Defining the Structural Basis of Human Plasminogen Binding by Streptococcal Surface Enolase
Bibliographic record
Abstract
The flesh-eating bacterium group A Streptococcus (GAS) binds and activates human plasminogen, promoting invasive disease. Streptococcal surface enolase (SEN), a glycolytic pathway enzyme, is an identified plasminogen receptor of GAS. Here we used mass spectrometry (MS) to confirm that GAS SEN is octameric, thereby validating in silico modeling based on the crystal structure of Streptococcus pneumoniae alpha-enolase. Site-directed mutagenesis of surface-located lysine residues (SEN(K252 + 255A), SEN(K304A), SEN(K334A), SEN(K344E), SEN(K435L), and SEN(Delta434-435)) was used to examine their roles in maintaining structural integrity, enzymatic function, and plasminogen binding. Structural integrity of the GAS SEN octamer was retained for all mutants except SEN(K344E), as determined by circular dichroism spectroscopy and MS. However, ion mobility MS revealed distinct differences in the stability of several mutant octamers in comparison with wild type. Enzymatic analysis indicated that SEN(K344E) had lost alpha-enolase activity, which was also reduced in SEN(K334A) and SEN(Delta434-435). Surface plasmon resonance demonstrated that the capacity to bind human plasminogen was abolished in SEN(K252 + 255A), SEN(K435L), and SEN(Delta434-435). The lysine residues at positions 252, 255, 434, and 435 therefore play a concerted role in plasminogen acquisition. This study demonstrates the ability of combining in silico structural modeling with ion mobility-MS validation for undertaking functional studies on complex protein structures.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".