Prediction of drugs having opposite effects on disease genes in a directed network was written by Yu, Hasun;Choo, Sungji;Park, Junseok;Jung, Jinmyung;Kang, Yeeok;Lee, Doheon. And the article was included in BMC Systems Biology in 2016.Quality Control of (Z)-2-(4-(4-Chloro-1,2-diphenylbut-1-en-1-yl)phenoxy)ethan-1-ol This article mentions the following:
Background: Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and mol. pathways, most of previous network-based studies disregarded this information. Methods: We developed a novel computational method, Prediction of Drugs having Opposite effects on Disease genes (PDOD), for identifying drugs having opposite effects on altered states of disease genes. PDOD utilized drug-drug target interactions with ‘effect type’, an integrated directed mol. network with ‘effect type’ and ‘effect direction’, and disease genes with regulated states in disease patients. With this information, we proposed a scoring function to discover drugs likely to restore altered states of disease genes using the path from a drug to a disease through the drug-drug target interactions, shortest paths from drug targets to disease genes in mol. pathways, and disease gene-disease associations Results: We collected drug-drug target interactions, mol. pathways, and disease genes with their regulated states in the diseases. PDOD is applied to 898 drugs with known drug-drug target interactions and nine diseases. We compared performance of PDOD for predicting known therapeutic drug-disease associations with the previous methods. PDOD outperformed other previous approaches which do not exploit directional information in mol. network. In addition, we provide a simple web service that researchers can submit genes of interest with their altered states and will obtain drugs seeming to have opposite effects on altered states of input genes. Conclusions: Our results showed that ‘effect type’ and ‘effect direction’ information in the network based approaches can be utilized to identify drugs having opposite effects on diseases. Our study can offer a novel insight into the field of network-based drug repositioning. In the experiment, the researchers used many compounds, for example, (Z)-2-(4-(4-Chloro-1,2-diphenylbut-1-en-1-yl)phenoxy)ethan-1-ol (cas: 128607-22-7Quality Control of (Z)-2-(4-(4-Chloro-1,2-diphenylbut-1-en-1-yl)phenoxy)ethan-1-ol).
(Z)-2-(4-(4-Chloro-1,2-diphenylbut-1-en-1-yl)phenoxy)ethan-1-ol (cas: 128607-22-7) belongs to alcohols. Because alcohols are easily synthesized and easily transformed into other compounds, they serve as important intermediates in organic synthesis. Under carefully controlled conditions, simple alcohols can undergo intermolecular dehydration to give ethers. This reaction is effective only with methanol, ethanol, and other simple primary alcohols.Quality Control of (Z)-2-(4-(4-Chloro-1,2-diphenylbut-1-en-1-yl)phenoxy)ethan-1-ol
Referemce:
Alcohol – Wikipedia,
Alcohols – Chemistry LibreTexts