The study aims to explore the herb-drug interaction between Xuefu Zhuyu Decoction(XFZY) and atorvastatin(AT). Reverse transcription polymerase chain reaction(RT-PCR) was used to analyze the transcription levels of proteins related to drug metabolism and transport in LS174T cells, detect the intracellular drug uptake under various substrate concentrations and incubation time, and optimize the model reaction conditions of transporter multidrug resistance protein 1(MDR1)-specific probe Rhodamine 123 and AT to establish a cell model for investigating the human intestinal drug interaction. The cell counting kit-8(CCK-8) method was adopted to evaluate the cytotoxicity of XFZY on LS174T cells. After a single and continuous 48 h culture with XFZY, AT or Rhodamine 123 was added for co-incubation. The effect and mechanism of XFZY on human intestinal absorption of AT were analyzed by measuring the intracellular drug concentrations and transcription levels of related transporters and metabolic enzymes. The results of in vitro experiments show that a single co-culture with a high concentration of XFZY significantly increases the intracellular concentrations of Rhodamine 123 and AT. A high concentration of XFZY co-culture for 48 h increases the AT uptake level, significantly induces the CYP3A4 and UGT1A1 gene expression levels, and inhibits the OATP2B1 gene expression level. To compare with the evaluation results of the in vitro human cell model, the pharmacokinetic experiment of XFZY combined with AT was carried out in rats. Sprague-Dawley(SD) rats were randomly divided into a blank control group and an XFZY group. After 14 days of continuous intragastric administration, AT was given in combination. The liquid chromatography-mass spectrometry(LC-MS)/MS method was used to detect the concentrations of AT and metabolites 2-hydroxyatorvastatin acid(2-HAT), 4-hydroxyatorvastatin acid(4-HAT), atorvastatin lactone(ATL), 2-hydroxyatorvastatin lactone(2-HATL), and 4-hydroxyatorvastatin lactone(4-HATL) in plasma samples, and the pharmacokinetic parameters were calculated. Pharmacokinetic analysis in rats shows that continuous administration of XFZY does not significantly change the pharmacokinetic characteristics of AT in rats, but the AUC_(0-6 h) values of AT and metabolites 2-HAT, 4-HAT, and 2-HATL increase by 21.37%, 14.94%, 12.42%, and 6.68%, respectively. The metabolic rate of the main metabolites shows a downward trend. The study indicates that administration combined with XFZY can significantly increase the uptake level of AT in human intestinal cells and increase the exposure level of AT and main metabolites in rats to varying degrees. The mechanism may be mainly due to the inhibition of intestinal MDR1 transport activity.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Atorvastatin/administration & dosage* ; Humans ; Rats ; Rats, Sprague-Dawley ; Male ; Intestines/cytology* ; Intestinal Mucosa/metabolism* ; Herb-Drug Interactions ; Cytochrome P-450 CYP3A/metabolism* ; Intestinal Absorption/drug effects*

OBJECTIVES: To develop a heterogeneous graph prediction method based on the fusion of multi-layer semantics and topological information for addressing the challenges in drug-target interaction prediction, including insufficient modeling of high-order semantic dependencies, lack of adaptive fusion of semantic paths, and over-smoothing of node features. METHODS: A heterogeneous graph network with multiple types of entities such as drugs, proteins, side effects, and diseases was constructed, and graph embedding techniques were used to obtain low-dimensional feature representations. An adaptive metapath search module was introduced to automatically discover semantic path combinations for guiding the propagation of high-order semantic information. A semantic aggregation mechanism integrating multi-head attention was designed to automatically learn the importance of each semantic path based on contextual information and achieve differentiated aggregation and dynamic fusion among paths. A structure-aware gated graph convolutional module was then incorporated to regulate the feature propagation intensity for suppressing redundant information and redcuing over-smoothing. Finally, the potential interactions between drugs and targets were predicted through an inner product operation. RESULTS: Compared with existing drug-target interaction prediction methods, the proposed method achieved an average improvement of 3.4% and 2.4%, 3.0% and 3.8% in terms of the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPRC) on public datasets, respectively. CONCLUSIONS The drug-target interaction prediction method developed in this study can effectively extract complex high-order semantic and topological information from heterogeneous biological networks, thereby improving the accuracy and stability of drug-target interaction prediction. This method provides technical support and theoretical foundation for precise drug target discovery and targeted treatment of complex diseases.
Semantics ; Humans ; Drug Interactions ; Neural Networks, Computer ; Algorithms

The host-microbe co-metabolism system, generating diverse exogenous and endogenous bioactive molecules that influence the host's immune and metabolic functions, plays a crucial role in the pathogenesis of atherosclerosis. Recent studies have elucidated the interaction between natural medicines and this co-metabolism system. Upon oral administration, natural medicine ingredients can undergo transformation by gut microbiota, potentially enhancing their bioavailability or anti-atherogenic efficacy. Furthermore, natural medicines can exert anti-atherogenic effects via modulation of endogenous host-microbe co-metabolism. This review presents an updated understanding of the dual association between natural medicines and host-microbe co-metabolites. It explores the critical function of microbial exogenous metabolites derived from natural medicines and uncovers the mechanisms underlying natural medicines' intervention on key nodes of endogenous host-microbe co-metabolism. These insights may offer new perspectives for cardiovascular disease (CVD) treatment and guide future drug discovery efforts.
Humans ; Atherosclerosis/metabolism* ; Gastrointestinal Microbiome/drug effects* ; Biological Products/therapeutic use* ; Animals ; Host Microbial Interactions/drug effects*

Poly ADP-ribose polymerase inhibitors (PARPi), which approved in recent years, are recommended for ovarian cancer, breast cancer, pancreatic cancer, prostate cancer and other cancers by The National Comprehensive Cancer Network (NCCN) and Chinese Society of Clinical Oncology (CSCO) guidelines. Because most of PARPi are metabolized by cytochrome P450 enzyme system, there are extensive interactions with other drugs commonly used in cancer patients. By setting up a consensus working group including pharmaceutical experts, clinical experts and methodology experts, this paper forms a consensus according to the following steps: determine clinical problems, data retrieval and evaluation, Delphi method to form recommendations, finally formation expert opinion on PARPi interaction management. This paper will provide practical reference for clinical medical staff.
Male ; Female ; Humans ; Poly(ADP-ribose) Polymerase Inhibitors/pharmacology* ; Consensus ; Ovarian Neoplasms/drug therapy* ; Drug Interactions ; Adenosine Diphosphate Ribose/therapeutic use*

The prognosis of infectious diseases is determined by host-pathogen interactions. Control of pathogens has been the central dogma of treating infectious diseases in modern medicine, but the pathogen-directed medicine is facing significant challenges, including a lack of effective antimicrobials for newly emerging pathogens, pathogen drug resistance, and drug side effects. Here, a mathematic equation (termed equation of host-pathogen interactions, HPI-Equation) is developed to dissect the key variables of host-pathogen interactions. It shows that control of pathogens does not necessarily lead to host recovery. Instead, a combination of promoting a host's power of self-healing and balancing immune responses provides the best benefit for host. Moreover, the HPI-Equation elucidates the scientific basis of traditional Chinese medicine (TCM), a host-based medicine that treats infectious diseases by promoting self-healing power and balancing immune responses. The importance of self-healing power elucidated in the HPI-Equation is confirmed by recent studies that the tolerance mechanism, which is discovered in plants and animals and conceptually similar to self-healing power, improves host survival without directly attacking pathogens. In summary, the HPI-Equation describes host-pathogen interactions with mathematical logic and precision; it translates the ancient wisdoms of TCM into apprehensible modern sciences and opens a new venue for integrating TCM and modern medicine for a future medicine. Sun J. A mathematic equation derived from host-pathogen interactions elucidates the significance of integrating modern medicine with traditional Chinese medicine to treat infectious diseases. J Integr Med. 2023; 21(4):324-331.
Animals ; Medicine, Chinese Traditional ; Communicable Diseases/drug therapy* ; Mathematics ; Host-Pathogen Interactions ; Drugs, Chinese Herbal/therapeutic use*

Cardiovascular diseases are a global public health problem, and the combination of Chinese and western medicine tends to be a major solution in China. However, the complex components in traditional Chinese medicine may interact with the therapeutic western medicines for the diseases, which will lead to the herb-drug interaction(HDI). The information on the interaction can serve as a reference for the rational combination of the Chinese and western medicines in the clinical treatment of cardiovascular diseases and help avoid the occurrence of clinical safety events. However, the research on the interaction of Chinese medicine is limited as compared with that on western medicine, and no systematic review on HDI in the treatment of cardiovascular diseases is available. Therefore, this study first introduced the mechanism of HDI, then summarized the research on HDI for the commonly used drugs for cardiovascular diseases, analyzed the problems in the available studies, and put forward suggestions on the application, regulation, and research. This study aims to highlight HDI in clinical drug use and provide a reference for rational use of combination of Chinese and western medicines in the treatment of cardiovascular diseases.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Cardiovascular Diseases/drug therapy* ; Herb-Drug Interactions ; Medicine, Chinese Traditional ; China

Mutations in the epithelial growth factor receptor (EGFR) is a driving factor that causes non-small cell lung carcinoma (NSCLC). The epithelial growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) is a crucial discovery in the treatment of lung cancer, particularly the efficacy of EGFR-TKIs is superior to that of the standard chemotherapy for patients with EGFR mutation-positive advanced NSCLC. Patients with NSCLC use EGFR-TKIs and other medications simultaneously is commonly seen, especially among those with comorbidities, which increases the risk of drug-drug interactions (DDIs) of EGFR-TKIs. The most common mechanisms underlying the DDIs of EGFR-TKIs are modulations of cytochrome P450 (CYP) and drug transporters [including P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP)], as well as gastrointestinal acid-inhibitory drugs [proton pump inhibitors (PPIs) and H(2) receptor antagonists (H(2)RA)]. Inhibitors or inducers of CYP enzymes and drug transporters can inhibit or accelerate the metabolism of EGFR-TKIs, which increase or reduce the exposure of EGFR-TKIs, thereby affect the efficacy and safety of EGFR-TKIs. In addition, PPIs or H(2)RA can decrease the solubility, bioavailability and efficacy of EGFR-TKIs. This review summarizes the mechanisms of DDIs of gefitinib, erlotinib, icotinib, afatinib, dacomitinib and osimertinib; the management recommendations for DDIs of those EGFR-TKIs from the Chinese and global guideline, as well as from the recent pre-clinical and clinical studies, which provide the reference and evidence for managing the combination therapies of EGFR-TKIs and other medications in clinics.
ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Drug Interactions ; ErbB Receptors/genetics* ; Humans ; Lung Neoplasms/pathology* ; Mutation ; Neoplasm Proteins/metabolism* ; Protein Kinase Inhibitors/adverse effects*

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has occasioned worldwide alarm. Globally, the number of reported confirmed cases has exceeded 84.3 million as of this writing (January 2, 2021). Since there are no targeted therapies for COVID-19, the current focus is the repurposing of drugs approved for other uses. In some clinical trials, antiviral drugs such as remdesivir (Grein et al., 2020), lopinavir/ritonavir (LPV/r) (Cao et al., 2020), chloroquine (Gao et al., 2020), hydroxychloroquine (Gautret et al., 2020), arbidol (Wang et al., 2020), and favipiravir (Cai et al., 2020b) have shown efficacy in COVID-19 patients. LPV/r combined with arbidol, which is the basic regimen in some regional hospitals in China including Zhejiiang Province, has shown antiviral effects in COVID-19 patients (Guo et al., 2020; Xu et al., 2020). A retrospective cohort study also reported that this combination therapy showed better efficacy than LPV/r alone for the treatment of COVID-19 patients (Deng et al., 2020).
Animals ; COVID-19/drug therapy* ; Drug Interactions ; Drug Therapy, Combination ; Female ; Indoles/pharmacokinetics* ; Lopinavir/pharmacokinetics* ; Male ; Rats ; Retrospective Studies ; Ritonavir/pharmacokinetics* ; SARS-CoV-2

Depression is a common affective disorder. The application of antidepressants can significantly alleviate the symptoms of depression, which is the most important way to treat depression in clinical practice. Due to the complex etiology, wide variety, as well as diversity and severity of serious concomitant symptoms, rational addition of other drugs into antidepressants can significantly improve the cure rates of depression, reduce adverse reactions, and improve patient compliances. Therefore, the combined applications of differential drugs have been commonly used in clinic. In this paper, more than 600 literatures about depression from 2010 to 2019 were collected based on the key words of antidepressant, depression, combined medication, synergism and increase efficiency. Based on this, by summarizing and classifying the existing combinations of antidepressant drugs, this paper systematically expounds the current combined applications of antidepressant drugs in three categories, i.e. western medicines combined with western medicines, western medicines combined with traditional Chinese medicines, and traditional Chinese medicines combined with traditional Chinese medicines, in the expectation of providing the direction and basis for the selection of rational combinations of antidepressant drugs in clinic.
Antidepressive Agents ; Drug Interactions ; Humans ; Medicine, Chinese Traditional

Sugammadex provides fast and safe recovery from neuromuscular blockade without causing major adverse effects, and its clinical use is increasing. However, there are some reports on the potential risks of sugammadex, such as severe bradycardia, interactions with steroids, coagulopathy, and neuronal damage. Although these potential risks are not clearly proven, they are considered to be dose-dependent and occur more frequently with the free-form of sugammadex. Until further pieces of evidence are accumulated, it is prudent to be aware of these potential risks and avoid an overdose of sugammadex.
Blood Coagulation Disorders ; Bradycardia ; Drug Interactions ; Neuromuscular Blockade ; Neurons ; Neurotoxicity Syndromes ; Steroids