Investigation on the Interactions of NiCR and NiCR-2H with DNA

5-Substituted Flavones-Another Class of Potent Triplex DNA-Specific Ligands as Antigene Enhancers

In the field of drug development, the quest for novel compounds that bind to DNA with high affinity and specificity never ends. In the present work, we report the newest development in this field, namely, triplex DNA-specific binding ligands based on the 5-substituted flavone scaffold in our lab. Biophysical studies showed that the newly synthesized flavone derivatives (depending on the side chains) bind to triplex DNA with binding affinities better than or similar to 5-substituted 3,3',4',7-tetramethoxyflavonoids. These compounds selectively stabilize triplex DNA while having little effect on duplex DNA, as verified by various biophysical methods. A detailed structural analysis suggested that the binding of these compounds to triplex DNA depends on the type of amino groups in the side chains and the length of the side chains. Viscosity studies suggested that these ligands bind to triplex DNA via intercalation. A representative ligand, compound 4b, showed a positive inhibitory effect on the activity of a restriction endonuclease (DraI) via ligand-mediated triplex formation. Several of these compounds exhibited excellent cytotoxicity toward various cancer cell lines (HT-29, HCT116, and HL-60), as indicated by the MTT assay. The work presented here is part of a continued effort from our laboratory to explore the novel structural motifs of natural product flavonoids for the development of triplex-specific ligands as antigene enhancers.

Application of Ammonium Persulfate for Selective Oxidation of Guanines for Nucleic Acid Sequencing

Nucleic acids can be sequenced by a chemical procedure that partially damages the nucleotide positions at their base repetition. Many methods have been reported for the selective recognition of guanine. The accurate identification of guanine in both single and double regions of DNA and RNA remains a challenging task. Herein, we present a new, non-toxic and simple method for the selective recognition of guanine in both DNA and RNA sequences via ammonium persulfate modification. This strategy can be further successfully applied to the detection of 5-methylcytosine by using PCR.

Specific recognition of guanines in non-duplex regions of nucleic acids with potassium tungstate and hydrogen peroxide

Structural features of nucleic acids have become an integral part of current biomedical research. Highly selective and readily performed methods with little toxicity that target guanosines in non-duplex nucleic acids are needed, which led us to search for an effective agent for guanosine sequencing. Treatment of DNA or RNA with potassium tungstate and hydrogen peroxide produced damaged guanosines in DNA or RNA sequences. The damaged guanosines in non-duplex DNA could be cleaved by hot piperidine. Similarly, damaged guanosines in non-duplex RNA could be cleaved by aniline acetate. We could identify structural features of nucleic acid using this strategy instead of dimethyl sulphate and Ribonuclease T1.

Predicting antigenicity of proteins in a bacterial proteome; a protein microarray and naïve Bayes classification approach

Discovery of novel antigens associated with infectious diseases is fundamental to the development of serodiagnostic tests and protein subunit vaccines against existing and emerging pathogens. Efforts to predict antigenicity have relied on a few computational algorithms predicting signal peptide sequences (SignalP), transmembrane domains, or subcellular localization (pSort). An empirical protein microarray approach was developed to scan the entire proteome of any infectious microorganism and empirically determine immunoglobulin reactivity against all the antigens from a microorganism in infected individuals. The current database from this activity contains quantitative antibody reactivity data against 35,000 proteins derived from 25 infectious microorganisms and more than 30 million data points derived from 15,000 patient sera. Interrogation of these data sets has revealed ten proteomic features that are associated with antigenicity, allowing an in silico protein sequence and functional annotation based approach to triage the least likely antigenic proteins from those that are more likely to be antigenic. The first iteration of this approach applied to Brucella melitensis predicted 37% of the bacterial proteome containing 91% of the antigens empirically identified by probing proteome microarrays. In this study, we describe a naïve Bayes classification approach that can be used to assign a relative score to the likelihood that an antigen will be immunoreactive and serodiagnostic in a bacterial proteome. This algorithm predicted 20% of the B. melitensis proteome including 91% of the serodiagnostic antigens, a nearly twofold improvement in specificity of the predictor. These results give us confidence that further development of this approach will lead to further improvements in the sensitivity and specificity of this in silico predictive algorithm.