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A novel optical-based high-throughput screening technology has been developed for increasing the rate of discovering chemical leads against RNA targets. SCAN^™ ( Screen for Compounds with Affinity for Nucleic Acids) is an affinity-based assay that identifies small molecules that bind and recognize structured RNA elements. This technology provides the opportunity to conduct high-throughput screening of a new class of targets—RNA. SCAN^™ offers many attractive features including a simple homogeneous format, low screening costs, and the ability to use common laboratory equipment. A SCAN^™ assay was developed for the HCV IRES Loop IIId RNA domain. A high-throughput screen of our entire compound library resulted in the identification of small molecule ligands that bind to Loop IIId. The Z′ values were greater than 0.8, showing this to be a robust high-throughput screening assay. A correlation between SCAN^™ EC₅₀ and K_D values is reported suggesting the ability to use the assay for compound optimization. (Journal of Biomolecular Screening 2009:219-229)

26:T4e9,

For hit selection in genome-scale RNAi research, we do not want to miss small interfering RNAs (siRNAs) with large effects; meanwhile, we do not want to include siRNAs with small or no effects in the list of selected hits. There is a strong need to control both the false-negative rate (FNR), in which the siRNAs with large effects are not selected as hits, and the restricted false-positive rate (RFPR), in which the siRNAs with no or small effects are selected as hits. An error control method based on strictly standardized mean difference (SSMD) has been proposed to maintain a flexible and balanced control of FNR and RFPR. In this article, the authors illustrate how to maintain a balanced control of both FNR and RFPR using the plot of error rate versus SSMD as well as how to keep high powers using the plot of power versus SSMD in RNAi high-throughput screening experiments. There are relationships among FNR, RFPR, Type I and II errors, and power. Understanding the differences and links among these concepts is essential for people to use statistical terminology correctly and effectively for data analysis in genome-scale RNAi screens. Here the authors explore these differences and links. (Journal of Biomolecular Screening 2009:230-238)

27:T4f2,

Although embryonic stem cell (ESC)—derived cardiomyocytes may be a powerful tool in drug discovery, their potential has not yet been fully explored. Nor has a detailed comparison with adult heart tissue been performed. We have