药物警戒
不良事件报告系统
药效团
不利影响
医学
上市后监督
优势比
对接(动物)
药理学
生物信息学
内科学
生物
护理部
作者
Aina M. Shaju,Nishi Panicker,Venkumahanti Chandni,V. Lakshmi Prasanna,Gouri Nair,Viswam Subeesh
摘要
What is known and objective Red man syndrome (RMS) is a non-IgE-mediated anaphylactoid adverse event frequently witnessed after a rapid infusion of vancomycin. This study aims to unravel drugs and associated off-label targets that induce RMS by exploiting FDA Adverse Event Reporting System (FAERS) and Pharmacovigilance/Pharmacogenomics Insilico Pipeline (PHARMIP). Methods The case/non-case retrospective observational study was conducted in the FAERS database. Reporting odds ratio (ROR) and proportional reporting ratio (PRR) data mining algorithms were used to evaluate the strength of the signal. The off-label targets of the drugs with potential signals were obtained using online servers by applying a similarity ensemble approach and a reverse pharmacophore database, which was further validated by molecular docking studies. Results and discussion Oritavancin exhibited a strong positive signal (PRR:1185.20 and ROR:1256), which suggests a higher risk for causing RMS. The literature search revealed the involvement of the MRGPRX2 gene in the development of RMS. PHARMIP study unearthed Carbonic anhydrase II (CA2) as the common off-label target among the drugs causing RMS. The results obtained from molecular docking studies reinforced the findings as mentioned earlier, wherein the highest docking score was disinterred for oritavancin (−9.4 for MRGPRX2 and − 8.7 for CA2). What is new and conclusion Many antibiotics and other classes of medications have been discovered in the quest for drugs that may induce RMS, although a causal relationship could not be established. The implication of MRGPX2 and CA2 in the initial stages of pathogenesis necessitates the development of inhibitors that could be used as potential therapeutic agents against RMS.
科研通智能强力驱动
Strongly Powered by AbleSci AI