Global view of a drug-sensitivity gene network

Abstract

An important challenge in drug development is to gain insight into the mechanism of drug sensitivity. Looking for insights into the global relationships between drugs and their sensitivity genes would be expected to reveal mechanism of drug sensitivity. Here we constructed a drug-sensitivity gene network (DSGN) based on the relationships between drugs and their sensitivity genes, using drug screened genomic data from the NCI-60 cell line panel, including 181 drugs and 1057 sensitivity genes, and 1646 associations between them. Through network analysis, we found that two drugs that share the same sensitivity genes tend to share the same Anatomical Therapeutic Chemical classification and side effects. We then found that the sensitivity genes of same drugs tend to cluster together in the human interactome and participate in the same biological function modules (pathways). Finally, we noticed that the sensitivity genes and target genes of the same drug have a significant dense distance in the human interactome network and they were functionally related. For example, target genes such as epidermal growth factor receptor gene can activate downstream sensitivity genes of the same drug in the PI3K/Akt pathway. Thus, the DSGN would provide great insights into the mechanism of drug sensitivity.

Environmental microbiology – the next 20 years: bioconnectivity and meta'omics 2.0

“…Once basic cellular interactome maps have been created for enough microbes, and 3D models of enough enzymes of key metabolic processes have been elucidated, prediction of interaction surfaces will become routine and automated (e.g., see Meyer et al, 2018). Such surfaces will constitute new drug targets for interruption of essential metabolic functions in pathogenic microbes (e.g., Zoraghi and Reiner, 2013;Li et al, 2018;Llano and Peña-Hernandez, 2018;Yang et al, 2018). Contemporary efforts to inventarize microbial diversity (Venter et al, 2004;Alivisatos et al, 2015;Salazar et al, 2016;Thompson et al, 2017) will eventually lead to the availability of representative genome sequences of much of microbial diversity.…”