Microtubule-Inspired Functionalization of Carbon Nanotubes: A Biomimetic Carrier Design
Bibliographic record
Abstract
Abstract We propose a bioinspired, non-covalent carbon nanotubes (CNTs) functionalization strategy to augment their bioavailability and alleviate their biotoxicity. For functionalization, select amphiphilic peptides from a cytoskeletal biopolymer, microtubule (MT), were used. The peptides are involved in the MT polymerization by maintaining the essential lateral interactions among the MT’s α- and β-tubulin subunits. They also participate in forming the MT-binding sites for hosting several MT-targeting antimitotics. Utilizing in silico methods, this study showed the peptides influenced CNT’s diffusivity and aqueous solubility. The hydrodynamic shield formed by the peptides from β-tubulin was more widespread on the CNT than the α-tubulin peptides’; however, the latter created a broader hydrophobic CNT coating than those from the β-tubulin. In particular, the peptides consisting of the H1-B2, H10, H1-B2, and the M-loop, demonstrated structural features that serve to augment CNTs’ water solubility and dispersibility. The performance of the peptide-functionalized CNTs as drug carriers was examined by studying seventeen antimitotics. The CNT-peptides structural composition was identified as a suitable carrier for phomopsin A, laulimalide, epothilone A, epothilone D, discodermolide, eribulin, and docetaxel. The peptides played dual roles displaying affinities to the antimitotics and the CNT; in particular, the peptides from the H1-B2 and H2-B3 loops of β-tubulin exhibited exceptional binding properties. Specific mutations on the wildtype peptides, including those from the α-tubulin M-loop and H2-B3, or the β-tubulin H1-B2, are proposed to refine their hydrophobicity, eliminate unfavorable inter-peptides electrostatic interactions or the spatial hindrance at certain regions, to enhance their conformational steadiness and exposure to the tube surface. A combination of the select amphiphilic peptides from both tubulin subunits is suggested to improve CNTs bioavailability and efficiency for carrying insoluble hydrophobic cargos.
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 | 0.001 | 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".