Bioinformatics Lab, National Institute of Plant Genome Research (NIPGR), New Delhi, India.
Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, India.
J Biomol Struct Dyn. 2024;42(20):10950-10964. doi: 10.1080/07391102.2023.2259487. Epub 2023 Sep 20.
Antibiotic resistance against () has been a significant cause of death worldwide. The Enhanced intracellular survival (EIS) protein of the bacteria is an acetyltransferase that multiacetylates aminoglycoside antibiotics, preventing them from binding to the bacterial ribosome. To overcome the EIS-mediated antibiotics resistance of ., we compiled 888 alkaloids and derivatives from five different databases and virtually screened them against the EIS receptor. The compound library was filtered down to 87 compounds, which underwent additional analysis and filtration. Moreover, the top 15 most prominent phytocompounds were obtained after the drug-likeness prediction and ADMET screening. Out of 15, nine compounds confirmed the maximum number of hydrogen bond interactions and reliable binding energies during molecular docking. Additionally, the Molecular dynamics (MD) simulation of nine compounds showed the three most stable complexes, further verified by re-docking with mutated protein. The density functional theory (DFT) calculation was performed to identify the HOMO-LUMO energy gaps of the selected three potential compounds. Finally, our selected top lead compounds i.e., Alkaloid AQC2 (PubChem85634496), Nobilisitine A (ChEbi68116), and N-methylcheilanthifoline (ChEbi140673) demonstrated more favourable outcomes when compared with reference compounds (i.e., 39b and 2i) in all parameters used in this study. Therefore, we anticipate that our findings will help to explore and develop natural compound therapy against multi and extensively drug-resistant strains of .Communicated by Ramaswamy H. Sarma.
针对 () 的抗生素耐药性已成为全球范围内的主要死亡原因之一。细菌的增强细胞内生存 (EIS) 蛋白是一种乙酰转移酶,可使氨基糖苷类抗生素多乙酰化,使其无法与细菌核糖体结合。为了克服. 中 EIS 介导的抗生素耐药性,我们从五个不同的数据库中编译了 888 种生物碱及其衍生物,并对 EIS 受体进行了虚拟筛选。化合物库被筛选到 87 种化合物,然后对这些化合物进行了进一步的分析和筛选。此外,在进行药物相似性预测和 ADMET 筛选后,获得了前 15 种最突出的植物化合物。在这 15 种化合物中,有 9 种化合物在分子对接过程中确认了与受体之间最多的氢键相互作用和可靠的结合能。此外,这 9 种化合物的分子动力学 (MD) 模拟显示了三个最稳定的复合物,进一步通过与突变蛋白的重新对接得到了验证。最后,我们通过密度泛函理论 (DFT) 计算确定了所选三个潜在化合物的 HOMO-LUMO 能隙。最后,与参考化合物 (即 39b 和 2i) 相比,我们选择的三种最有前景的先导化合物,即 Alkaloid AQC2 (PubChem85634496)、Nobilisitine A (ChEbi68116) 和 N-methylcheilanthifoline (ChEbi140673) 在本研究中使用的所有参数中均显示出更有利的结果。因此,我们预计我们的研究结果将有助于探索和开发针对多药和广泛耐药菌株的天然化合物治疗方法。通讯作者为 Ramaswamy H. Sarma。