reactions that are physiologically relevant. Furthermore, enzymes have adapted to the direct (cellular) environment in which they have to function (e.g. operative at ambient temperature, resilient towards proteolysis, catalytic turnover rate should fit with metabolic enzyme partners). This excludes the existence of enzymes that do not fit within boundaries set by nature. It is a great challenge to go beyond these natural boundaries and develop methodologies to design ‘unnatural’ tailor-made enzymes. Ideally it should become possible to (re)design enzymes to convert pre-defined substrates. Such designer enzymes could theoretically exhibit unsurpassed catalytic properties and, obviously, will be of significant interest for industrial biotechnology. The OXYGREEN project aims at the design and construction of novel oxygenating enzymes (designer oxygenases) for the production of compounds that can be used in medicine, food and agriculture and the development of novel powerful and generic enzyme redesign tools for this purpose. The enzymes and whole-cell biocatalysts that will be developed should catalyze the specific incorporation of oxygen to afford synthesis of bioactive compounds in a selective and clean way, with minimal side products and with no use of toxic materials. For this, generic platform technologies (novel high-throughput methodology and methods for engineering dedicated host cells) will be developed that allow effective structure-inspired directed evolution of enzyme.
The objective of the BioSapiens Network of Excellence is to provide a large-scale effort to annotate human genome using both informatics tools and input from experimentalists. The Network will create a European Virtual Institute for Genome Annotation, bringing together many of the best laboratories in Europe. This institute will help to improve bioinformatics research in Europe and encourage cooperation between various laboratories.
The BioSapiens network tries also to integrate experimentalists and bioinformaticians, through a directed programme of genome analysis, focused on specific biological problems. The annotations generated by the Institute will be available in the public domain and easily accessible on the web. This will be achieved initially through a distributed annotation system (DAS), which will evolve to take advantage of new developments in the GRID.
The Institute will establish a permanent European School of Bioinformatics, to train bioinformaticians and to encourage best practise in the exploitation of genome annotation data for biologists. The courses and meetings will be open to all scientists throughout Europe, and available at all levels, from basic courses for experimentalists to more advanced training for experts. The BioSapiens NoE will increase European competitiveness, by new discoveries, increased integration, expert training and improved tools and services, and enhance Europe’s role in the academic and industrial exploitation of genomics.
Our particle-based method allows us to synthesise high complexity peptide arrays by combinatorial synthesis and for an unrivalled prize. We plan to further develop this new technology up to the level of robust prototype machines, and mate it to bioinformatics and readout tools. Together, our procedure(s) should boost the field of proteomics in a similar way as the lithographic technologies did with the field of genomics. Central to our novel method are the activated chemical building blocks that are “frozen” within solid amino acid particles. Thereby, we can use a colour laser printer to send them to defined addresses on a 2D support, where the particles are simply melted to induce a spatially defined coupling reaction of now freed amino acid derivatives. By repeated printing and melting cycles this simple trick yields high complexity peptide arrays. Based on existing pre-prototypes, we will develop a user-friendly peptide laser printer that spatially defined addresses our 20 different amino acid toners in high resolution to a support (WP1), and a scanner that especially fast and sensitive reads out the large formats delivered by the peptide laser printer (WP2). The increased production of amino acid toners and array supports are other bottlenecks in the output of peptide arrays that are tackled in WP3. This should allow us to increase the output of individual peptide spots from currently 0,5 Million to >10 Million peptides per month. Finally, to foster a market for high complexity peptide arrays, we will work out paradigmatic application examples in WP4. These aim to directly screen for antibiotic or apoptosis inducing D-peptides, and for the comprehensive readout of the different antibodies that patrol the serum of autoimmune patients. Based on user-friendly prototype machines, on first paradigmatic application examples for high complexity peptide arrays, and shielded by a strong patent, the participating SMEs will commercialise this new technology.
The four principal objectives of the ELM consortium are to (1) design, (2) develop, (3) maintain and (4) apply, a novel infrastructure resource devoted to the prediction of functional motifs in protein sequences. ELM (short for Eukaryotic Linear Motif) will be both “virtual” – provided electronically – and “distributed” – provided by a network of sites. Effective prediction of short motifs will require the implementation of hitherto unique context-dependent filtering software. The ELM resource will be made available to researchers as WWW servers and as a package for local installation.
The four principle objectives correspond approximately to overlapping phases of the ELM project:
Design: The initial design requirements are to integrate: (I) a relational database; (II) data input requirements; (III) new application software; (IV) private consortium web servers; and (V) public web servers. The partners will collectively contribute both the inferred biological needs and the underlying technical specifications. A document will be prepared that describes the internal ELM architecture. Subsequent revisions to the document will be ratified by all ELM partners. A web-based input form will ensure that data input meets the internal specification.
Develop: An extensive development phase is needed to create the software needed to effectively query ELM and to generate useful predictions. Various context filters will be developed as separate modules. The easiest filter modules will be completed first, and the more complex filters later in the project. As the modules are completed, they will be integrated into the ELM resource as serial filters. For optimal performance, the fastest executing filters will be accessed first, so that only the surviving motif candidates are passed on to the slower filters.
Maintain: The ELM servers will be continually maintained and extended as the project matures. Data will be continually added into the ELM resource and older data will be revised as new biological findings are published in the literature. While many motifs are already known, during the project there will be a steady stream of new motif publications. In the mature phase of ELM, releases will be scheduled at 6 month intervals.
Apply: As the ELM resource matures, it will become increasingly powerful and useful to experimentalists. Predicted motifs will suggest unexpected functional interactions or help to confirm suspected but poorly characterised ones. The consortium partners, and their close collaborators in the host institutes, will investigate predicted motifs relevant to their research interests. Verification (and to an extent exclusion) of predicted linear motifs will lead to enhanced understanding of multifunctional multidomain proteins, many of which assemble (via linear motifs) into huge complexes whose aggregate functions are hard to investigate with current experimental approaches.
The new partner will develop an additional ab-initio filter to estimate the conformational preferences of parts of proteins. The main objective of the task proposed by the new partner is to provide a reliable tool for detection of protease target sites. This new objective represents an expansion of the ongoing work complementary to the objectives outlined in WP2 and W3.
Genome scale analysis of the immune response against pathogenic micro-organisms; identification of diagnostic markers, vaccine candidates and development of an integrated micro array platform for clinical investigations.
The genome sequences of microbial organisms responsible for diseases of world-wide medical importance have been sequenced or will be available in the near future. Technologies for producing large numbers of proteins have been developed and high-throughput assays such as protein micro arrays have been clinically validated for detecting the presence of antibodies, in serum, directed against microbial antigens. These achievements offer the opportunity of investigating the natural immune response against the whole proteome of a variety of micro-organisms. Powerful combinations of genomic information, molecular tools and immunological assays are becoming available to help identify the antigens that function as targets of protective immunity or could be used as markers for serodiagnosis. We propose here to identify in micro-organisms of great medical relevance (M. pneumoniae, C. pneumoniae, L. pneumophila, coronavirus spp and P. falciparum), a large collection of surface and secreted proteins as well as putative endotoxins. This protein repertoire will be produced as recombinant molecules or as sets of overlapping synthetic peptides and printed on array slides. The serum reactivity of groups of individuals with proven history of exposure to the selected micro-organisms will be analysed against the arrayed proteins to identify diagnostic markers and correlates of protection.
This project will significantly expand the SMEs bank of Intellectual Property and contribute to expertise within the RTDs. It is anticipated that the proposed work in high throughput protein expression, software analysis, surface peptides synthesis, protein and peptide surface capture, and array reader instrumentation will create an integrated platform of great commercial and research value. Finally it will contribute to unravelling how the humoral immune response interacts with the microbial proteomes thus filling the gap between genomic data and development of novel vaccines and diagnostic tools.
Structural genomics is a wide term describing the determination of a structure representation based on information contained in the genome, and at present is almost exclusively limited to the proteins. Although in common understanding genetic information means “genes and their encoded protein products”, thousands of human genes produce transcripts which are biologically important but they do not produce proteins. Furthermore, even though the sequence of the human DNA is known by now, the meaning of the most of the sequences still remains unknown. It is very likely that a large amount of genes has been highly underestimated, mainly because the actual gene finders work well only for large, highly expressed, evolutionary conserved protein-coding genes. Most of those genome elements encode RNA from which transfer and ribosomal RNAs are the classical examples. But beside these well-known molecules there is a vast unknown world of tiny RNAs that might play a crucial role in a number of cellular processes. Those elements are named Noncoding RNAs (ncRNA) and they perform their function without transcription to the protein product. Here, we propose the development of the integrated bioinformatics platform that is specifically addressed for detecting, verifying, and classifying noncoding RNAs. This complex approach to “computational RNomics” will provide a pipeline which will be capable of detecting RNA motifs with low sequence conservation. It will also integrate the RNA motif prediction which should significantly improve the quality of the RNA homologues searching.
Combatting and eventually eradicating the new coronavirus causing Severe Acute Respiratory Syndrome (SARS) requires specific and efficient antiviral drugs and improved diagnostics. The Sino-European Project on SARS Diagnostics and Antivirals (SEPSDA) is an integrated project that applies modern biotechnical technology for the generation of improved diagnostics and of lead compounds for antiviral drugs. SEPSDA brings together leading SARS researchers from Germany, Denmark, Poland, and China, who together have an excellent publication record on the molecular biology of SARS coronavirus (SARS-CoV). Several of the existing anti-SARS drug leads as well as the first antibody-based diagnostic kit were created by members of SEPSDA. Participation of four leading laboratories in China brings SEPSDA in the unique position of having access to samples from Chinese patients at various stages of disease. Serological studies will lead to improved SARS diagnostics.
Analysis of the genome and the proteome of SARS coronavirus by sequencing and advanced bioinformatics will further determine the genetic variability of the virus isolates and identify new possible targets for therapeutic intervention, both at the RNA and the protein level. SEPSDA aims at determining the three-dimensional structures of all soluble SARS-CoV proteins or domains thereof. This structural genomics approach will provide the basis for the virtual screening of large compound databases, including those containing Chinese traditional medicines, for molecules potentially interfering with the function of the viral proteins or their interaction partners in the host cell. Candidate inhibitors will be tested in cell culture and improved by synthetic chemistry. After patenting, the lead compounds will be offered to an industrial platform on SARS, yet to be created, which should form an interface between SEPSDA and the pharmaceutical industry.
A High-throughput and universal system for DNA removal from biological samples
The project aims to create and test an innovative system for DNA removal from biological samples. Obtained DNase will have properties allowing for easy removal or inactivation after the reactions and enabling its use in solutions with high salt concentrations. Thus, the result of the project is a response to a market demand for easy to use and efficient DNase. The product will have an application in many areas of life-science sector in the purification of RNA and proteins, as well as in in vitro expression and cell cultures. The end results of the project will be the complete protocols of industrial preparation and utilization of nuclease-purification system.
The project is co-founded by the European Union through the Smart Growth Operational Programme 2014-2020
Chirality is a key factor in the efficacy of many drugs and the production of single enantiomers of chiral intermediates has therefore become increasingly important. Biocatalysis offers high enantioselectivity and regioselectivity in chiral synthesis through enzyme-catalyzed reactions and thus has an important advantage over chemical synthesis. Molecular genomic data is an unprecedented resource of enzymes for biocatalysis, but rational and effective methodologies must be established to realize the full potential of these resources. This project will focus on the discovery of novel enzymes, from both public and proprietary eubacterial genomes, in particular novel alcohol dehydrogenases, cytochrome P450 monooxygenases and amino acid modifying enzymes for use in established and innovative processes for chiral synthesis.
The DataGenome project extends from genome analysis, through cloning, expression, enzyme production, screening and protein engineering, to the enzymatic production of chiral biomolecules. The design of the project takes advantage of broad funnel-approach starting with innovative data-mining and processing of a large number of genes to ensure high flow-through in the process and rational selection of best enzyme candidates. The specific combination of expertise and design of the research project is aimed at high success-rate for the development of successful biocatalysts. Emphasis will be put on effective bioinformatics analysis to minimize the requirement for the more laborious “wet chemistry” analysis as well as development of optimized vector-host systems for efficient gene expression and enzyme production. Rational protein engineering or directed molecular evolution will be employed in order to obtain more robust variants, new substrate preferences or enhanced enantiomeric selectivity. Selected enzymes will be tested in existing and/or novel biocatalytic processes for production of chiral pharmaceutical intermediates with applications in therapeutic areas including AIDS, cancer and Alzheimer’s disease.