A Fluorogenic Disaccharide Substrate for α-Mannosidases Enables High-Throughput Screening and Identification of an Inhibitor of the GH92 Virulence Factor from <i>Streptococcus pneumoniae</i>
Bibliographic record
Abstract
Trimming of host glycans is a mechanism that is broadly employed by both commensal and pathogenic microflora to enable colonization. Host glycan trimming by the opportunistic Gram-positive bacterium Streptococcus pneumoniae has been demonstrated to be an important mechanism of virulence. While S. pneumoniae employs a multitude of glycan processing enzymes, the exo -mannosidase SpGH92 has been shown to be an important virulence factor. Accordingly, SpGH92 is hypothesized to be a target for much-needed new treatments of S. pneumoniae infection. Here we report the synthesis of 4-methylumbelliferyl α- d -mannopyranosyl-(1→2)-β- d -mannopyranoside (Manα1,2Manβ-4MU) as a fluorogenic disaccharide substrate and development of an assay for SpGH92 that overcomes its requirement for +1 binding site occupancy. We miniaturize our in vitro assay and apply it to a high-throughput screen of >65 000 compounds, identifying a single inhibitory chemotype, LIPS-343. We further show that Manα1,2Manβ-4MU is also a substrate of the human Golgi-localized α-mannosidase MAN1A1, suggesting that this substrate should be useful for assessing the activity of this and other mammalian α-mannosidases.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".