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

IF 3.9 2区化学 Q2 CHEMISTRY, APPLIED

Molecular Diversity Pub Date : 2024-08-03 DOI:10.1007/s11030-024-10946-1

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

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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.

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通过计算药物发现靶向 Eis 蛋白抑制结核分枝杆菌的毒力和耐药性

结核病（TB）仍然是一个严重的健康威胁，尤其是随着耐多药菌株的出现。这需要全世界的科学界和医疗保健专业人员给予关注，以开发出有效的治疗方法。增强细胞内生存（Eis）蛋白是结核分枝杆菌的一种乙酰转移酶，其功能是在氨基糖苷类抗生素上添加乙酰基，干扰其与细菌核糖体结合的能力，从而阻止其抑制蛋白质合成并杀死细菌。因此，以这种蛋白质为靶点可以加快恢复氨基糖苷类药物活性的机会，从而减少耐药性结核病的出现。为此，我们从椰子数据库中筛选了 406,747 种针对 Eis 蛋白的天然化合物。根据 MM/GBSA 重排结合能，选出了前 5 个最突出的天然化合物，即 CNP0187003（- 96.14 kcal/mol）、CNP0176690（- 93.79 kcal/mol）、CNP0136537（- 92.31 kcal/mol）、CNP0398701（- 91.96 kcal/mol）和 CNP0043390（- 91.60 kcal/mol）。在对接过程中，这些化合物显示出大量氢键和其他重要的相互作用，证实它们与 Eis 蛋白具有很强的结合亲和力。随后，对这些化合物进行的 MD 模拟显示，Eis-CNP0043390 复合物最稳定，其次是 Eis-CNP0187003 和 Eis-CNP0176690 复合物，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了这一点。这些化合物在本次研究使用的所有参数中都显示出最有利的结果，可能具有抑制 Eis 蛋白的潜力。这些发现将利用计算技术确定和开发一种天然化合物抑制剂，作为抗药性结核病的替代疗法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Molecular Diversity 化学-化学综合

CiteScore

7.30

自引率

7.90%

发文量

219

审稿时长

2.7 months

期刊介绍： Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including: combinatorial chemistry and parallel synthesis; small molecule libraries; microwave synthesis; flow synthesis; fluorous synthesis; diversity oriented synthesis (DOS); nanoreactors; click chemistry; multiplex technologies; fragment- and ligand-based design; structure/function/SAR; computational chemistry and molecular design; chemoinformatics; screening techniques and screening interfaces; analytical and purification methods; robotics, automation and miniaturization; targeted libraries; display libraries; peptides and peptoids; proteins; oligonucleotides; carbohydrates; natural diversity; new methods of library formulation and deconvolution; directed evolution, origin of life and recombination; search techniques, landscapes, random chemistry and more;