TS-AMIR: a topology string alignment method for intensive rapid protein structure comparison

<p>Abstract</p> <p>Background</p> <p>In structural biology, similarity analysis of protein structure is a crucial step in studying the relationship between proteins. Despite the considerable number of techniques that have been explored within the past two decades, the development of new alternative methods is still an active research area due to the need for high performance tools.</p> <p>Results</p> <p>In this paper, we present TS-AMIR, a Topology String Alignment Method for Intensive Rapid comparison of protein structures. The proposed method works in two stages: In the first stage, the method generates a topology string based on the geometric details of secondary structure elements, and then, utilizes an n-gram modelling technique over entropy concept to capture similarities in these strings. This initial correspondence map between secondary structure elements is submitted to the second stage in order to obtain the alignment at the residue level. Applying the Kabsch method, a heuristic step-by-step algorithm is adopted in the second stage to align the residues, resulting in an optimal rotation matrix and minimized RMSD. The performance of the method was assessed in different information retrieval tests and the results were compared with those of CE and TM-align, representing two geometrical tools, and YAKUSA, 3D-BLAST and SARST as three representatives of linear encoding schemes. It is shown that the method obtains a high running speed similar to that of the linear encoding schemes. In addition, the method runs about 800 and 7200 times faster than TM-align and CE respectively, while maintaining a competitive accuracy with TM-align and CE.</p> <p>Conclusions</p> <p>The experimental results demonstrate that linear encoding techniques are capable of reaching the same high degree of accuracy as that achieved by geometrical methods, while generally running hundreds of times faster than conventional programs.</p

The restorative role of annexin A1 at the blood–brain barrier

Annexin A1 is a potent anti-inflammatory molecule that has been extensively studied in the peripheral immune system, but has not as yet been exploited as a therapeutic target/agent. In the last decade, we have undertaken the study of this molecule in the central nervous system (CNS), focusing particularly on the primary interface between the peripheral body and CNS: the blood–brain barrier. In this review, we provide an overview of the role of this molecule in the brain, with a particular emphasis on its functions in the endothelium of the blood–brain barrier, and the protective actions the molecule may exert in neuroinflammatory, neurovascular and metabolic disease. We focus on the possible new therapeutic avenues opened up by an increased understanding of the role of annexin A1 in the CNS vasculature, and its potential for repairing blood–brain barrier damage in disease and aging

Non-coding RNAs underlying chemoresistance in gastric cancer.

BackgroundGastric cancer (GC) is a major health issue in the Western world. Current clinical imperatives for this disease include the identification of more effective biomarkers to detect GC at early stages and enhance the prevention and treatment of metastatic and chemoresistant GC. The advent of non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long-non coding RNAs (lncRNAs), has led to a better understanding of the mechanisms by which GC cells acquire features of therapy resistance. ncRNAs play critical roles in normal physiology, but their dysregulation has been detected in a variety of cancers, including GC. A subset of ncRNAs is GC-specific, implying their potential application as biomarkers and/or therapeutic targets. Hence, evaluating the specific functions of ncRNAs will help to expand novel treatment options for GC.ConclusionsIn this review, we summarize some of the well-known ncRNAs that play a role in the development and progression of GC. We also review the application of such ncRNAs in clinical diagnostics and trials as potential biomarkers. Obviously, a deeper understanding of the biology and function of ncRNAs underlying chemoresistance can broaden horizons toward the development of personalized therapy against GC