Faculty Opinions recommendation of Yeast surface display platform for rapid discovery of conformationally selective nanobodies.
Bibliographic record
Abstract
Camelid single-domain antibody fragments ("nanobodies") provide the remarkable specificity of antibodies within a single 15 kDa immunoglobulin V HH domain.This unique feature has enabled applications ranging from use as biochemical tools to therapeutic agents.Nanobodies have emerged as especially useful tools in protein structural biology, facilitating studies of conformationally dynamic proteins such as G protein-coupled receptors (GPCRs).Nearly all nanobodies available to date have been obtained by animal immunization, a bottleneck restricting many applications of this technology.To solve this problem, we report a fully in vitro platform for nanobody discovery based on yeast surface display.We provide a blueprint for identifying nanobodies, demonstrate the utility of the library by crystallizing a nanobody with its antigen, and most importantly, we utilize the platform to discover conformationally-selective nanobodies to two distinct human GPCRs.To facilitate broad deployment of this platform, the library and associated protocols are freely available for non-profit research.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.063 |
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".