使用减法基因组学方法优先考虑结核分枝杆菌药物靶标的最先进策略

Adetutu Akinnuwesi, Samuel Egieyeh, Ruben Cloete
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引用次数: 0

摘要

结核病仍然是单一传染性细菌造成死亡的原因之一。抗生素使用不当和患者不遵医嘱等因素推动了耐药结核病的出现。耐多药和广泛耐药结核病菌株对目前的治疗方案构成重大挑战,因为它们对这些菌株的疗效降低,限制了患者的成功治疗结果。此外,二线药物的有限有效性和相关毒性进一步加剧了这一问题。此外,新的药理学靶点的缺乏以及药物开发管道中抗结核化合物数量的下降进一步阻碍了新疗法的出现。因此,研究人员需要开发创新的方法来识别潜在的新的抗结核药物。技术的发展和组学数据的突破允许使用计算生物学方法,例如,代谢组学分析来揭示基于结构的药物设计的药理学靶点。代谢在病原体发育、生长、生存和感染中的作用已经确立。因此,本文将重点介绍结核分枝杆菌代谢网络作为新靶点鉴定的枢纽,并强调了一种逐步减少的基因组学方法来确定靶点的优先级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State-of-the-art strategies to prioritize Mycobacterium tuberculosis drug targets for drug discovery using a subtractive genomics approach
Tuberculosis remains one of the causes of death from a single infectious bacterium. The inappropriate use of antibiotics and patients’ non-compliance among other factors drive the emergence of drug-resistant tuberculosis. Multidrug-resistant and extensively drug-resistant strains of tuberculosis pose significant challenges to current treatment regimens, as their reduced efficacy against these strains limits successful patient outcomes. Furthermore, the limited effectiveness and associated toxicity of second-line drugs further compound the issue. Moreover, the scarcity of novel pharmacological targets and the subsequent decline in the number of anti-TB compounds in the drug development pipeline has further hindered the emergence of new therapies. As a result, researchers need to develop innovative approaches to identify potential new anti-TB drugs. The evolution of technology and the breakthrough in omics data allow the use of computational biology approaches, for example, metabolomic analysis to uncover pharmacological targets for structured-based drug design. The role of metabolism in pathogen development, growth, survival, and infection has been established. Therefore, this review focuses on the M. tb metabolic network as a hub for novel target identification and highlights a step-by-step subtractive genomics approach for target prioritization.
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