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1.  Structure-based discovery of pyrazolobenzothiazine derivatives as inhibitors of hepatitis C virus replication 
Journal of medicinal chemistry  2013;56(6):2270-2282.
The NS5B RNA-dependent RNA polymerase is an attractive target for the development of novel and selective inhibitors of hepatitis C virus replication. In order to identify novel structural hits as anti-HCV agents, we performed structure-based virtual screening of our in-house library followed by rational drug design, organic synthesis and biological testing. These studies led to the identification of pyrazolobenzothiazine scaffold as a suitable template for obtaining novel anti-HCV agents targeting the NS5B polymerase. The best compound of this series was the meta-fluoro-N-1-phenyl pyrazolobenzothiazine derivative 4a, which exhibited an EC50= 3.6 µM, EC90= 25.6 µM and CC50 > 180 µM in the Huh 9–13 replicon system, thus providing a good starting point for further hit evolution.
doi:10.1021/jm301643a
PMCID: PMC3627225  PMID: 23409936
Hepatitis C virus; RNA-dependent RNA polymerase; structure-based drug discovery; virtual screening; NS5B inhibitors; pyrazolobenzothiazines
2.  Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data 
PLoS ONE  2009;4(6):e6057.
Background
Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells.
Principal Finding
Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection.
Conclusion
Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.
doi:10.1371/journal.pone.0006057
PMCID: PMC2699026  PMID: 19557126

Results 1-2 (2)