Attenuation of Pathway Complexity in Arginine‐Rich Peptide with Polydopamine

Dynamic peptide networks represent an attractive structural space of supramolecular polymers in the realm of emergent complexity. Point mutations in the peptide sequence exert profound effects over the landscapes of self-assembly with an intricate interplay among the structure-function relationships. Herein, the pathway complexity of an arginine-rich peptide is studied, FmocVFFARR derived by the mutation of minimalist amyloid-inspired peptide amphiphile FmocVFFAKK, thereby focusing on its pathway-dependent self-assembly behavior. Interestingly, an interplay of competing primary and secondary nucleation in this minimalist model presumably due to the sticky interactions of the di-arginine motifs is encountered. This furnishes transient nanosheets from on-pathway metastable nanoparticles upon pH trigger, eventually leading to nanofibers. Moreover, external cues, e.g., pH, and temperature convert the nanofibers in off-pathway nanoparticles. For the first time, polydopamine-based surface engineering strategy to mask the arginines is demonstrated to render permanent arrest of the dynamic, transient peptide nanostructures. Finally, such polydopamine layer over the peptide nanostructures furnishes resilience against environmental stress, while also imparting mechanical robustness to the composites. The dynamic peptide nanostructures exhibited adaptive systems capable of processing chemical information while the surface coated nanostructures open wide avenues for designing stress-resilient biomaterials.

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Publication Details

Journal
Small
Published
2024-12-24
DOI
https://doi.org/10.1002/smll.202409176
Citations
4
Primary Topic
Supramolecular Self-Assembly in Materials
Type
article
Field-Weighted Citation Impact
0.69

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article

Attenuation of Pathway Complexity in Arginine‐Rich Peptide with Polydopamine

Yadu Chandran, Aasheesh Srivastava, Asish Pal, Manas Kumar Pradhan et al.
4 citations
Small
Supramolecular Self-Assembly in Materials
0.69
article

Attenuation of Pathway Complexity in Arginine‐Rich Peptide with Polydopamine

Yadu Chandran, Aasheesh Srivastava, Asish Pal, Manas Kumar Pradhan, Viswanath Balakrishnan, Nimisha A. Mavlankar, Anand Kumar Awasthi
article en
4 citations

Abstract

Dynamic peptide networks represent an attractive structural space of supramolecular polymers in the realm of emergent complexity. Point mutations in the peptide sequence exert profound effects over the landscapes of self-assembly with an intricate interplay among the structure-function relationships. Herein, the pathway complexity of an arginine-rich peptide is studied, FmocVFFARR derived by the mutation of minimalist amyloid-inspired peptide amphiphile FmocVFFAKK, thereby focusing on its pathway-dependent self-assembly behavior. Interestingly, an interplay of competing primary and secondary nucleation in this minimalist model presumably due to the sticky interactions of the di-arginine motifs is encountered. This furnishes transient nanosheets from on-pathway metastable nanoparticles upon pH trigger, eventually leading to nanofibers. Moreover, external cues, e.g., pH, and temperature convert the nanofibers in off-pathway nanoparticles. For the first time, polydopamine-based surface engineering strategy to mask the arginines is demonstrated to render permanent arrest of the dynamic, transient peptide nanostructures. Finally, such polydopamine layer over the peptide nanostructures furnishes resilience against environmental stress, while also imparting mechanical robustness to the composites. The dynamic peptide nanostructures exhibited adaptive systems capable of processing chemical information while the surface coated nanostructures open wide avenues for designing stress-resilient biomaterials.

SmallVol. 21(6)
Indian Institute of Science Education and Research Mohali (IN), Indian Institute of Science Education and Research, Bhopal (IN), Indian Institute of Technology Mandi (IN)
Department of Science and Technology, Government of West Bengal
Life in Land
Openalex Percentile: Top 33%
Supramolecular Self-Assembly in Materials
0.69
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