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

Abstract

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 molecules for pre-training and fine-tuning, was aided in predicting and exploring novel molecules against H. pylori. A positively predicted novel berberine derivative 8 with 3,13-disubstituted alkene exhibited a potency against all tested drug-susceptible and resistant H. pylori strains with minimum inhibitory concentrations (MICs) of 0.25-0.5 μg/mL. Pharmacokinetic studies demonstrated an ideal gastric retention of 8, with the stomach concentration significantly higher than its MIC at 24 h post dose. Oral administration of 8 and omeprazole (OPZ) showed a comparable gastric bacterial reduction (2.2-log reduction) to the triple-therapy, namely OPZ + amoxicillin (AMX) + clarithromycin (CLA) without obvious disturbance on the intestinal flora. A combination of OPZ, AMX, CLA, and 8 could further decrease the bacteria load (2.8-log reduction). More importantly, the mono-therapy of 8 exhibited comparable eradication to both triple-therapy (OPZ + AMX + CLA) and quadruple-therapy (OPZ + AMX + CLA + bismuth citrate) groups. SecA and BamD, playing a major role in outer membrane protein (OMP) transport and assembling, were identified and verified as the direct targets of 8 by employing the chemoproteomics technique. In summary, by targeting the relatively conserved OMPs transport and assembling system, 8 has the potential to be developed as a novel anti-H. pylori candidate, especially for the eradication of drug-resistant strains.

Fig. 1

Establishment of the deep learning model. a Deep learning-based anti-H. pylori compound discovery. SMILES simplified molecular input line entry system. b A pie chart for data distributions, including three pre-train sets, a fine-tune set and a test set. c ROC-AUC plot evaluating model performance under the ten-fold cross-validation. d t-Distributed stochastic neighbor embedding (t-SNE) of all molecules from the pre-training, fine tune, and test set, revealing chemical relationships between these compounds

Fig. 2

In vivo antibacterial evaluations for compound 8. a Chemical structures of BBR and 8. b Serum biochemical indices of liver and kidney functions for mice in different treatment groups (n = 6). c Plasma and stomach concentration–time profiles of 8 following a single oral dose of 30 mg/kg (n = 4). d The schematic diagram of H. pylori infection and treatment process in C57BL/6 mice. e, g The viable counts in the stomach of mice infected with H. pylori CCPM(A)-P-3722159 in each group (n = 5) after different treatments. The administration dosage of each treatment component is as follows: OPZ (200 μg/kg); 8 (30 mg/kg); AMX (15 mg/kg); CLA (15 mg/kg); CMC, carboxymethyl cellulose; AC, AMX + CLA; Bi, bismuth citrate (5 mg/kg). f Hematoxylin and eosin (H&E) staining of stomach tissues

Fig. 3

Gut microbiome analysis in different treatment groups (n = 5). Uninfect, the uninfected group; CMC, vehicle control group; T8, dual therapy group (OPZ + 8); AC, triple therapy group (OPZ + AC); AC8, quadruple therapy group (OPZ + AC + 8). a The Venn diagram of microbial characteristic sequences of each treatment group. b Alpha diversity analysis on microbiota diversity of each treatment group. c Beta diversity of PCoA analysis. d A bar plot analysis at the genus level (ten bacterial genera with the highest abundance). e A heatmap analysis at the genus level (ten bacterial genera with the highest abundance). f LDA value distribution histogram revealed by LEfSe software. When species with LDA Score >4 are statistically different, the length of the histogram (LDA Score) represent the impact size of the different species. g Evolutionary branching trees from the inside out in a clade represent the level of phylum, class, order, family, genus

Fig. 4

Mechanism of action and direct targets exploration on compound 8. a, b Images for morphology of H. pylori under electron microscope (a) SEM images of H. pylori treated without (upper) or with (lower) 8. b TEM images of H. pylori treated without (upper) or with (lower) 8. c The structure of the active photoaffinity probe 8-O. d Cy3-labeled target proteins were identified using fluorescent gel imaging. SecA (e) and BamD (f) were pulled down from H. pylori by using probe 8-O in immunoblot assay. SecA and BamD pulled down by 8-O were competitively inhibited by 8. The recombinant SecA (g) and BamD (h) proteins pulled down by 8-O were competitively inhibited by 8. Surface plasmon resonance (SPR) sensorgrams obtained on SecA (i)/BamD (j)-coated chips at different concentrations of 8. The thermal stability of SecA (k)/BamD (l) proteins with or without 8-treatment (n = 3)

Fig. 5

The exploration of active binding sites between 8 and SecA/BamD. a Experimental workflow for binding site and interaction residues investigation and validation based on LC-MS/MS analysis. The predicted docking patterns between 8 and SecA (b)/BamD (d) were performed by Discovery Studio 4.5 software based on the peptide fragment difference identification results of LC-MS/MS analysis. Specific binding pattern between 8 and SecA (c)/BamD (e)

Fig. 6

Compound 8 disturbs the OMPs related gene transcription and inhibits the protein function of SecA and BamD. a, b Transcriptome analysis of H. pylori with or without the treatment of 8 (n = 3). a Volcano plot analysis (Red dots: 239 up-regulated genes; Green dots: 302 down-regulated genes), and (b) KEGG analysis. c The differential expression genes at transcriptional level related to the OMPs secretion and transport dysfunction. d RT-qPCR verifications on gene transcription of the key H. pylori OMPs after the treatment of 8 (n = 3). e Inhibition of 8 on the ATPase activity of SecA (n = 3). f The interaction of BamA and BamD was inhibited by 8 in Co-IP analysis. g The change of the total amount of H. pylori OMPs after the treatment of 8. h, i Confocal analysis on adhesive effect of 8-treated H. pylori to GES-1 cells. No treatment group (h); 8 treatment group (i). For cell nucleic acid staining: 4’,6-diamidino2-phenylindole (DAPI); for cell membrane staining: 1,1’-Dioctadecyl-3,3,3’,3’-tetramethylindodicarbocyanine, 4-chlorobenzenesulfonate salt (DiD); for bacteria staining: fluorescein isothiocyanate (FITC)

Fig. 7

Cartoon of the mechanism of action of 8 (By Figdraw)