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从编码到治愈:通过计算方法鉴定LasR抑制剂以对抗铜绿假单胞菌中的群体感应

From code to cure: computational identification of LasR inhibitors to combat quorum sensing in P. aeruginosa.

作者信息

Chowdhury Subarnarekha, Kumar Mukesh, Rawat Shivani, Singh Shweta, Kaur Punit

机构信息

Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, 110029, India.

出版信息

Mol Divers. 2025 Aug 30. doi: 10.1007/s11030-025-11333-0.

Abstract

Biofilm formation by Pseudomonas aeruginosa (PA) poses a significant challenge in clinical settings due to its contribution to chronic infections and antibiotic resistance. Quorum sensing (QS), particularly regulated by the LasR receptor, plays a crucial role in biofilm development and virulence. In this study, an integrative in silico approach was employed to identify the potential LasR inhibitors. Molecular docking predicted binding affinities of candidate molecules, followed by molecular dynamics simulations to assess complex stability in a dynamic system. Druggability analysis, quantum mechanical evaluation via density functional theory, and binding free energy calculations refined the selection, yielding six promising inhibitors. Among these, compounds 26529, 22498, and 25412 showed strong binding within the LasR-ligand-binding domain, engaging key residues such as Tyr56, Trp60, Asp73, and Ser129. Notably, compound 26529 formed an additional pi-cation interaction with Trp88, providing greater stabilization than typical hydrogen bonds and distinguishing it as the lead molecule. ADMET profiling further confirmed their favorable pharmacokinetic and toxicity properties, selecting the most drug-like candidates. The findings align with the previous reports targeting LasR to attenuate PA virulence and biofilm formation. However, experimental validation remains essential to confirm their therapeutic efficacy. Overall, this study highlights promising QS inhibitors as potential anti-virulence agents against PA.

摘要

铜绿假单胞菌(PA)形成生物膜在临床环境中构成了重大挑战,因为它会导致慢性感染和抗生素耐药性。群体感应(QS),特别是由LasR受体调控的群体感应,在生物膜形成和毒力方面起着关键作用。在本研究中,采用了一种综合的计算机模拟方法来识别潜在的LasR抑制剂。分子对接预测了候选分子的结合亲和力,随后进行分子动力学模拟以评估动态系统中复合物的稳定性。成药性质分析、通过密度泛函理论进行的量子力学评估以及结合自由能计算优化了筛选过程,产生了六种有前景的抑制剂。其中,化合物26529、22498和25412在LasR配体结合域内显示出强结合,与Tyr56、Trp60、Asp73和Ser129等关键残基相互作用。值得注意的是,化合物26529与Trp88形成了额外的π-阳离子相互作用,提供了比典型氢键更大的稳定性,并将其作为先导分子区分开来。ADMET分析进一步证实了它们良好的药代动力学和毒性性质,筛选出最具药物样性质的候选物。这些发现与之前针对LasR以减弱PA毒力和生物膜形成的报道一致。然而,实验验证对于确认它们的治疗效果仍然至关重要。总体而言,本研究突出了有前景的QS抑制剂作为针对PA的潜在抗毒力药物。

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