Rational screening of biomineralisation peptides for colour-selected one-pot gold nanoparticle syntheses

Tanaka, Masayoshi; Takahashi, Yuta; Roach, Lucien; Critchley, Kevin; Evans, Stephen D.; Okochi, Mina

doi:10.1039/c8na00075a

Cited by 19 publications

(30 citation statements)

References 47 publications

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“…After a 7-h incubation of the peptide array in an aqueous solution of 50 mM AgNO 3 in MilliQ water, individual peptide array spots were observed to change color, indicative of AgNP mineralization. The mineralization profiles using a peptide array with the same peptide library were not identical to the results of an AuNP mineralization evaluation previously reported [15]. From this observation, the mineralization mechanism associated with peptides seems to be different between AuNP and AgNP mineralization.…”

Section: Screening Of Agnp Mineralization Peptide Using Peptide Arraycontrasting

confidence: 45%

“…To screen various types of AgNP mineralization peptides, AgNP mineralization properties of the top 200 (TOP200) high AuNP-binding peptide sequences (Table S1 in [15]) were investigated. Based on the result shown in Figure 1a, approximately 50 AgNP mineralization peptides were isolated using the peptide array.…”

Section: Screening Of Agnp Mineralization Peptide Using Peptide Arraymentioning

confidence: 99%

“…Whereas various biological molecules, including pigments, nucleic acids and proteins are utilized for nanoparticle synthesis and functionalization [7][8][9][10][11][12][13], peptides also comprise promising ligand molecules 2 of 10 that bind, not only metallic ions, but also metallic crystals. This is because variants are designed abundantly from combinations using amino acids with various physicochemical properties through chemical synthesis [14][15][16][17][18]. Among a wide range of functional peptides, catalytic peptides used for nanoparticle synthesis regulation, named mineralization peptides, have commonly been isolated from peptides that are strongly bound to target crystals [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…This is because variants are designed abundantly from combinations using amino acids with various physicochemical properties through chemical synthesis [14][15][16][17][18]. Among a wide range of functional peptides, catalytic peptides used for nanoparticle synthesis regulation, named mineralization peptides, have commonly been isolated from peptides that are strongly bound to target crystals [14][15][16]. Considering the chemical equilibrium of crystalline nanoparticles and their metallic ions in solution, it has been suggested that the strong binding of peptides stabilizes the crystals, resulting in a shift in the equilibrium from an ionic state towards that of the crystal; specifically, target crystal mineralization is mediated by peptide addition.…”

Section: Introductionmentioning

confidence: 99%

“…To investigate the AgNP mineralization by peptides, peptide array technology was used to identify a list of mineralization peptides with various physicochemical properties. The peptide library was designed from an AuNP-binding peptide, previously reported, because many of these peptide sequences revealed AuNP mineralization activity [15,25]. To expand the potential for other nanoparticle synthesis, the top 200 AuNP-binding peptides were herein evaluated in terms of AgNP mineralization activity.…”

Section: Introductionmentioning

confidence: 99%

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Array-Based Screening of Silver Nanoparticle Mineralization Peptides

Tanaka

Saito

Kita

et al. 2020

IJMS

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The use of biomolecules in nanomaterial synthesis has received increasing attention, because they can function as a medium to produce inorganic materials in ambient conditions. Short peptides are putative ligands that interact with metallic surfaces, as they have the potential to control the synthesis of nanoscale materials. Silver nanoparticle (AgNP) mineralization using peptides has been investigated; however, further comprehensive analysis must be carried out, because the design of peptide mediated-AgNP properties is still highly challenging. Herein, we employed an array comprising 200 spot synthesis-based peptides, which were previously isolated as gold nanoparticle (AuNP)-binding and/or mineralization peptides, and the AgNP mineralization activity of each peptide was broadly evaluated. Among 10 peptides showing the highest AgNP-synthesis activity (TOP10), nine showed the presence of EE and E[X]E (E: glutamic acid, and X: any amino acid), whereas none of these motifs were found in the WORST25 (25 peptides showing the lowest AgNP synthesis activity) peptides. The size and morphology of the particles synthesized by TOP3 peptides were dependent on their sequences. These results suggested not only that array-based techniques are effective for the peptide screening of AgNP mineralization, but also that AgNP mineralization regulated by peptides has the potential for the synthesis of AgNPs, with controlled morphology in environmentally friendly conditions.

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Section: Screening Of Agnp Mineralization Peptide Using Peptide Arraycontrasting

confidence: 45%

Section: Screening Of Agnp Mineralization Peptide Using Peptide Arraymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Array-Based Screening of Silver Nanoparticle Mineralization Peptides

Tanaka

Saito

Kita

et al. 2020

IJMS

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Machine Learning‐Assisted Clustering of Nanoparticle‐Binding Peptides and Prediction of Their Properties

Kenry

2023

Advcd Theory and Sims

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Bioinspired and biomimetic nanostructures have attracted tremendous interest for theranostic and nanomedicine applications. Among the strategies employed to synthesize these nanostructures, surface functionalization and biomineralization of nanomaterials using peptides stand out due to the wide availability of peptides and their variations as well as the ease of modification process. Effective peptide‐based modification of nanomaterials relies on preferential and strong binding between peptides and target nanomaterials. Therefore, the discovery and design of specific peptides with high binding affinity to nanomaterials are essential. Unfortunately, conventional peptide screening methods suffer from shortcomings which render peptide discovery time‐consuming, expensive, and cumbersome. Herein, leveraging unsupervised and supervised machine learning, a framework to accelerate peptide analysis is presented. Specifically, more than 1700 nanoparticle‐binding peptides are classified into peptide clusters to identify important peptide features to realize higher‐affinity binding. In addition, the binding and biomineralization properties of peptides are predicted with high classification accuracy, precision, and recall. This work then proposes the use of unsupervised k‐means clustering and supervised k‐nearest neighbors algorithms for grouping peptides and predicting their properties, respectively. It is anticipated that the framework originated from this study will further facilitate the rational selection and design of peptides for engineering functional bioinspired and biomimetic nanostructures.

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Structure‐guided identification of a peptide for bio‐enabled gold nanoparticle synthesis

Thaker

Sirajudeen

Simmons

et al. 2021

Biotech & Bioengineering

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In this study, we show that maltose-binding protein (MBP) is capable of facilitating stable gold nanoparticle synthesis, and a structure of MBP in the presence of gold ions was determined by X-ray crystallography. Using this high-resolution structure of gold ion bound MBP, a peptide (AT1) was selected and synthesized and was shown to also aid in the synthesis of stable gold nanoparticles under similar experimental conditions to those used for protein facilitated synthesis. This structurebased approach represents a new potential method for the selection of peptides capable of facilitating stable nanoparticle synthesis.

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Rational screening of biomineralisation peptides for colour-selected one-pot gold nanoparticle syntheses

Abstract: Biomineralisation peptides that facilitate the one-pot synthesis of gold nanoparticles (AuNPs) with selected optical properties, were screened using a coherent peptide-spotted array consisting of a AuNP binding peptide library.

Cited by 19 publications

References 47 publications

Array-Based Screening of Silver Nanoparticle Mineralization Peptides

Array-Based Screening of Silver Nanoparticle Mineralization Peptides

Machine Learning‐Assisted Clustering of Nanoparticle‐Binding Peptides and Prediction of Their Properties

Structure‐guided identification of a peptide for bio‐enabled gold nanoparticle synthesis

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