New analytical tools for studying autoimmune diseases

Protein microarrays with immobilised proteins on their surface are new analytical tools to overcome the current limits with respect to sample volume and throughput. They have a great potential as well with respect to multiplexing of complex samples, as a research tool and in diagnostics. Based on recent advances in this technology, new applications for protein microarrays in studying autoimmune diseases were described. Required tools for bioinformatical analysis of protein microarrays concerning normalisation, clustering and classification methods are discussed. The huge potential of this technology as well as future requirements such as protein microarray based diagnostics are presented.     

Parallel confocal detection of single biomolecules using diffractive optics and integrated detector units

The past few years we have witnessed a tremendous surge of interest in so-called array-based miniaturised analytical systems due to their value as extremely powerful tools for high-throughput sequence analysis, drug discovery and development, and diagnostic tests in medicine (see articles in Issue 1). Terminologies that have been used to describe these array-based bioscience systems include (but are not limited to): DNA-chip, microarrays, microchip, biochip, DNA-microarrays and genome chip. Potential technological benefits of introducing these miniaturised analytical systems include improved accuracy, multiplexing, lower sample and reagent consumption, disposability, and decreased analysis times, just to mention a few examples. Among the many alternative principles of detection-analysis (e.g.chemiluminescence, electroluminescence and conductivity), fluorescence-based techniques are widely used, examples being fluorescence resonance energy transfer, fluorescence quenching, fluorescence polarisation, time-resolved fluorescence, and fluorescence fluctuation spectroscopy (see articles in Issue 11). Time-dependent fluctuations of fluorescent biomolecules with different molecular properties, like molecular weight, translational and rotational diffusion time, colour and lifetime, potentially provide all the kinetic and thermodynamic information required in analysing complex interactions. In this mini-review article, we present recent extensions aimed to implement parallel laser excitation and parallel fluorescence detection that can lead to even further increase in throughput in miniaturised array-based analytical systems. We also report on developments and characterisations of multiplexing extension that allow multifocal laser excitation together with matched parallel fluorescence detection for parallel confocal dynamical fluorescence fluctuation studies at the single biomolecule level.     

Immobilised enzymes as drugs

The main objective of the work is to present the state of the art in a relatively new field of biotechnology — the use of immobilised enzymes in applied medicine. Enzyme therapy seems to be promising in the treatment of cardiovascular, oncological, intestinal, viral and hereditary diseases. At the same time there exist many limitations for the everyday clinical use of native enzymes. Enzymes are unstable, have a short lifetime in the circulation, cause toxic and immune reactions, and are costly, etc. These drawbacks can be at least partially eliminated by enzyme immobilisation onto different carriers. Such immobilisation can make enzymes more stable, less antigenic and impart a longer circulation lifetime in the organism. This present contribution reviews the data on natural and synthetic carriers used for enzyme immobilisation, chemistry of enzyme binding, in vitro and in vivo properties of immobilised enzymes as well as their clinical use. Immobilised enzymes can be used as drugs for either local or systemic application (including soluble and insoluble immobilised enzymes for thrombolytic therapy, and for the treatment of both malignant diseases and some in-born enzyme deficiences). Immobilised enzymes can be also used for preparation of artificial cells (based on semipermeable microcapsules, liposomes, cells and cell ghosts). Special attention is paid to the problem of using the immobilisation principles for the construction of drug targeting systems (vector protein and antibody immobilisation, enzyme-polymer-vector conjugates, etc.).     

Immobilised enzymes as drugs

The main objective of the work is to present the state of the art in a relatively new field of biotechnology — the use of immobilised enzymes in applied medicine. Enzyme therapy seems to be promising in the treatment of cardiovascular, oncological, intestinal, viral and hereditary diseases. At the same time there exist many limitations for the everyday clinical use of native enzymes. Enzymes are unstable, have a short lifetime in the circulation, cause toxic and immune reactions, and are costly, etc. These drawbacks can be at least partially eliminated by enzyme immobilisation onto different carriers. Such immobilisation can make enzymes more stable, less antigenic and impart a longer circulation lifetime in the organism. This present contribution reviews the data on natural and synthetic carriers used for enzyme immobilisation, chemistry of enzyme binding, in vitro and in vivo properties of immobilised enzymes as well as their clinical use. Immobilised enzymes can be used as drugs for either local or systemic application (including soluble and insoluble immobilised enzymes for thrombolytic therapy, and for the treatment of both malignant diseases and some in-born enzyme deficiences). Immobilised enzymes can be also used for preparation of artificial cells (based on semipermeable microcapsules, liposomes, cells and cell ghosts). Special attention is paid to the problem of using the immobilisation principles for the construction of drug targeting systems (vector protein and antibody immobilisation, enzyme-polymer-vector conjugates, etc.).     

Protein structure prediction in structure based drug design

The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.     

Site-directed structure generation by fragment-joining

Summary Recently, several computer programs for de novo ligand design have been described that construct novel molecules by combining several fragments into one molecule. The present review discusses the advantages and disadvantages of this fragment-based approach to de novo design. The computer program LUDI for automated structure-based ligand design is described in some detail. This program constructs possible new ligands for a given protein of known three-dimensional structure. In addition, LUDI can also be used for 3D database searching. LUDI is based upon rules about energetically favorable nonbonded contact geometries between functional groups of the protein and the ligand which are derived from a statistical analysis of crystal packings of organic molecules. All putative ligands retrieved or constructed by LUDI are scored by a simple scoring function that was fitted to experimentally determined binding constants of protein-ligand complexes. LUDI is a fast program that is suitable for interactive usage.     

Detection and traceability of genetically modified organisms in the food production chain.

Both labelling and traceability of genetically modified organisms are current issues that are considered in trade and regulation. Currently, labelling of genetically modified foods containing detectable transgenic material is required by EU legislation. A proposed package of legislation would extend this labelling to foods without any traces of transgenics. These new legislations would also impose labelling and a traceability system based on documentation throughout the food and feed manufacture system. The regulatory issues of risk analysis and labelling are currently harmonised by Codex Alimentarius. The implementation and maintenance of the regulations necessitates sampling protocols and analytical methodologies that allow for accurate determination of the content of genetically modified organisms within a food and feed sample. Current methodologies for the analysis of genetically modified organisms are focused on either one of two targets, the transgenic DNA inserted- or the novel protein(s) expressed- in a genetically modified product. For most DNA-based detection methods, the polymerase chain reaction is employed. Items that need consideration in the use of DNA-based detection methods include the specificity, sensitivity, matrix effects, internal reference DNA, availability of external reference materials, hemizygosity versus homozygosity, extrachromosomal DNA, and international harmonisation. For most protein-based methods, enzyme-linked immunosorbent assays with antibodies binding the novel protein are employed. Consideration should be given to the selection of the antigen bound by the antibody, accuracy, validation, and matrix effects. Currently, validation of detection methods for analysis of genetically modified organisms is taking place. In addition, new methodologies are developed, including the use of microarrays, mass spectrometry, and surface plasmon resonance. Challenges for GMO detection include the detection of transgenic material in materials with varying chromosome numbers. The existing and proposed regulatory EU requirements for traceability of genetically modified products fit within a broader tendency towards traceability of foods in general and, commercially, towards products that can be distinguished from each other. Traceability systems document the history of a product and may serve the purpose of both marketing and health protection. In this framework, segregation and identity preservation systems allow for the separation of genetically modified and non-modified products from "farm to fork". Implementation of these systems comes with specific technical requirements for each particular step of the food processing chain. In addition, the feasibility of traceability systems depends on a number of factors, including unique identifiers for each genetically modified product, detection methods, permissible levels of contamination, and financial costs. In conclusion, progress has been achieved in the field of sampling, detection, and traceability of genetically modified products, while some issues remain to be solved. For success, much will depend on the threshold level for adventitious contamination set by legislation.     

Detection methods of microsphere based single-step bioaffinity and in vitro diagnostics assays

Microspheres provide a solid phase substrate for bioaffinity binding similar to the walls of traditional test tubes and the wells of microtiter plates. The coated microsphere concentrates analyte molecules in the reaction volume on its surface. When the bioaffinity binding reaction has reached an equilibrium, the local concentration of the analyte in close proximity of the microsphere is orders of magnitude higher than the concentration of the analyte in the total reaction volume. The preparation and quality control of microspheres coated with bioactive material is less costly and labour intensive when compared to test tube or microwell plate coating procedures. In addition, the cost for logistics and transportation of microsphere reagents is lower than that of coated tubes or plates. Moreover, microspheres can be easily used in miniaturised assay formats and several different detection schemes can be employed in the measurement of microsphere-based assays. Several different types of microspheres are commercially available. The microspheres can be manufactured in different sizes from many materials, such as polystyrene, acrylate, and glass. The surface of the microspheres can be activated to enable covalent binding of biomolecules. Further, the microspheres may contain internal fluorochrome or magnetic material, for identification or separation purposes. In this paper we review different assay formats for single-step measurement of bioaffinity assays employing microspheres. The term single-step is used to describe assays where all reagents and the sample are mixed, incubated and measured without separate washing steps.     

铅对发育脑纹状体毒蕈碱和多巴胺受体的影响

母鼠从受孕d0至分娩后d21连续饮用含300和1000ppm的铅水。新生大鼠出生后d21处死。结果表明,血和纹状体铅含量明显增加;在1000ppm组,DNA,RNA降低和蛋白质/DNA比值升高;纹状体DA含量亦减少。铅不影响[~3H]spiperone与纹状体DA受体的特异结合。但影响[~3H]QNB与MACh受体的特异结合,受体数目增加,亲和力未变,提示脑纹状体MACh受体功能状态与铅含量有关。铅影响发育脑纹状体的这两种受体的相互平衡,可能是铅对仔代神经毒性的原因之一。     

Applicability of Computational Systems Biology in Toxicology

Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search. However, computational systems biology offers more advantages than providing a high‐throughput literature search; it may form the basis for establishment of hypotheses on potential links between environmental chemicals and human diseases, which would be very difficult to establish experimentally. This is possible due to the existence of comprehensive databases containing information on networks of human protein–protein interactions and protein–disease associations. Experimentally determined targets of the specific chemical of interest can be fed into these networks to obtain additional information that can be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method in the hypothesis‐generating phase of toxicological research.     

Protein Microarrays: Novel Developments and Applications

Protein microarray technology possesses some of the greatest potential for providing direct information on protein function and potential drug targets. For example, functional protein microarrays are ideal tools suited for the mapping of biological pathways. They can be used to study most major types of interactions and enzymatic activities that take place in biochemical pathways and have been used for the analysis of simultaneous multiple biomolecular interactions involving protein-protein, protein-lipid, protein-DNA and protein-small molecule interactions. Because of this unique ability to analyze many kinds of molecular interactions en masse, the requirement of very small sample amount and the potential to be miniaturized and automated, protein microarrays are extremely well suited for protein profiling, drug discovery, drug target identification and clinical prognosis and diagnosis. The aim of this review is to summarize the most recent developments in the production, applications and analysis of protein microarrays.     

RNAi versus small molecules: different mechanisms and specificities can lead to different outcomes

The methodology of RNA interference (RNAi) arrived on the scene of mammalian systems research in 2001. Since that time, there has been widespread use of this technology in both academic and industrial settings. RNAi and small molecules were initially considered as equivalent methods for inhibiting protein activity within cells, but as our understanding of the mechanism of RNAi has improved, it has become apparent that differences in their cellular mechanisms have unexpected consequences. There can be profound differences in the phenotypic outcomes of treatment with RNAi versus small molecules. This review discusses the similarities, as well as the predicted differences between RNAi and small molecule effects on therapeutic paradigms and drug discovery.     

Privileged molecules for protein binding identified from NMR-based screening

A statistical analysis of NMR-derived binding data on 11 protein targets was performed to identify molecular motifs that are preferred for protein binding. The analysis indicates that compounds which contain a biphenyl substructure preferentially bind to a wide range of proteins and that high levels of specificity (>250-fold) can be achieved even for these small molecules. These results suggest that high-throughput screening libraries that are enriched with biphenyl-containing compounds can be expected to have increased chances of yielding high-affinity ligands for proteins, and they suggest that the biphenyl can be utilized as a template for the discovery and design of therapeutics with high affinity and specificity for a broad range of protein targets.     

Toward a more efficient handling of conformational flexibility in computer-assisted modelling of drug molecules

Summary Several computational search techniques are described to map the conformation space of flexible organic molecules. A vast multiplicity of geometries is produced that has to be minimized according to a particular energy function. Comparative studies on a nine-membered cyclic lactam are taken as an example. They show that thoroughly tailored search conditions can obtain roughly comparable search efficiencies. Out of the vast multiplicity of geometrically possible and computationally accessible conformers, only a limited number will be of relevance for the problem under consideration. In ligand design for drug discovery, a relative energy ranking determined on isolated conformers is only of limited use for the selection of biologically relevant conformers. This is due to an unsatisfactory transferability of energy scales between different energy functions and the strong modulation of conformational energies of isolated molecules once exposed to a structured molecular environment. A knowledge-based approach, using torsionangle libraries as retrieved for common fragments in small-molecule crystal structures, allows one to map more efficiently the biologically relevant part of conformation space. The relevance of these libraries for the conditions at the binding pocket of a protein is evidenced by experimental data. Sets of well-distributed conformers can be used to compare different drug molecules binding to common targets. Such comparisons reveal new modes of structural superposition of the molecules and consideration of their physicochemical properties leads to interesting pharmacophore hypotheses. They indicate possible binding geometries at the recognition site of a protein and highlight the structural similarities and differences that correlate with changes in the biological properties. Comparisons of GP IIb/IIIa receptor antagonists and of thrombin inhibitors are discussed.This paper is dedicated to Prof. Dr. Richard Neidlein (University of Heidelberg, Heidelberg, Germany) on the occasion of his 65th birthday.     

Volarea – A Bioinformatics Tool to Calculate the Surface Area and the Volume of Molecular Systems

We have developed a computer program named ‘VolArea’ that allows for a rapid and fully automated analysis of molecular structures. The software calculates the surface area and the volume of molecular structures, as well as the volume of molecular cavities. The surface area facility can be used to calculate the solvent‐exposed surface area of a molecule or the contact area between two molecules. The volume algorithm can be used to predict not only the space occupied by any molecular structure, but also the volume of cavities, such as tunnels or clefts. The software finds wide application in the characterization of systems, such as protein/ligand complexes, enzyme active sites, protein/protein interfaces, enzyme channels, membrane pores, solvent tunnels, among others. Some examples are given to illustrate its potential. VolArea is as a plug‐in of the widely distributed software Visual Molecular Dynamics (VMD) and is freely available at http://www.fc.up.pt/PortoBioComp/Software/Volarea/Home.html .     

Fast liquid chromatographic method to determine compounds binding to human serum albumin

A fast gradient HPLC method (cycle time 15 min) has been developed to determine Human Serum Albumin (HSA) binding of discovery compounds using chemically bonded protein stationary phases. The 2- propanol concentration is increased from 0 to 25% in 3 minutes, thus allowing strongly bond compounds to elute within the 15 minutes. The HSA binding values were derived from the logarithmic values of the gradient retention times that were converted to logarithm of the equilibrium constants (logK HSA) using a calibration set of molecules. The logK HSA values for the calibration set of molecules have been derived from literature values of the % plasma protein binding. The method is fully automated and it has been used for lead optimization in more than 20 projects. The obtained HSA binding data on more than 4000 compounds were suitable to set up global and project specific quantitative structure binding relationships that helped compound design in the early drug discovery settings. The method has been validated using literature plasma protein binding data of 70 known drug molecules. It was shown that compound lipophilicity dominates the HSA binding, however compounds binding to a specific binding site show stronger HSA binding that can be expected from their lipophilicity values. The solvation equation approach has been used to characterize the non-specific lipophilic binding ability of HSA. Based on our approach we can identify compounds with specific and non-specific binding.     

Studying Cellular Processes and Detecting Disease with Protein Microarrays

Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications, and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.     

Studying cellular processes and detecting disease with protein microarrays

Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications, and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.     

Transient pockets on protein surfaces involved in protein-protein interaction

A new pocket detection protocol successfully identified transient pockets on the protein surfaces of BCL-XL, IL-2, and MDM2. Because the native inhibitor binding pocket was absent or only partly detectable in the unbound proteins, these crystal structures were used as starting points for 10 ns long molecular dynamics simulations. Trajectory snapshots were scanned for cavities on the protein surface using the program PASS. The detected cavities were clustered to determine several distinct transient pockets. They all opened within 2.5 ps, and most of them appeared multiple times. All three systems gave similar results overall. At the native binding site, pockets of similar size compared with a known inhibitor bound could be observed for all three systems. AutoDock could successfully place inhibitor molecules into these transient pockets with less than 2 A rms deviation from their crystal structures, suggesting this protocol as a viable tool to identify transient ligand binding pockets on protein surfaces.     

Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 3. The free energy contribution of structural water molecules in HIV-1 protease complexes

Structural water molecules within protein active sites are relevant for ligand-protein recognition because they modify the active site geometry and contribute to binding affinity. In this work an analysis of the interactions between 23 ligands and dimeric HIV-1 protease is reported. The X-ray structures of these complexes show the presence of four types of structural water molecules: water 301 (on the symmetry axis), water 313, water 313bis, and peripheral waters. Except for water 301, these are generally complemented with a symmetry-related set. The GRID program was used both for checking water locations and for placing water molecules that appear to be missing from the complexes due to crystallographic uncertainty. Hydropathic analysis of the energetic contributions using HINT indicates a significant improvement of the correlation between HINT scores and the experimentally determined binding constants when the appropriate bridging water molecules are taken into account. In the absence of water r2 = 0.30 with a standard error of +/- 1.30 kcal mol(-1) and when the energetic contributions of the constrained waters are included r2 = 0.61 with a standard error of +/- 0.98 kcal mol(-1). HINT was shown to be able to map quantitatively the contribution of individual structural waters to binding energy. The order of relevance for the various types of water is water 301 > water 313 > water 313bis > peripheral waters. Thus, to obtain the most reliable free energy predictions, the contributions of structural water molecules should be included. However, care must be taken to include the effects of water molecules that add information value and not just noise.