药品
药物开发
药物发现
代谢组学
肺结核
抗药性
计算生物学
药理学
药物代谢
机制(生物学)
药物作用
药物重新定位
药物靶点
医学
生物
生物信息学
作用机理
代谢途径
系统生物学
病菌
药物相互作用
生物转化
酶
精密医学
制药工业
治疗指标
广泛耐药结核
评论文章
信号转导
功效
作者
Periyasamy Vijayalakshmi,Faiz Alfaiz,Rajendran Vijayakumar,Deepali Desai,Chandrabose Selvaraj
标识
DOI:10.1016/j.micpath.2025.108173
摘要
Tuberculosis (TB) remains a major public health problem with increased incidence of drug-resistant TB due to failure of existing treatments. Current anti-TB drugs are mainly directed at targeting important biochemical pathways in the Mtb with the biotransformation of drugs through hepatic metabolism. However, new proof indicates that Mtb can directly contribute to drug metabolism, therefore determining both the effectiveness and the resistance of a therapeutic agent. This review aims to explore the mechanism of action of Mtb mediated drug biotransformation, the several enzymes it contains and new metabolic pathway by which the pathogen could alter, neutralize or even stimulate antitubercular agents. Static liver-based models of metabolism are then compared to pathogen-based models to give a deeper understanding of how the host and pathogen jointly determine the final outcome and efficacy of the drug. In addition, the Mtb driven biotransformation, causes impact Mtb metabolism on pharmacokinetics, drug half-life, and bioavailability, and the potential to develop new therapeutic approaches are also elaborated. This review also discusses possible directions in drug discovery by identifying Mtb-specific enzymes, using combination therapy, which affects the host and pathogen's metabolism, and using metabolomic and computational analysis for pathway identification. The potential lies in applying pathogen-specific knowledge to TB drug development to address adaptive resistance, improve on drug dosing regimens, and improve treatment outcomes. Additionally, host-directed therapies (HDTs) and the concept of developing drugs with dual activity are suggested as possible new strategies in TB control. Holders of co-culture systems, organoids, and machine learning-driven metabolomics are considered as advanced models for demystifying Mtb drug metabolism. These findings emphasize the need for a shift towards precision medicine approach to TB therapy to consider the kinetic nature and Mtb metabolism patterns in relation to human health.
科研通智能强力驱动
Strongly Powered by AbleSci AI