New insights regarding HCV-NS5A structure/function and indication of genotypic differences

<p>Abstract</p> <p>Background</p> <p>HCV is prevalent throughout the world. It is a major cause of chronic liver disease. There is no effective vaccine and the most common therapy, based on Peginterferon, has a success rate of ~50%. The mechanisms underlying viral resistance have not been elucidated but it has been suggested that both host and virus contribute to therapy outcome. Non-structural 5A (NS5A) protein, a critical virus component, is involved in cellular and viral processes.</p> <p>Methods</p> <p>The present study analyzed structural and functional features of 345 sequences of HCV-NS5A genotypes 1 or 3, using <it>in silico </it>tools.</p> <p>Results</p> <p>There was residue type composition and secondary structure differences between the genotypes. In addition, second structural variance were statistical different for each response group in genotype 3. A motif search indicated conserved glycosylation, phosphorylation and myristoylation sites that could be important in structural stabilization and function. Furthermore, a highly conserved integrin ligation site was identified, and could be linked to nuclear forms of NS5A. ProtFun indicated NS5A to have diverse enzymatic and nonenzymatic activities, participating in a great range of cell functions, with statistical difference between genotypes.</p> <p>Conclusion</p> <p>This study presents new insights into the HCV-NS5A. It is the first study that using bioinformatics tools, suggests differences between genotypes and response to therapy that can be related to NS5A protein features. Therefore, it emphasizes the importance of using bioinformatics tools in viral studies. Data acquired herein will aid in clarifying the structure/function of this protein and in the development of antiviral agents.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe