Dataset Information

Bottom-up synthesis of protein-based nanomaterials from engineered ?-solenoid proteins.

ABSTRACT: Biomolecular self-assembly is an emerging bottom-up approach for the synthesis of novel nanomaterials. DNA and viruses have both been used to create scaffolds but the former lacks chemical diversity and the latter lack spatial control. To date, the use of protein scaffolds to template materials on the nanoscale has focused on amyloidogenic proteins that are known to form fibrils or two-protein systems where a second protein acts as a cross-linker. We previously developed a unique approach for self-assembly of nanomaterials based on engineering ?-solenoid proteins (BSPs) to polymerize into micrometer-length fibrils. BSPs have highly regular geometries, tunable lengths, and flat surfaces that are amenable to engineering and functionalization. Here, we present a newly engineered BSP based on the antifreeze protein of the beetle Rhagium inquisitor (RiAFP-m9), which polymerizes into stable fibrils under benign conditions. Gold nanoparticles were used to functionalize the RiAFP-m9 fibrils as well as those assembled from the previously described SBAFP-m1 protein. Cysteines incorporated into the sequences provide site-specific gold attachment. Additionally, silver was deposited on the gold-labelled fibrils by electroless plating to create nanowires. These results bolster prospects for programable self-assembly of BSPs to create scaffolds for functional nanomaterials.

SUBMITTER: Peng Z

PROVIDER: S-EPMC7034853 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Bottom-up synthesis of protein-based nanomaterials from engineered β-solenoid proteins.

Peng Zeyu Z Peralta Maria D R MDR Cox Daniel L DL Toney Michael D MD

PloS one 20200221 2

Biomolecular self-assembly is an emerging bottom-up approach for the synthesis of novel nanomaterials. DNA and viruses have both been used to create scaffolds but the former lacks chemical diversity and the latter lack spatial control. To date, the use of protein scaffolds to template materials on the nanoscale has focused on amyloidogenic proteins that are known to form fibrils or two-protein systems where a second protein acts as a cross-linker. We previously developed a unique approach for se ...[more]

PMID: 32084222

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Project description:MotivationSolenoid proteins are emerging as a protein class with properties intermediate between structured and intrinsically unstructured proteins. Containing repeating structural units, solenoid proteins are expected to share sequence similarities. However, in many cases, the sequence similarities are weak and non-detectable. Moreover, solenoids can be degenerated and widely vary in the number of units. So that it is difficult to detect them. Recently, several solenoid repeats detection methods have been proposed, such as self-alignment of the sequence, spectral analysis and discrete Fourier transform of sequence. Although these methods have shown good performance on certain data sets, they often fail to detect repeats with weak similarities. In this article, we propose a new approach to recognize solenoid repeats and non-solenoid proteins using stationary wavelet packet transform (SWPT). Our method associates with three advantages: (i) naturally representing five main factors of protein structure and properties by wavelet analysis technique; (ii) extracting novel wavelet features that can capture hidden components from solenoid sequence similarities and distinguish them from global proteins; (iii) obtaining statistics features that capture repeating motifs of solenoid proteins.ResultsOur method analyzes the characteristics of amino acid sequence in both spectral and temporal domains using SWPT. Both global and local information of proteins are captured by SWPT coefficients. We obtain and integrate wavelet-based features and statistics-based features of amino acid sequence to improve the classification task. Our proposed method is evaluated by comparing to state-of-the-art methods such as HHrepID and REPETITA. The experimental results show that our algorithm consistently outperforms them in areas under ROC curve. At the same false positive rate, the sensitivity of our WAVELET method is higher than other methods.Availabilityhttp://www.naaan.org/anvo/Software/Software.htm.

Dataset Information

Bottom-up synthesis of protein-based nanomaterials from engineered ?-solenoid proteins.

Publications

Bottom-up synthesis of protein-based nanomaterials from engineered β-solenoid proteins.

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