The multifaceted helical net of amphipathic alpha-helices; the next dimension of the helical peptide wheel
Bibliographic record
Abstract
The amphipathic nature of helical proteins is crucial to their binding features across a broad spectrum of physiological examples, including heat-shock proteins and hyaluronic acid (HA) receptor binding. By taking advantage of the amphipathic balance of amino acids and their presentation in helical faces, novel synthetic peptides can be designed to improve biofunctionality. We present a new approach for designing synthetic alpha helical peptides using a multifaceted analysis, which allows for new bioengineering designs of amphipathic alpha helices. Amphipathic helical peptides were presented with distinct hydrophobic and hydrophilic faces; two series of analogs, namely, peptides AX9 and AX7, were designed to contain a hydrophobic and hydrophilic face, respectively. The presence of one series of peptides exhibited a distinct hydrophobic face and the second series exhibited a distinct hydrophilic face, which was corroborated with reversed-phase chromatography (C8). Using a multifaceted approach to analyze the potential faces of an amphipathic helix, we demonstrated that these helices contain seven distinct “side-viewed” helical faces (based on the hydrophobic face of the AXP series of analogs), which provides additional spatial dimensional information beyond the averaging effect of the hydrophobic moment generated from the “top-down” view of a helical wheel. Furthermore, we cross-compared our recently published HA-binding peptide in this manner to demonstrate that the most significant binding was related to (1) balanced amphipathicity and (2) a distribution of the key HA-binding domain B1(X 7 )B2 presented spatially. For example, our most effective peptide binder 17x-3 has five of seven faces with B1(X 7 )B2 domains, while the positive control mPEP35 has three, which reflects a lower affinity. With such a tool, one is able to map helical peptides on an additional dimension to characterize and redesign fundamental amphipathic properties among other critical characteristics, such as sugar and glycan binding, which is a fundamental characteristic feature of cellular interactions in almost every biological system.
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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".