Predicting existing targets for new drugs base on strategies for missing interactions

Background

There has been paid more and more attention to supervised classification models in the area of predicting drug-target interactions (DTIs). However, in terms of classification, unavoidable missing DTIs in data would cause three issues which have not yet been addressed appropriately by former approaches. Directly labeled as negatives (non-DTIs), missing DTIs increase the confusion of positives (DTIs) and negatives, aggravate the imbalance between few positives and many negatives, and are usually discriminated as highly-scored false positives, which influence the existing measures sharply.

Results

Under the framework of local classification model (LCM), this work focuses on the scenario of predicting how possibly a new drug interacts with known targets. To address the first two issues, two strategies, Spy and Super-target, are introduced accordingly and further integrated to form a two-layer LCM. In the bottom layer, Spy-based local classifiers for protein targets are built by positives, as well as reliable negatives identified among unlabeled drug-target pairs. In the top layer, regular local classifiers specific to super-targets are built with more positives generated by grouping similar targets and their interactions. Furthermore, to handle the third issue, an additional performance measure, Coverage, is presented for assessing DTI prediction. The experiments based on benchmark datasets are finally performed under five-fold cross validation of drugs to evaluate this approach. The main findings are concluded as follows. (1) Both two individual strategies and their combination are effective to missing DTIs, and the combination wins the best. (2) Having the advantages of less confusing decision boundary at the bottom layer and less biased decision boundary at the top layer, our two-layer LCM outperforms two former approaches. (3) Coverage is more robust to missing interactions than other measures and is able to evaluate how far one needs to go down the list of targets to cover all the proper targets of a drug.

Conclusions

Proposing two strategies and one performance measure, this work has addressed the issues derived from missing interactions, which cause confusing and biased decision boundaries in classifiers, as well as the inappropriate measure of predicting performance, in the scenario of predicting interactions between new drugs and known targets.

     

Expression of an extracellular ribonuclease gene increases resistance to <Emphasis Type="Italic">Cucumber mosaic virus</Emphasis> in tobacco

Background

The apoplast plays an important role in plant defense against pathogens. Some extracellular PR-4 proteins possess ribonuclease activity and may directly inhibit the growth of pathogenic fungi. It is likely that extracellular RNases can also protect plants against some viruses with RNA genomes. However, many plant RNases are multifunctional and the direct link between their ribonucleolytic activity and antiviral defense still needs to be clarified. In this study, we evaluated the resistance of Nicotiana tabacum plants expressing a non-plant single-strand-specific extracellular RNase against Cucumber mosaic virus.

Results

Severe mosaic symptoms and shrinkage were observed in the control non-transgenic plants 10 days after inoculation with Cucumber mosaic virus (CMV), whereas such disease symptoms were suppressed in the transgenic plants expressing the RNase gene. In a Western blot analysis, viral proliferation was observed in the uninoculated upper leaves of control plants, whereas virus levels were very low in those of transgenic plants. These results suggest that resistance against CMV was increased by the expression of the heterologous RNase gene.

Conclusion

We have previously shown that tobacco plants expressing heterologous RNases are characterized by high resistance to Tobacco mosaic virus. In this study, we demonstrated that elevated levels of extracellular RNase activity resulted in increased resistance to a virus with a different genome organization and life cycle. Thus, we conclude that the pathogen-induced expression of plant apoplastic RNases may increase non-specific resistance against viruses with RNA genomes.

     

Comparison of human and mouse E-selectin binding to Sialyl-Lewis<Superscript>x</Superscript>

Background

During inflammation, leukocytes are captured by the selectin family of adhesion receptors lining blood vessels to facilitate exit from the bloodstream. E-selectin is upregulated on stimulated endothelial cells and binds to several ligands on the surface of leukocytes. Selectin:ligand interactions are mediated in part by the interaction between the lectin domain and Sialyl-Lewis x (sLe^x), a tetrasaccharide common to selectin ligands. There is a high degree of homology between selectins of various species: about 72 and 60 % in the lectin and EGF domains, respectively. In this study, molecular dynamics, docking, and steered molecular dynamics simulations were used to compare the binding and dissociation mechanisms of sLe^x with mouse and human E-selectin. First, a mouse E-selectin homology model was generated using the human E-selectin crystal structure as a template.

Results

Mouse E-selectin was found to have a greater interdomain angle, which has been previously shown to correlate with stronger binding among selectins. sLe^x was docked onto human and mouse E-selectin, and the mouse complex was found to have a higher free energy of binding and a lower dissociation constant, suggesting stronger binding. The mouse complex had higher flexibility in a few key residues. Finally, steered molecular dynamics was used to dissociate the complexes at force loading rates of 2000–5000 pm/ps². The mouse complex took longer to dissociate at every force loading rate and the difference was statistically significant at 3000 pm/ps². When sLe^x-coated microspheres were perfused through microtubes coated with human or mouse E-selectin, the particles rolled more slowly on mouse E-selectin.

Conclusions

Both molecular dynamics simulations and microsphere adhesion experiments show that mouse E-selectin protein binds more strongly to sialyl Lewis x ligand than human E-selectin. This difference was explained by a greater interdomain angle for mouse E-selectin, and greater flexibility in key residues. Future work could introduce similar amino acid substitutions into the human E-selectin sequence to further modulate adhesion behavior.

     

Case report of whole genome sequencing in the XY female: identification of a novel <Emphasis Type="Italic">SRY</Emphasis> mutation and revision of a misdiagnosis of androgen insensitivity syndrome

Background

The 46,XY female is characterised by a male karyotype and female phenotype arising due to any interruption in the sexual development pathways in utero. The cause is usually genetic and various genes are implicated.

Case presentation

Herein we describe a 46,XY woman who was first diagnosed with androgen insensitivity syndrome (testicular feminisation) at 18 years; however, this was later questioned due to the presence of intact Müllerian structures. The clinical phenotype suggested several susceptibility genes including SRY, DHH, NR5A1, NR0B1, AR, AMH, and AMHR2. To study candidate genes simultaneously, we performed whole genome sequencing. This revealed a novel and likely pathogenic missense variant (p.Arg130Pro, c.389G>C) in SRY, one of the major genes implicated in complete gonadal dysgenesis, hence securing this condition over androgen insensitivity syndrome as the cause of the patient’s disorder of sexual development.

Conclusion

This case highlights the emerging clinical utility of whole genome sequencing as a tool in differentiating disorders of sexual development.

     

A power analysis for future clinical trials on the potential adverse effects of SSRIs on amygdala reactivity

Treatment of adolescents with antidepressants may induce an increased risk for suicidality in this population. The activity of the amygdala during processing of emotional faces with functional Magnetic Resonance Imaging (fMRI) is a well-known measure of emotional dysregulation. Based upon data of our prematurely ended randomized clinical trial with fluoxetine (NTR3103) in anxious and or depressed girls (12–14 years of age) we calculated that with the found effect size of r = 0.66, compared to placebo, only 8 subjects are needed to demonstrate increased amygdala activity following 16 weeks of treatment with fluoxetine.     

Antibacterial effect of bestatin during periodontitis

Periodontitis is a polymicrobial disease inciting inflammatory destruction of the tooth-supporting tissues, i.e., periodontium. The initiation of this infectious disease is ascribed to the formation of subgingival biofilms. These biofilms cause stimulation of myriad of chronic inflammatory reactions by the affected tissue. The Gram-negative anaerobe Porphyromonas gingivalis is commonly found as part of the microbiota of subgingival biofilms, and is involved in the occurrence of the disease. P. gingivalis possesses numerous virulence factors supporting its survival, regulating its communication with other species in the biofilm, degrading host tissues. Fusobacterium nucleatum is pivotal for formation of biofilm and promotes growth and invasion properties of P. gingivalis. Bestatin is an aminopeptide inhibitor, produced by actinomycetes. It possesses antibacterial properties against P. gingivalis and F. nucleatum. The following review focuses on action of bestatin on the mentioned bacteria.