A Polymer Therapeutic Having Universal Heparin Reversal Activity: Molecular Design and Functional Mechanism
Bibliographic record
Abstract
Heparins are widely used to prevent blood clotting during surgeries and for the treatment of thrombosis. However, bleeding associated with heparin therapy is a concern. Protamine, the only approved antidote for unfractionated heparin (UFH) could cause adverse cardiovascular events. Here, we describe a unique molecular design used in the development of a synthetic dendritic polycation named as universal heparin reversal agent (UHRA), an antidote for all clinically used heparin anticoagulants. We elucidate the mechanistic basis for the selectivity of UHRA to heparins and its nontoxic nature. Isothermal titration calorimetry based binding studies of UHRAs having different methoxypolyethylene glycol (mPEG) brush structures with UFH as a function of solution conditions, including ionic strength, revealed that mPEG chains impose entropic penalty to the electrostatic binding. Binding studies confirm that, unlike protamine or N-UHRA (a truncated analogue of UHRA with no mPEG chains), the mPEG chains in UHRA avert nonspecific interactions with blood proteins and provide selectivity toward heparins through a combined steric repulsion and Donnan shielding effect (a balance of F el and F steric ). Clotting assays reveal that UHRA with mPEG chains did not adversely affect clotting, and neutralized UFH over a wide range of concentrations. Conversely, N-UHRA and protamine display intrinsic anticoagulant activity and showed a narrow concentration window for UFH neutralization. In addition, we found that mPEG chains regulate the size of antidote-UFH complexes, as revealed by atomic force microscopy and dynamic light scattering studies. UHRA molecules with mPEG chains formed smaller complexes with UFH, compared to N-UHRA and protamine. Finally, fluorescence and ELISA experiments show that UHRA disrupts antithrombin-UFH complexes to neutralize heparin’s activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".