Characterization of the structure and self-assembly of two distinct class IB hydrophobins
Bibliographic record
Abstract
Abstract Hydrophobins are small proteins secreted by fungi that accumulate at interfaces, modify surface hydrophobicity, and self-assemble into large amyloid-like structures. These unusual properties make hydrophobins an attractive target for commercial applications as emulsifiers and surface modifying agents. Hydrophobins have diverse sequences and tertiary structures, complicating attempts to characterize how they function. Here we describe the atomic resolution structure of the unusual hydrophobin SLH4 and compare its function to another hydrophobin, SC16. Despite containing only one charged residue, SLH4 has a similar structure to SC16 yet has strikingly different rodlet morphology and propensity to self-assemble. Secondary structure analysis of both SC16 and SLH4 before and after assembly suggest that residues in the first intercysteine loop undergo conformational changes. This work outlines a representative structure for class IB hydrophobins and illustrates how hydrophobin surface properties govern self-assembly, which provides context to rationally select hydrophobins for applications as surface modifiers. Keypoints -The atomic-resolution structure of the hydrophobin SLH4 was determined using nuclear magnetic resonance spectroscopy -The structure of SLH4 outlines a representative structure for class IB hydrophobins -The assembly characteristics of SLH4 and SC16 are strikingly different, outlining how surface properties of hydrophobins influence their function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".