Heparin Antagonism by Polyvalent Display of Cationic Motifs on Virus‐Like Particles
Bibliographic record
Abstract
Particles to the rescue! The construction of cationic amino acid motifs on the surface of bacteriophage Qbeta by genetic engineering or chemical conjugation gives particles that are potent inhibitors of the anticoagulant action of heparin, which is a common anticlotting agent subject to clinical overdose.Polyvalent interactions allow biological structures to exploit low-affinity ligand-receptor binding events to affect physiological responses. We describe here the use of bacteriophage Qbeta as a multivalent platform for the display of polycationic motifs that act as heparin antagonists. Point mutations to the coat protein allowed us to generate capsids bearing the K16M, T18R, N10R, or D14R mutations; because 180 coat proteins form the capsid, the mutants provide a spectrum of particles differing in surface charge by as much as +540 units (K16M vs. D14R). Whereas larger poly-Arg insertions (for example, C-terminal Arg(8)) did not yield intact virions, it was possible to append chemically synthesized oligo-Arg peptides to stable wild-type (WT) and K16M platforms. Heparin antagonism by the particles was evaluated by using the activated partial thrombin time (aPTT) clotting assay; this revealed that T18R, D14R, and WT-(R(8)G(2))(95) were the most effective at disrupting heparin-mediated anticoagulation (>95 % inhibition). This activity agreed with measurements of zeta potential (ZP) and retention time on cation exchange chromatography for the genetic constructs, which distribute their added positive charge over the capsid surface (+180 and +360 for T18R and D14R relative to WT). The potent activity of WT-(R(8)G(2))(95), despite its relatively diminished overall surface charge is likely a consequence of the particle's presentation of locally concentrated regions with high positive charge density that interact with heparin's extensively sulfated domains. The engineered cationic capsids retained their ability to inhibit heparin at high concentrations and showed no anticlotting activity of the kind that limits the utility of antiheparin polycationic agents that are currently in clinical use.
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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) | 0.001 | 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".