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em Bucknell University Digital Commons - Pensilvania - USA


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Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Previous work revealed that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat model systems, interacting with an unknown receptor, while peptides smaller than eight amino acids did not inhibit breast cancer. We have shown that the use of replica exchange molecular dynamics predicts structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. These simulations identified smaller peptide analogs with a conserved turn, a β-turn formed in the larger peptides. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used with the experimental information that led to the successful completion of this research.

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In 2011, researchers at Bucknell University and Illinois Wesleyan University compared the search efficacy of Serial Solutions Summon, EBSCO Discovery Service, Google Scholar and conventional library databases. Using a mixed-methods approach, qualitative and quantitative data was gathered on students’ usage of these tools. Regardless of the search system, students exhibited a marked inability to effectively evaluate sources and a heavy reliance on default search settings. On the quantitative benchmarks measured by this study, the EBSCO Discovery Service tool outperformed the other search systems in almost every category. This article describes these results and makes recommendations for libraries considering these tools.