scholarly journals Bioinformatics for Membrane Lipid Simulations: Models, Computational Methods, and Web Server Tools

Author(s):  
S.W. Leong ◽  
T.S. Lim ◽  
Y.S. Choong
2020 ◽  
Vol 16 (5) ◽  
pp. 620-625 ◽  
Author(s):  
Wei Chen ◽  
Pengmian Feng ◽  
Fulei Nie

Background: Tuberculosis is one of the biggest threats to human health. Recent studies have demonstrated that anti-tubercular peptides are promising candidates for the discovery of new anti-tubercular drugs. Since experimental methods are still labor intensive, it is highly desirable to develop automatic computational methods to identify anti-tubercular peptides from the huge amount of natural and synthetic peptides. Hence, accurate and fast computational methods are highly needed. Methods and Results: In this study, a support vector machine based method was proposed to identify anti-tubercular peptides, in which the peptides were encoded by using the optimal g-gap dipeptide compositions. Comparative results demonstrated that our method outperforms existing methods on the same benchmark dataset. For the convenience of scientific community, a freely accessible web-server was built, which is available at http://lin-group.cn/server/iATP. Conclusion: It is anticipated that the proposed method will become a useful tool for identifying anti-tubercular peptides.


2017 ◽  
Author(s):  
Pan Zeng ◽  
Ji Chen ◽  
Yuan Zhou ◽  
Jichun Yang ◽  
Qinghua Cui

ABSTRACTMeasuring the essentiality of genes is critically important in biology and medicine. Some bioinformatic methods have been developed for this issue but none of them can be applied to long noncoding RNAs (lncRNAs), one big class of biological molecules. Here we developed a computational method, GIC (Gene Importance Calculator), which can predict the essentiality of both protein-coding genes and lncRNAs based on RNA sequence information. For identifying the essentiality of protein-coding genes, GIC is competitive with well-established computational scores. More important, GIC showed a high performance for predicting the essentiality of lncRNAs. In an independent mouse lncRNA dataset, GIC achieved an exciting performance (AUC=0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. As a public web server, GIC is freely available at http://www.cuilab.cn/gic/.


1982 ◽  
Vol 48 (01) ◽  
pp. 049-053 ◽  
Author(s):  
C G Fenn ◽  
J M Littleton

SummaryEthanol at physiologically tolerable concentrations inhibited platelet aggregation in vitro in a relatively specific way, which may be influenced by platelet membrane lipid composition. Aggregation to collagen, calcium ionophore A23187 and thrombin (low doses) were often markedly inhibited by ethanol, adrenaline and ADP responses were little affected, and aggregation to exogenous arachidonic acid was actually potentiated by ethanol. Aggregation to collagen, thrombin and A23187 was inhibited more by ethanol in platelets enriched with saturated fatty acids than in those enriched with unsaturated fats. Platelets enriched with cholesterol showed increased sensitivity to ADP, arachidonate and adrenaline but this increase in cholesterol content did not appear to influence the inhibition by ethanol of platelet responses. The results suggest that ethanol may inhibit aggregation by an effect on membrane fluidity and/or calcium mobilization resulting in decreased activity of a membrane-bound phospholipase.


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