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突破方阵:利用增强抗生素治疗活性的群体感应抑制剂克服细菌耐药性

Breaking the Phalanx: Overcoming Bacterial Drug Resistance with Quorum Sensing Inhibitors that Enhance Therapeutic Activity of Antibiotics.

作者信息

Beasley Jon-Michael, Dorjsuren Dorjbal, Jain Sankalp, Rath Marielle, Tieghi Ricardo Scheufen, Tropsha Alexander, Simeonov Anton, Zakharov Alexey V, Muratov Eugene

机构信息

UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.

Division of Preclinical Innovation, National Center for Advancing Translational Sciences, Rockville, MD, 20850.

出版信息

bioRxiv. 2025 Jan 22:2025.01.17.633658. doi: 10.1101/2025.01.17.633658.

Abstract

Antibiotic-resistant bacterial infections loom over humanity as an increasing deadly threat. There exists a dire need for new treatments, especially those that synergize with our existing arsenal of antibiotic drugs to help overcome the gap in antibiotic efficacy and attenuate the development of new antibiotic-resistance in the most dangerous pathogens. Quorum sensing systems in bacteria drive the formation of biofilms, increase surface motility, and enhance other virulence factors, making these systems attractive targets for the discovery of novel antibacterials. Quorum sensing inhibitors (QSIs) are hypothesized to synergize with existing antibiotics, making bacteria more sensitive to the effects of these drugs. In this study, we aimed to find the synergistic combinations between the QSIs and known antibiotics to combat the two deadliest hospital infections - and . We mined biochemical activity databases and literature to identify known, high efficacy QSIs against these bacteria. We used these data to develop and validate a Quantitative Structure-Activity Relationship (QSAR) model for predicting QSI activity and then employed this model to identify new potential QSIs from the Inxight database of approved and investigational drugs. We then tested binary mixtures of the identified QSIs with 11 existing antibiotics using a combinatorial matrix screening approach with ten (five of each) clinical isolates of and . Amongst explored drug combinations, 31 exhibited a synergistic effect, including mixtures involving naldemedine and telotristat, two drugs predicted by our model with previously undescribed QSI activity. Although no mixture inhibiting all the strains was found, piperacillin combined with curcumin, ketoprofen, indomethacin, and piroxicam demonstrated the broadest antimicrobial action. We anticipate that further preclinical investigation of these combinations of novel repurposed QSIs with a known antibiotic may lead to novel clinical candidates.

摘要

抗生素耐药性细菌感染正作为一种日益致命的威胁笼罩着人类。迫切需要新的治疗方法,尤其是那些能与我们现有的抗生素药物协同作用的方法,以帮助克服抗生素疗效方面的差距,并减缓最危险病原体中新的抗生素耐药性的发展。细菌中的群体感应系统驱动生物膜的形成、增加表面运动性并增强其他毒力因子,使这些系统成为发现新型抗菌药物的有吸引力的靶点。群体感应抑制剂(QSIs)被假定能与现有抗生素协同作用,使细菌对这些药物的作用更敏感。在本研究中,我们旨在找到QSIs与已知抗生素之间的协同组合,以对抗两种最致命的医院感染—— 和 。我们挖掘生化活性数据库和文献,以识别针对这些细菌的已知高效QSIs。我们利用这些数据开发并验证了一个用于预测QSI活性的定量构效关系(QSAR)模型,然后使用该模型从已批准和正在研究的药物的Inxight数据库中识别新的潜在QSIs。然后,我们使用组合矩阵筛选方法,用 和 的十种(每种五种)临床分离株,测试了所识别的QSIs与11种现有抗生素的二元混合物。在所探索的药物组合中,31种表现出协同效应,包括涉及纳地美定和替洛曲星的混合物,这两种药物是我们的模型预测具有先前未描述的QSI活性的药物。虽然没有发现能抑制所有菌株的混合物,但哌拉西林与姜黄素、酮洛芬、吲哚美辛和吡罗昔康的组合表现出最广泛的抗菌作用。我们预计,对这些新型重新利用的QSIs与已知抗生素的组合进行进一步的临床前研究可能会产生新的临床候选药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51a5/12233667/dc530e6fcee0/nihpp-2025.01.17.633658v3-f0002.jpg

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