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Manifold of self-assembly of a de novo designed peptide: amyloid fibrils, peptide bundles, and fractals.

ABSTRACT: We report that a peptide with the sequence of EGAGAAAAGAGE can have different aggregation states, viz., amyloid fibrils, peptide bundles, and fractal assembly under different incubation conditions. The chemical state of the Glu residue played a pivotal regulating role in the aggregation behavior of the peptide. The mechanism of the fractal assembly of this peptide has been unraveled as follows. The peptide fragments adopting the beta-sheet conformation are well dispersed in alkaline solution. In the buffer of sodium bicarbonate, peptide rods are formed with considerable structural rigidity at the C- and N-termini. The peptide rods undergo random trajectory in the solution and form a fractal pattern on a two-dimensional surface via the diffusion-limited aggregation process.

SUBMITTER: Chao YJ

PROVIDER: S-EPMC9055936 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Manifold of self-assembly of a <i>de novo</i> designed peptide: amyloid fibrils, peptide bundles, and fractals.

Chao Yu-Jo YJ Wu Kan K Chang Hsun-Hui HH Chien Ming-Jou MJ Chan Jerry Chun Chung JCC

RSC advances 20200810 49

We report that a peptide with the sequence of EGAGAAAAGAGE can have different aggregation states, <i>viz.</i>, amyloid fibrils, peptide bundles, and fractal assembly under different incubation conditions. The chemical state of the Glu residue played a pivotal regulating role in the aggregation behavior of the peptide. The mechanism of the fractal assembly of this peptide has been unraveled as follows. The peptide fragments adopting the beta-sheet conformation are well dispersed in alkaline solut ...[more]

PMID: 35521097

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Project description:Antimicrobial resistance is a great public health concern that is now described as a "silent pandemic". The global burden of antimicrobial resistance requires new antibacterial treatments, especially for the most challenging multidrug-resistant bacteria. There are various mechanisms by which bacteria develop antimicrobial resistance including expression of β-lactamase enzymes, overexpression of efflux pumps, reduced cell permeability through downregulation of porins required for β-lactam entry, or modifications in penicillin-binding proteins. Inactivation of the β-lactam antibiotics by β-lactamase enzymes is the most common mechanism of bacterial resistance to these agents. Although several effective small-molecule inhibitors of β-lactamases such as clavulanic acid and avibactam are clinically available, they act only on selected class A, C, and some class D enzymes. Currently, none of the clinically approved inhibitors can effectively inhibit Class B metallo-β-lactamases. Additionally, there is increased resistance to these inhibitors reported in several bacteria. The objective of this study is to use the Resonant Recognition Model (RRM), as a novel strategy to inhibit/modulate specific antimicrobial resistance targets. The RRM is a bio-physical approach that analyzes the distribution of energies of free electrons and posits that there is a significant correlation between the spectra of this energy distribution and related protein biological activity. In this study, we have used the RRM concept to evaluate the structure-function properties of a group of 22 β-lactamase proteins and designed 30-mer peptides with the desired RRM spectral periodicities (frequencies) to function as β-lactamase inhibitors. In contrast to the controls, our results indicate 100% inhibition of the class A β-lactamases from Escherichia coli and Enterobacter cloacae. Taken together, the RRM model can likely be utilized as a promising approach to design β-lactamase inhibitors for any specific class. This may open a new direction to combat antimicrobial resistance.

Dataset Information

Manifold of self-assembly of a de novo designed peptide: amyloid fibrils, peptide bundles, and fractals.

Publications

Manifold of self-assembly of a <i>de novo</i> designed peptide: amyloid fibrils, peptide bundles, and fractals.

Similar Datasets

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