Effect of Sequence on the Ionization Behavior of a Series of Amphiphilic Polypeptides
Bibliographic record
Abstract
The behavior of five polypeptides made of hydrophilic and pH-responsive aspartic acid (Asp) and hydrophobic phenylalanine (Phe), which had been prepared by stitching together short well-defined sequences of Asp and Phe, was studied as a function of pH. The effect of pH on these polypeptides referred to as (Asp3Phe1)n, (Asp2Phe1)n, (Asp1Phe1)n, (Asp1Phe2)n, and (Asp1Phe3)n varied dramatically depending on their constituting sequence. The more hydrophobic polypeptides (Asp1Phe2)n and (Asp1Phe3)n behaved as if the Asp's were isolated from each other and showed an apparent pKa (pKa(app)) that remained constant with level of ionization (α = [Asp(-)]/[Asp]total) and equaled 5.4 and 6.4, respectively. The more hydrophilic polypeptides (Asp3Phe1)n and (Asp2Phe1)n behaved like weak polyacids showing a linear increase in pKa(app) with increasing α. The pKa(app) of (Asp1Phe1)n showed a trend as a function of α intermediate between the Asp-rich and Phe-rich polypeptides, behaving as if the Asp's were isolated at low α values (<0.35) but acting as a weak polyacid for large α values (>0.35). The effect that α, and thus the charge density of the polypeptides, had on the collapse and aggregation of the polypeptides was characterized by conducting static light scattering and fluorescence measurements. Static light scattering measurements demonstrated that all polypeptides precipitated and aggregated in solution at a critical charge density of 0.2. Fluorescence measurements with pyrene indicated that this behavior was due to the formation of Phe aggregates in water. Together, these experiments provide a complete description of how pH affects the behavior of a series of unique amphiphilic polypeptides designed with a well-defined sequence.
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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 | 0.000 | 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) | 0.000 | 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".