Abstract:
The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.
摘要:
结核分枝杆菌(MTB)的吡嗪酰胺(PZA)抗性菌株的兴起对常规结核病(TB)治疗提出了重大挑战。PZA,结核病治疗的基石,必须被分枝杆菌酶吡嗪酰胺酶(PZase)激活以转化其活性形式,吡嗪酸,靶向核糖体蛋白S1。阻力,通常与RpsA蛋白的突变有关,使治疗复杂化,并突出了在理解结构动力学和耐药机制方面的关键差距,特别是在G97D突变的背景下。这项研究利用了一种新颖的计算技术集成,包括多尺度生物分子和分子动力学模拟,物理化学和药物化学预测,来自ZINC和Chembridge数据库的量子计算和虚拟筛选,阐明耐药机制并确定有可能改善PZA耐药MTB治疗结果的先导化合物,即ZINC15113786、ZINC20735155、Chem10269711、Chem10279789和Chem10295790。这些计算方法提供了一种具有成本效益的,通过绕过对有机受试者的需求,同时提供对新候选药物的结合位点和功效的高度准确的见解,快速替代传统药物试验。需要快速和适当的药物开发强调需要强大的计算分析,以证明通过体外和体内实验进一步验证。