Peptide interactions with zigzag edges in graphene

Kuang, Zhen‐Bang; Kim, Steve S.; Ngo, Yen; McAlpine, Michael C.; Farmer, Barry L.; Naik, Rajesh R.

doi:10.1116/1.4966266

Cited by 6 publications

(7 citation statements)

References 57 publications

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“…However, many of the more recent simulation studies of the peptide–materials biointerface involve the use of advanced conformational sampling. ,,,,,− ,,,,,− That said, we reiterate here that the use of advanced conformational sampling is a necessary, but not sufficient, factor in making physically reasonable predictions of abiotic/biotic interfacial interactions; the influences of the interfacial force field and the structural model of the substrate can also exert a critical influence on the simulation outcomes. For example, Sahai and co-workers reported the use of advanced conformational sampling (using parallel tempering metadynamics) to predict the adsorption free energies and structures of the aqueous peptide/hydroxyapatite (HAP) interface .…”

Section: Bioinspired Nanotechnologymentioning

confidence: 87%

Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials

2017

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Peptide sequences are known to recognize and bind different nanomaterial surfaces, which has resulted in the screening and identification of hundreds of peptides with the ability to bind to a wide range of metallic, metal oxide, mineral, and polymer substrates. These biomolecules are able to bind to materials with relatively high affinity, resulting in the generation of a complex biointerface between the biotic and abiotic components. While the number of material-binding sequences is large, at present, quantitative materials-binding characterization of these peptides has been accomplished only for a relatively small number of sequences. Moreover, it is currently very challenging to determine the molecular-level structure(s) of these peptides in the materials adsorbed state. Despite this lack of data related to the structure and function of this remarkable biointerface, several of these peptide sequences have found extensive use in creating functional nanostructured materials for assembly, catalysis, energy, and medicine, all of which are dependent on the structure of the individual peptides and collective biointerface at the material surface. In this Review, we provide a comprehensive overview of these applications and illustrate how the versatility of this peptide-mediated approach for the growth, organization, and activation of nanomaterials could be more widely expanded via the elucidation of biointerfacial structure/property relationships. Future directions and grand challenges to realize these goals are highlighted for both experimental characterization and molecular-simulation strategies.

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Section: Bioinspired Nanotechnologymentioning

confidence: 87%

Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials

2017

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“…Molecular dynamics simulation. We have further validated the experimentally determined adsorption free energy using the adaptive biasing force method (ABF) 33,35,36 . First, we constructed the potential mean force (PMF) profile as described in the methods section.…”

Section: Free Adsorption Energy From Mp-spr Experimentsmentioning

confidence: 94%

“…To obtain the initial configuration at each window, seven constraint molecular dynamics simulations were run to bring the peptide to each window center by imposing a harmonic force on the collective variable D. To obtain smooth free energy profile, each window was divided into 60 bins so that the bin size δD Y was 0.1 Å. Therefore, the free energy difference was reconstructed by 33,36 ΔA ¼ AðD b…”

Section: Methodsmentioning

confidence: 99%

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Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

et al. 2020

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A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 kBT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations.

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“…Kuang et al found a peptide that tends to be adsorbed on the graphene edges because of having some specific residues. [ 24,36 ]…”

Section: Introductionmentioning

confidence: 99%

Mechanical loading of graphene quantum dots on Staphylococcus aureus surface protein G: A molecular dynamics study

Mousanezhad

Davoodi

2022

Biopolymers

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This research studies graphene quantum dots (GQDs) adsorption on Staphylococcus aureus surface protein G (SasG) using the molecular dynamics simulation method that in addition to investigating various aspects of adsorption, including edge and surface effects of GQDs, and effects of orientation and size of GQDs, proposes a new study method in edge effects studies. Through our simulations to find edge effects, we found that even if GQD approaches the protein with its edges, GQDs' edges are not freely adsorbed on the protein because when the particles interact with each other, GQD rotates and then adsorbs the protein with its surface; therefore, GQD having initial velocity was applied to the protein to force the protein to interact with GQDs' edges to find both surface and edge effects. This is a new way of investigating that we propose to study edge effects in the molecular dynamics simulation method.

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Peptide interactions with zigzag edges in graphene

Cited by 6 publications

References 57 publications

Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials

Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

Mechanical loading of graphene quantum dots on Staphylococcus aureus surface protein G: A molecular dynamics study

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