Structural Elucidation of a Polypeptoid Chain in a Crystalline Lattice Reveals Key Morphology-Directing Role of the N-Terminus
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The ability to engineer synthetic polymers with the same structural precision as biomacromolecules is crucial to enable the de novo design of robust nanomaterials with biomimetic function. Peptoids, poly( N -substituted) glycines, are a highly controllable bio-inspired polymer family that can assemble into a variety of functional, crystalline nanostructures over a wide range of sequences. Extensive investigation on the molecular packing in these lattices has been reported; however, many key atomic-level details of the molecular structure remain underexplored. Here, we use cryo-TEM 3D reconstruction to directly visualize the conformation of an individual polymer chain within a peptoid nanofiber lattice in real space at 3.6 Å resolution. The backbone in the N -decylglycine hydrophobic core is shown to clearly adopt an extended, all- cis -sigma strand conformation, as previously suggested in many peptoid lattice models. We also show that packing interactions (covalent and noncovalent) at the solvent-exposed N-termini have a dominant impact on the local chain ordering and hence the ability of the chains to pack into well-ordered lattices. Peptoids in pure water form fibers with limited growth in the a direction (<14 molecules in width), whereas in the presence of formamide, they grow to over microns in length in the a direction. This dependence points to the significant role of the chain terminus in determining the long-range order in the packing of peptoid lattices and provides an opportunity to modulate lattice stability and nanoscale morphology by the addition of exogenous small molecules. These findings help resolve a major challenge in the de novo structure-based design of sequence-defined biomimetic nanostructures based on crystalline domains and should accelerate the design of functional nanostructures.
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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".