Discovery of novel polymyxin E adjuvants against Acinetobacter baumannii guided by a stacking-based machine learning model

RSC Medicinal Chemistry 2026 Open access

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Authors: Yuce Chen, Kunkun Shen, Ting Lin, Daijie Chen, Zhong Li, Yuheng Yang, Xiaoyong Xu
DOI: 10.1039/d5md00768b
Cited by: 0
References: 68

Abstract

ADMET profile evaluation demonstrated that F26 possessed good pharmacokinetic profiles and drug-likeness properties. Shapley Additive exPlanations (SHAP) analysis elucidated the relationship between molecular substructures and potentiating activity. This study demonstrated the power of machine learning in identifying novel antibiotic adjuvants, offering an innovative approach to combat antibiotic resistance.

Fields of Study & Subjects

Antibiotic Resistance in Bacteria Computational Drug Discovery Methods vaccines and immunoinformatics approaches

Publication details

Journal / source
RSC Medicinal Chemistry
Volume
17
Issue
2
Pages
1050–1065
Publication date
1 January 2026
Language
EN