Multivalent designed proteins protect against SARS-CoV-2 variants of concern
Bibliographic record
Abstract
Abstract Escape variants of SARS-CoV-2 are threatening to prolong the COVID-19 pandemic. To address this challenge, we developed multivalent protein-based minibinders as potential prophylactic and therapeutic agents. Homotrimers of single minibinders and fusions of three distinct minibinders were designed to geometrically match the SARS-CoV-2 spike (S) trimer architecture and were optimized by cell-free expression and found to exhibit virtually no measurable dissociation upon binding. Cryo-electron microscopy (cryoEM) showed that these trivalent minibinders engage all three receptor binding domains on a single S trimer. The top candidates neutralize SARS-CoV-2 variants of concern with IC 50 values in the low pM range, resist viral escape, and provide protection in highly vulnerable human ACE2-expressing transgenic mice, both prophylactically and therapeutically. Our integrated workflow promises to accelerate the design of mutationally resilient therapeutics for pandemic preparedness. One-Sentence Summary We designed, developed, and characterized potent, trivalent miniprotein binders that provide prophylactic and therapeutic protection against emerging SARS-CoV-2 variants of concern.
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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) | 0.003 | 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".