Small-Molecule Inhibitors of the Pseudaminic Acid Biosynthetic Pathway: Targeting Motility as a Key Bacterial Virulence Factor
Bibliographic record
Abstract
Helicobacter pylori is motile by means of polar flagella, and this motility has been shown to play a critical role in pathogenicity. The major structural flagellin proteins have been shown to be glycosylated with the nonulosonate sugar, pseudaminic acid (Pse). This glycan is unique to microorganisms, and the process of flagellin glycosylation is required for H. pylori flagellar assembly and consequent motility. As such, the Pse biosynthetic pathway offers considerable potential as an antivirulence drug target, especially since motility is required for H. pylori colonization and persistence in the host. This report describes screening the five Pse biosynthetic enzymes for small-molecule inhibitors using both high-throughput screening (HTS) and in silico (virtual screening [VS]) approaches. Using a 100,000-compound library, 1,773 hits that exhibited a 40% threshold inhibition at a 10 μM concentration were identified by HTS. In addition, VS efforts using a 1.6-million compound library directed at two pathway enzymes identified 80 hits, 4 of which exhibited reasonable inhibition at a 10 μM concentration in vitro. Further secondary screening which identified 320 unique molecular structures or validated hits was performed. Following kinetic studies and structure-activity relationship (SAR) analysis of selected inhibitors from our refined list of 320 compounds, we demonstrated that three inhibitors with 50% inhibitory concentrations (IC50s) of approximately 14 μM, which belonged to a distinct chemical cluster, were able to penetrate the Gram-negative cell membrane and prevent formation of flagella.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".