Characterization of FITC-conjugated lectin binding to Candida albicans

Avidity of yeast and hyphal forms of Candida albicans for FITC-conjugated lectins was determined by flow cytometry and digital microscopy. Yeast phase cells bound Con A, a lectin with marked affinity for mannose, irrespective of growth phase, yet demonstrated little avidity for WGA and SBA. Yeast phase cell avidity for mannose-specific lectins was characterized through determination of FITC-conjugated Con A, LcH, PSA and GNA binding and subsequent calculation of Bmax, EC50 and Hn values. Such an approach, through comparison among FITC-conjugated lectins of differing specific activities, furnishes further insight into exposed outer cell wall mannose moieties. The rank order of lectin affinity as defined by EC50 values was GNA > Con A > LcH > PSA. Values for Hn suggest that lectins predominantly bind to a single receptor class, the relative abundance of which as defined by Bmax values was PSA > GNA > Con A > LcH. Hyphal surfaces in common with yeast phase cells demonstrated marked avidity for FITC-Con A, however, fluorescence of Candida morphological forms differed significantly, indicative of varying outer cell wall mannose exposure.

In vitro and in vivo activities of AM-112, a novel oxapenem

AM-112[1′R,5R,6R)-3-(4-amino-1,1-dimethyl-butyl)-6-(1′- hydroxyethyl)oxapenem-3-carboxylatel is a novel oxapenem compound which possesses potent β-lactamase-inhibitory properties. Fifty-percent inhibitory concentrations (IC50s) of AM-112 for class A enzymes were between 0.16 and 2.24 μM for three enzymes, compared to IC50s of 0.008 to 0.12 μM for clavulanic acid. Against class C and class D enzymes, however, the activity of AM-112 was between 1,000- and 100,000-fold greater than that of clavulanic acid. AM-112 had affinity for the penicillin-binding proteins (PBPs) of Escherichia coli DC0, with PBP2 being inhibited by the lowest concentration of AM-112 tested, 0.1 μg/ml. Ceftazidime was combined with AM-112 at 1:1 and 2:1 ratios in MIC determination studies against a panel of β-lactamase-producing organisms. These studies demonstrated that AM-112 was effective at protecting ceftazidime against extended-spectrum β-lactamase-producing strains and derepressed class C enzyme producers, reducing ceftazidime MICs by 16- and 2,048-fold. Similar results were obtained when AM-112 was combined with ceftriaxone, cefoperazone, or cefepime in a 1:2 ratio. Protection of ceftazidime with AM-112 was maintained against Enterobacter cloacae P99 and Klebsiella pneumoniae SHV-5 in a murine intraperitoneal sepsis model. The 50% effective dose of ceftazidime against E. cloacae P99 and K. pneumoniae SHV-5 was reduced from >100 and 160 mg/kg of body weight to 2 and 33.6 mg/kg, respectively, when it was combined with AM-112 at a 1:1 ratio. AM-112 demonstrates potential as a new β-lactamase inhibitor.

Self-association of calcium-binding protein S100A4 and metastasis

Elevated levels of the calcium-binding protein S100A4 promote metastasis and in carcinoma cells are associated with reduced survival of cancer patients. S100A4 interacts with target proteins that affect a number of activities associated with metastatic cells. However, it is not known how many of these interactions are required for S100A4-promoted metastasis, thus hampering the design of specific inhibitors of S100A4-induced metastasis. Intracellular S100A4 exists as a homodimer through previously identified, well conserved, predominantly hydrophobic key contacts between the subunits. Here it is shown that mutating just one key residue, phenylalanine 72, to alanine is sufficient to reduce the metastasis-promoting activity of S100A4 to 50% that of the wild type protein, and just 2 or 3 specific mutations reduces the metastasis-promoting activity of S100A4 to less than 20% that of the wild type protein. These mutations inhibit the self-association of S100A4 in vivo and reduce markedly the affinity of S100A4 for at least two of its protein targets, a recombinant fragment of non-muscle myosin heavy chain isoform A, and p53. Inhibition of the self-association of S100 proteins might be a novel means of inhibiting their metastasis-promoting activities.

Selective inhibition of the human tie-1 promoter with triplex-forming oligonucleotides targeted to ets binding sites

The Tie receptors (Tie-1 and Tie-2/Tek) are essential for angiogenesis and vascular remodeling/integrity. Tie receptors are up-regulated in tumor-associated endothelium, and their inhibition disrupts angiogenesis and can prevent tumor growth as a consequence. To investigate the potential of anti-gene approaches to inhibit tie gene expression for anti-angiogenic therapy, we have examined triple-helical (triplex) DNA formation at 2 tandem Ets transcription factor binding motifs (designated E-1 and E-2) in the human tie-1 promoter. Various tie-1 promoter deletion/mutation luciferase reporter constructs were generated and transfected into endothelial cells to examine the relative activities of E-1 and E-2. The binding of antiparallel and parallel (control) purine motif oligonucleotides (21-22 bp) targeted to E-1 and E-2 was assessed by plasmid DNA fragment binding and electrophoretic mobility shift assays. Triplex-forming oligonucleotides were incubated with tie-1 reporter constructs and transfected into endothelial cells to determine their activity. The Ets binding motifs in the E-1 sequence were essential for human tie-1 promoter activity in endothelial cells, whereas the deletion of E-2 had no effect. Antiparallel purine motif oligonucleotides targeted at E-1 or E-2 selectively formed strong triplex DNA (K(d) approximately 10(-7) M) at 37 degrees C. Transfection of tie-1 reporter constructs with triplex DNA at E-1, but not E-2, specifically inhibited tie-1 promoter activity by up to 75% compared with control oligonucleotides in endothelial cells. As similar multiple Ets binding sites are important for the regulation of several endothelial-restricted genes, this approach may have broad therapeutic potential for cancer and other pathologies involving endothelial proliferation/dysfunction.

Discovering properties of new DNA-binding activity of proteins

Protein-DNA interactions are an essential feature in the genetic activities of life, and the ability to predict and manipulate such interactions has applications in a wide range of fields. This Thesis presents the methods of modelling the properties of protein-DNA interactions. In particular, it investigates the methods of visualising and predicting the specificity of DNA-binding Cys2His2 zinc finger interaction. The Cys2His2 zinc finger proteins interact via their individual fingers to base pair subsites on the target DNA. Four key residue positions on the a- helix of the zinc fingers make non-covalent interactions with the DNA with sequence specificity. Mutating these key residues generates combinatorial possibilities that could potentially bind to any DNA segment of interest. Many attempts have been made to predict the binding interaction using structural and chemical information, but with only limited success. The most important contribution of the thesis is that the developed model allows for the binding properties of a given protein-DNA binding to be visualised in relation to other protein-DNA combinations without having to explicitly physically model the specific protein molecule and specific DNA sequence. To prove this, various databases were generated, including a synthetic database which includes all possible combinations of the DNA-binding Cys2His2 zinc finger interactions. NeuroScale, a topographic visualisation technique, is exploited to represent the geometric structures of the protein-DNA interactions by measuring dissimilarity between the data points. In order to verify the effect of visualisation on understanding the binding properties of the DNA-binding Cys2His2 zinc finger interaction, various prediction models are constructed by using both the high dimensional original data and the represented data in low dimensional feature space. Finally, novel data sets are studied through the selected visualisation models based on the experimental DNA-zinc finger protein database. The result of the NeuroScale projection shows that different dissimilarity representations give distinctive structural groupings, but clustering in biologically-interesting ways. This method can be used to forecast the physiochemical properties of the novel proteins which may be beneficial for therapeutic purposes involving genome targeting in general.

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

Background: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation. There have been several computational methods proposed in the literature to deal with the DNA-binding protein identification. However, most of them can't provide an invaluable knowledge base for our understanding of DNA-protein interactions. Results: We firstly presented a new protein sequence encoding method called PSSM Distance Transformation, and then constructed a DNA-binding protein identification method (SVM-PSSM-DT) by combining PSSM Distance Transformation with support vector machine (SVM). First, the PSSM profiles are generated by using the PSI-BLAST program to search the non-redundant (NR) database. Next, the PSSM profiles are transformed into uniform numeric representations appropriately by distance transformation scheme. Lastly, the resulting uniform numeric representations are inputted into a SVM classifier for prediction. Thus whether a sequence can bind to DNA or not can be determined. In benchmark test on 525 DNA-binding and 550 non DNA-binding proteins using jackknife validation, the present model achieved an ACC of 79.96%, MCC of 0.622 and AUC of 86.50%. This performance is considerably better than most of the existing state-of-the-art predictive methods. When tested on a recently constructed independent dataset PDB186, SVM-PSSM-DT also achieved the best performance with ACC of 80.00%, MCC of 0.647 and AUC of 87.40%, and outperformed some existing state-of-the-art methods. Conclusions: The experiment results demonstrate that PSSM Distance Transformation is an available protein sequence encoding method and SVM-PSSM-DT is a useful tool for identifying the DNA-binding proteins. A user-friendly web-server of SVM-PSSM-DT was constructed, which is freely accessible to the public at the web-site on http://bioinformatics.hitsz.edu.cn/PSSM-DT/.