Exploiting Peptide Nanostructures To Construct Functional Artificial Ion Channels
Bibliographic record
Abstract
Natural ion channel proteins possess remarkable properties that researchers could exploit to develop nanochemotherapeutics and diagnostic devices. Unfortunately, the poor stability, limited availability, and complexity of these structures have precluded their use in practical devices. One solution to these limitations is to develop simpler molecular systems through chemical synthesis that mimic the salient properties of artificial ion channels. Inspired by natural channel proteins, our group has developed a family of peptide nanostructures thatcreate channels for ions by aligning crown ethers on top of each other when they adopt an α-helical conformation. Advantages to this crown ether/peptide framework approach include the ease of synthesis, the predictability of their conformations, and the ability to fine-tune and engineer their properties. We have synthesized these structures using solid phase methods from artificial crown ether amino acids made from L-DOPA. Circular dichroism and FTIR spectroscopy studies in different media confirmed that the nanostructures adopt the predicted α-helical conformation. Fluorescence studies verified the crown ether stacking arrangement. We confirmed the channel activity by single-channel measurements using a modified patch-clamp technique, planar lipid bilayer (PLB) assays, and various vesicle experiments. From the results, we estimate that a 6 Å distance between two relays is ideal for sodium cation transport, but relatively efficient ion transport can still occur with an 11 Å distance between two crown ethers. Biophysical studies demonstrated that peptide channels operate as monomers in an equilibrium between adsorption at the surface and an active, transmembrane orientation. Toward practical applications of these systems, we have prepared channel analogs that bear a biotin moiety, and we have used them as nanotransducers successfully to detect avidin. Analogs of channel peptide nanostructures showed cytotoxicity against breast and leukemia cancer cells. Overall, we have prepared well-defined nanostructures with designed properties, demonstrated their transport abilities, and described their mechanism of action. We have also illustrated the advantages and the versatility of polypeptides for the construction of functional nanoscale artificial ion channels.
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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) | 0.000 | 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 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".