The authors have previously applied two integrated platforms, MetaCore and MetaDrug, for the assembly and analysis of human biological networks as a useful method for the integration and functional interpretation of high-throughput experimental data. The present study demonstrates in detail the specific algorithms that are used in both software platforms. Using a standard set of genes as input, namely CYP3A4 (an enzyme), PXR (a nuclear hormone receptor), MDR1 (a transporter) and hERG (an ion channel) related to the absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) of xenobiotics, we have now generated networks with each algorithm. The relative advantages and disadvantages of these algorithms are explained using these examples as well as appropriate instances of utility to illustrate further the particular circumstances for their use. In addition, the benefits of the different network algorithms are identified when compared with algorithms available in other products, where this information is available.

The challenge of predicting the metabolism or toxicity of a drug in humans has been approached using in vivo animal models, in vitro systems, high throughput genomics and proteomics methods, and, more recently, computational approaches. Understanding the complexity of biological systems requires a broader perspective rather than focusing on just one method in isolation for prediction. Multiple methods may therefore be necessary and combined for a more accurate prediction. In the field of drug metabolism and toxicology, we have seen the growth, in recent years, of computational quantitative structure-activity relationships (QSARs), as well as empirical data from microarrays. In the current study we have further developed a novel computational approach, MetaDrug, that 1) predicts metabolites for molecules based on their chemical structure, 2) predicts the activity of the original compound and its metabolites with various absorption, distribution, metabolism, excretion, and toxicity models, 3) incorporates the predictions with human cell signaling and metabolic pathways and networks, and 4) integrates networks and metabolites, with relevant toxicogenomic or other high throughput data. We have demonstrated the utility of such an approach using recently published data from in vitro metabolism and microarray studies for aprepitant, 2(S)-((3,5-bis(trifluoromethyl)benzyl)-oxy)-3(S)phenyl-4-((3-oxo-1,2,4-triazol-5-yl)methyl)morpholine (L-742694), trovofloxacin, 4-hydroxytamoxifen, and artemisinin and other artemisinin analogs to show the predicted interactions with cytochromes P450, pregnane X receptor, and P-glycoprotein, and the metabolites and the networks of genes that are affected. As a comparison, we used a second computational approach, MetaCore, to generate statistically significant gene networks with the available expression data. These case studies demonstrate the combination of QSARs and systems biology methods.

Comparative analysis of the mitochondrial genomes in Drosophila virilis species group (Diptera: Drosophilidae)

Популяционная структура ареала степного орла и предварительные данные по генетическому разнообразию его популяций и статусу подвидов

Here, we describe the effects of double knockout (KO) of the cbs and cse genes, which are responsible for H₂S synthesis through the transsulfuration pathway, and KO of the sulfurtransferase gene (dtst1) in Drosophila melanogaster females. The analysis of H₂S production in flies showed minimal levels in the double- and triple-knockout strains. The double- (cbs-/-; cse-/-) and triple- (cbs-/-; cse-/-; dtst-/-) KO flies exhibited a shortened lifespan and reduced fecundity, and showed dramatic changes in Malpighian tubule morphology. The transcriptomic analysis revealed a profound increase in the expression levels of several genes involved in excretory system function in the double-KO and especially the triple-KO flies. Importantly, major groups of differentially expressed genes (DEGs) in the whole bodies of females and ovaries of KO strains included genes responsible for detoxification, reproduction, mitochondrial activity, excretion, cell migration, and muscle system function. The reduced fecundity observed in the double- and triple-KO flies correlated with pronounced changes in the ovarian transcriptome. At the same time, the single knockout of dtst1 increased the flies’ fecundity and lifespan. Our experiments exploring unique Drosophila strains with KO of major H₂S-related genes revealed several new pathways controlled by this ancient adaptogenic system that is involved in various human diseases and aging.