As a kind of haemoglobin, cytochrome P450 enzymes (CYP450) participate in the metabolism of many substances, including endogenous substances, exogenous substances and drugs. It is estimated that 60% of common prescription drugs require bioconversion through CYP450. The influence of macrolides on CYP450 contributes to the metabolism and drug-drug interactions (DDIs) of macrolides. At present, most studies on the effects of macrolides on CYP450 are focused on CYP3A, but a few exist on other enzymes and drug combinations, such as telithromycin, which can decrease the activity of hepatic CYP1A2 and CYP3A2. This article summarizes some published applications of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. And the article may subsequently guide the rational use of drugs in clinical trials. To a certain extent, poisoning caused by adverse drug interactions can be avoided. Unreasonable use of macrolide antibiotics may enable the presence of residue of macrolide antibiotics in animal-origin food. It is unhealthy for people to eat food with macrolide antibiotic residues. So it is of great significance to guarantee food safety and protect the health of consumers by the rational use of macrolides. This review gives a detailed description of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. Moreover, it offers a perspective for researchers to further explore in this area.

Pathogens manipulate the cellular mechanisms of host organisms via pathogen-host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein-protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature.