A deep learning-driven discovery of berberine derivatives as novel antibacterial against multidrug-resistant Helicobacter pylori

• Published in: Signal transduction and targeted therapy Vol. 9; no. 1; pp. 183 - 18
• Main Authors: Guo, Xixi, Zhao, Xiaosa, Lu, Xi, Zhao, Liping, Zeng, Qingxuan, Chen, Fenbei, Zhang, Zhimeng, Xu, Mengyi, Feng, Shijiao, Fan, Tianyun, Wei, Wei, Zhang, Xin, Pang, Jing, You, Xuefu, Song, Danqing, Wang, Yanxiang, Jiang, Jiandong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08.07.2024; Nature Publishing Group
• Subjects: 631/154/309/555; 631/154/309/556; Amoxicillin; Amoxicillin - pharmacology; Animals; Anti-Bacterial Agents - chemistry; Anti-Bacterial Agents - pharmacology; Antibiotics; Berberine; Berberine - chemistry; Berberine - pharmacokinetics; Berberine - pharmacology; Cancer Research; Cell Biology; Clarithromycin; Clarithromycin - pharmacology; Deep Learning; Drug resistance; Drug Resistance, Multiple, Bacterial - drug effects; Drug Resistance, Multiple, Bacterial - genetics; Eradication; Gastric cancer; Helicobacter Infections - drug therapy; Helicobacter Infections - microbiology; Helicobacter pylori; Helicobacter pylori - drug effects; Humans; Internal Medicine; Intestinal microflora; Medicine; Medicine & Public Health; Membrane proteins; Microbial Sensitivity Tests; Multidrug resistance; Neural networks; Omeprazole; Omeprazole - pharmacology; Oncology; Oral administration; Outer membrane proteins; Pathology; Penicillin; Pharmacokinetics; Protein transport; Strains (organisms); Tumorigenesis

Helicobacter pylori ( H. pylori ) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high prevalence and resistance make it difficult to tackle. A graph neural network-based deep learning model, employing different training sets of 13,638 mole...