An application of combinatorial optimization in the printing industry

Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The print- ing technology used yields a number of specific constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technologi- cal and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.

Conformational diversity versus nucleic acid triplex stability, a combinatorial study

The stability of a triple helix formed between a DNA duplex and an incoming oligonucleotide strand strongly depends on the solvent conditions and on intrinsic chemical and conformational factors. Attempts to increase triple helix stability in the past included chemical modification of the backbone, sugar ring, and bases in the third strand. However, the predictive power of such modifications is still rather poor. We therefore developed a method that allows for rapid screening of conformationally diverse third strand oligonucleotides for triplex stability in the parallel pairing motif to a given DNA double helix sequence. Combinatorial libraries of oligonucleotides of the requisite (fixed) base composition and length that vary in their sugar unit (ribose or deoxyribose) at each position were generated. After affinity chromatography against their corresponding immobilized DNA target duplex, utilizing a temperature gradient as the selection criterion, the oligonucleotides forming the most stable triple helices were selected and characterized by physicochemical methods. Thus, a series of oligonucleotides were identified that allowed us to define basic rules for triple helix stability in this conformationally diverse system. It was found that ribocytidines in the third strand increase triplex stability relative to deoxyribocytidines independently of the neighboring bases and position along the strand. However, remarkable sequence-dependent differences in stability were found for (deoxy)thymidines and uridines

Exploring Multi-Component Superconducting Compounds by a High-Pressure Method and Ceramic Combinatorial Chemistry

In this short review, we provide some new insights into the material synthesis and characterization of modern multi-component superconducting oxides. Two different approaches such as the high-pressure, high-temperature method and ceramic combinatorial chemistry will be reported with application to several typical examples. First, we highlight the key role of the extreme conditions in the growth of Fe-based superconductors, where a careful control of the composition-structure relation is vital for understanding the microscopic physics. The availability of high-quality LnFeAsO (Ln = lanthanide) single crystals with substitution of O by F, Sm by Th, Fe by Co, and As by P allowed us to measure intrinsic and anisotropic superconducting properties such as Hc2, Jc. Furthermore, we demonstrate that combinatorial ceramic chemistry is an efficient way to search for new superconducting compounds. A single-sample synthesis concept based on multi-element ceramic mixtures can produce a variety of local products. Such a system needs local probe analyses and separation techniques to identify compounds of interest. We present the results obtained from random mixtures of Ca, Sr, Ba, La, Zr, Pb, Tl, Y, Bi, and Cu oxides reacted at different conditions. By adding Zr but removing Tl, Y, and Bi, the bulk state superconductivity got enhanced up to about 122 K.

DARPins recognizing the tumor-associated antigen EpCAM selected by phage and ribosome display and engineered for multivalency

Designed Ankyrin Repeat Proteins (DARPins) represent a novel class of binding molecules. Their favorable biophysical properties such as high affinity, stability and expression yields make them ideal candidates for tumor targeting. Here, we describe the selection of DARPins specific for the tumor-associated antigen epithelial cell adhesion molecule (EpCAM), an approved therapeutic target on solid tumors. We selected DARPins from combinatorial libraries by both phage display and ribosome display and compared their binding on tumor cells. By further rounds of random mutagenesis and ribosome display selection, binders with picomolar affinity were obtained that were entirely monomeric and could be expressed at high yields in the cytoplasm of Escherichia coli. One of the binders, denoted Ec1, bound to EpCAM with picomolar affinity (K(d)=68 pM), and another selected DARPin (Ac2) recognized a different epitope on EpCAM. Through the use of a variety of bivalent and tetravalent arrangements with these DARPins, the off-rate on cells was further improved by up to 47-fold. All EpCAM-specific DARPins were efficiently internalized by receptor-mediated endocytosis, which is essential for intracellular delivery of anticancer agents to tumor cells. Thus, using EpCAM as a target, we provide evidence that DARPins can be conveniently selected and rationally engineered to high-affinity binders of various formats for tumor targeting.

Anti-idiotypic Fab Fragments Image a Conserved N-terminal Epitope Patch of Grass Pollen Allergen Phl p 1

BACKGROUND AND AIMS: Naturally occurring anti-idiotypic antibodies structurally mimic the original antibody epitope. Anti-idiotypes, therefore, are interesting tools for the portrayal of conformational B-cell epitopes of allergens. In this study we used this strategy particularly for major timothy grass pollen (Phleum pratense) allergen Phl p 1. METHODS AND RESULTS: We used a combinatorial phage display library constructed from the peripheral IgG repertoire of a grass pollen allergic patient which was supposed to contain anti-idiotypic Fab specificities. Using purified anti-Phl p 1 IgG for biopanning, several Fab displaying phage clones could be isolated. 100 amplified colonies were screened for their binding capacity to anti-Phl p 1-specific antibodies, finally resulting in four distinct Fab clones according to sequence analysis. Interestingly, heavy chains of all clones derived from the same germ line sequence and showed high homology in their CDRs. Projecting their sequence information on the surface of the natural allergen Phl p 1 (PDB ID: 1N10) indicated matches on the N-terminal domain of the homo-dimeric allergen, including the bridging region between the two monomers. The resulting epitope patches were formed by spatially distant sections of the primary allergen sequence. CONCLUSION: In this study we report that anti-idiotypic specificities towards anti-Phl p 1 IgG, selected from a Fab library of a grass pollen allergic patient, mimic a conformational epitope patch being distinct from a previously reported IgE epitope area.

A sensitized RNA interference screen identifies a novel role for the PI3K p110γ isoform in medulloblastoma cell proliferation and chemoresistance

Medulloblastoma is the most common malignant brain tumor in children and is associated with a poor outcome. We were interested in gaining further insight into the potential of targeting the human kinome as a novel approach to sensitize medulloblastoma to chemotherapeutic agents. A library of small interfering RNA (siRNA) was used to downregulate the known human protein and lipid kinases in medulloblastoma cell lines. The analysis of cell proliferation, in the presence or absence of a low dose of cisplatin after siRNA transfection, identified new protein and lipid kinases involved in medulloblastoma chemoresistance. PLK1 (polo-like kinase 1) was identified as a kinase involved in proliferation in medulloblastoma cell lines. Moreover, a set of 6 genes comprising ATR, LYK5, MPP2, PIK3CG, PIK4CA, and WNK4 were identified as contributing to both cell proliferation and resistance to cisplatin treatment in medulloblastoma cells. An analysis of the expression of the 6 target genes in primary medulloblastoma tumor samples and cell lines revealed overexpression of LYK5 and PIK3CG. The results of the siRNA screen were validated by target inhibition with specific pharmacological inhibitors. A pharmacological inhibitor of p110γ (encoded by PIK3CG) impaired cell proliferation in medulloblastoma cell lines and sensitized the cells to cisplatin treatment. Together, our data show that the p110γ phosphoinositide 3-kinase isoform is a novel target for combinatorial therapies in medulloblastoma.

Phosphatidylinositol 3-kinase isoforms as novel drug targets

Phosphatidylinositol 3-kinases (PI3Ks) are key molecules in the signal transduction pathways initiated by the binding of extracellular signals to their cell surface receptors. The PI3K family of enzymes comprises eight catalytic isoforms subdivided into three classes and control a variety of cellular processes including proliferation, growth, apoptosis, migration and metabolism. Deregulation of the PI3K pathway has been extensively investigated in connection to cancer, but is also involved in other commonly occurring diseases such as chronic inflammation, autoimmunity, allergy, atherosclerosis, cardiovascular and metabolic diseases. The fact that the PI3K pathway is deregulated in a large number of human diseases, and its importance for different cellular responses, makes it an attractive drug target. Pharmacological PI3K inhibitors have played a very important role in studying cellular responses involving these enzymes. Currently, a wide range of selective PI3K inhibitors have been tested in preclinical studies and some have entered clinical trials in oncology. However, due to the complexity of PI3K signaling pathways, developing an effective anti-cancer therapy may be difficult. The biggest challenge in curing cancer patients with various signaling pathway abnormalities is to target multiple components of different signal transduction pathways with mechanism-based combinatorial treatments. In this article we will give an overview of the complex role of PI3K isoforms in human diseases and discuss their potential as drug targets. In addition, we will describe the drugs currently used in clinical trials, as well as promising emerging candidates.

Membrane disrupting antimicrobial peptide dendrimers with multiple amino termini

Antimicrobial peptide dendrimer H1 Leu8(Lys-Leu)4(Lys-Phe)2Lys-LysNH2 (Lys = branching lysine) was identified by screening a 6750-membered combinatorial library by the bead-diffusion assay. Sequence variations also revealed dendrimer bH1 Leu8(Dap-Leu)4(Dap-Phe)2Dap-LysNH2 (Dap = branching 2,3-diaminopropanoic acid) as a more potent analog. H1 and bH1 showed good antimicrobial activities mediated by membrane disruption (MIC = 2–4 μg mL−1 on Bacillus subtilis and Escherichia coli) but low hemolytic activity (MHC = 310 μg mL−1 respectively >2000 μg mL−1).

Dendritic glycopeptides as Pseudomonas aeruginosa biofilm inhibitors, Oral presentation, 32nd European Peptide symposium, Athens, Greece, 2-7 September 2012

Glycopeptide dendrimers as Pseudomonas aeruginosa biofilm inhibitors. Glycopeptide dendrimers are being developed for inhibition of pathogen adhesion to host cells, a process mediated by carbohydrate-lectins interactions. Such compounds could be used in the treatment of infections by pathogenic bacteria such as Pseudomonas aeruginosa that can be resistant to known antibiotics. Pseudomonas aeruginosa produces two lectins, the fucose binding LecB and the galactose binding LecA. Both lectins have been shown to be virulence factors, involved in cell adhesion and biofilms formation. Screening combinatorial libraries of fucosylated peptide dendrimers led to the glycopeptide dendrimer (C-Fuc-LysProLeu)4(LysPheLysIle)2 LysHisIleNH2. This dendrimer binds the lectin LecB with submicromolar IC50 and shows potent inhibition of P. aeruginosa biofilms for both the laboratory strain PAO1 and for clinical isolates [1]. Appending the peptide dendrimer portion of FD2 with galactosy endgroups gave galactosylpeptide dendrimers as potent ligands for LecA which also act as biofilm inhibitors. Structure-activity relationship studies demonstrated that multivalency was essential for strong binding and biofilm inhibition. [2]The results open the way to develop therapeutic agents based on glycopeptide dendrimers. Peptide dendrimers with antimicrobial properties and good cell penetration are other applications of dendritic peptides we are now investigating.

An Urn Model for Cascading Failures on a Lattice

A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.

Identification of pathogen and host-response markers correlated with periodontal disease

BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.

Emerging metabolic targets in the therapy of hematological malignancies

During the last decade, the development of anticancer therapies has focused on targeting neoplastic-related metabolism. Cancer cells display a variety of changes in their metabolism, which enable them to satisfy the high bioenergetic and biosynthetic demands for rapid cell division. One of the crucial alterations is referred to as the "Warburg effect", which involves a metabolic shift from oxidative phosphorylation towards the less efficient glycolysis, independent of the presence of oxygen. Although there are many examples of solid tumors having altered metabolism with high rates of glucose uptake and glycolysis, it was only recently reported that this phenomenon occurs in hematological malignancies. This review presents evidence that targeting the glycolytic pathway at different levels in hematological malignancies can inhibit cancer cell proliferation by restoring normal metabolic conditions. However, to achieve cancer regression, high concentrations of glycolytic inhibitors are used due to limited solubility and biodistribution, which may result in toxicity. Besides using these inhibitors as monotherapies, combinatorial approaches using standard chemotherapeutic agents could display enhanced efficacy at eradicating malignant cells. The identification of the metabolic enzymes critical for hematological cancer cell proliferation and survival appears to be an interesting new approach for the targeted therapy of hematological malignancies.