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通过计算机辅助药物发现靶向Eis蛋白抑制结核分枝杆菌的毒力和耐药性

Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery.

作者信息

Kumar Geethu S, Sahoo Amaresh Kumar, Ranjan Nishant, Dwivedi Vivek Dhar, Agrawal Sharad

机构信息

Centre for Development of Biomaterials and Department of Life Sciences, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida, Uttar Pradesh, 201310, India.

Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Allahabad, India.

出版信息

Mol Divers. 2025 Apr;29(2):1697-1723. doi: 10.1007/s11030-024-10946-1. Epub 2024 Aug 3.

DOI:10.1007/s11030-024-10946-1
PMID:39096353
Abstract

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (- 96.14 kcal/mol), CNP0176690 (- 93.79 kcal/mol), CNP0136537 (- 92.31 kcal/mol), CNP0398701 (- 91.96 kcal/mol), and CNP0043390 (- 91.60 kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

摘要

结核病(TB)仍然是一个严重的健康威胁,尤其是随着多重耐药菌株的出现。这需要全球科学界和医疗专业人员的关注,以开发有效的治疗方法。增强型细胞内存活(Eis)蛋白是结核分枝杆菌的一种乙酰转移酶,其作用是将乙酰基添加到氨基糖苷类抗生素上,这会干扰它们与细菌核糖体结合的能力,从而阻止它们抑制蛋白质合成并杀死细菌。因此,针对这种蛋白质可增加恢复氨基糖苷类药物活性的机会,从而减少耐药结核病的出现。为此,我们从椰子数据库中筛选了406,747种天然化合物针对Eis蛋白进行研究。基于MM/GBSA重新评分结合能,选出了最突出的5种天然化合物,即CNP0187003(-96.14千卡/摩尔)、CNP0176690(-93.79千卡/摩尔)、CNP0136537(-92.31千卡/摩尔)、CNP0398701(-91.96千卡/摩尔)和CNP0043390(-91.60千卡/摩尔)。这些化合物表现出大量氢键和其他重要相互作用的存在,证实了它们在对接过程中与Eis蛋白具有很强的结合亲和力。随后,对这些化合物的分子动力学模拟表明,Eis-CNP0043390复合物最稳定,其次是Eis-CNP0187003和Eis-CNP0176690复合物,通过结合自由能计算、主成分分析(PCA)和自由能景观分析进一步验证。这些化合物在本次研究所使用的所有参数中都显示出最有利的结果,并且可能具有抑制Eis蛋白的潜力。因此,这些发现将利用计算技术来识别和开发一种天然化合物抑制剂,作为耐药结核病的替代药物。

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引用本文的文献

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Overcoming aminoglycoside antibiotic resistance in by targeting Eis protein.通过靶向Eis蛋白克服氨基糖苷类抗生素耐药性。 (注:原英文文本“Overcoming aminoglycoside antibiotic resistance in by targeting Eis protein.”中“in”后面缺少内容,翻译时根据语境补充完整使其表意合理)
In Silico Pharmacol. 2025 Mar 4;13(1):36. doi: 10.1007/s40203-025-00325-5. eCollection 2025.

本文引用的文献

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Multi-Drug Resistance Tuberculosis (MDR-TB) Challenges in India: A Review.印度的耐多药结核病挑战:综述
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Protein J. 2024 Feb;43(1):12-23. doi: 10.1007/s10930-023-10165-x. Epub 2023 Nov 6.
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Long-term outcomes of the global tuberculosis and COVID-19 co-infection cohort.
全球结核病和 COVID-19 合并感染队列的长期结局。
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