Favorable adsorption of capped amino acids on graphene substrate driven by desolvation effect

Dragneva, Nadiya; Floriano, Wely B.; Stauffer, Douglas; Mawhinney, Robert C.; Fanchini, Giovanni; Rubel, Oleg

doi:10.1063/1.4828437

Cited by 38 publications

(78 citation statements)

References 45 publications

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“…Previous studies using non-polarisbale FFs have shown a correlation between the enthalpy of adsorption and either the mass or hydrophilicity of the AAs. [39][40][41] The free-energies calculated here showed little correlation with either. While Arg, Gln, and Trp all possess large side-chains, Gly has the smallest sidechain of the set and yet also adsorbs strongly.…”

Section: Adsorption Free Energy Of Amino Acidsmentioning

confidence: 82%

“…However, a number of previous studies have reported calculations of the adsorption enthalpy of AAs on graphene. [39][40][41]44 In these previous studies, Pandey et al used the, non-polarisable, AMBER ff99SB FF and calculated ∆H ads for capped AAs. While Camden et al calculated ∆H ads for G-X-G tripeptides (in the zwitterionic form) using the non-polarisbale TEAM FF.…”

Section: Adsorption Free Energy Of Amino Acidsmentioning

confidence: 99%

“…However, such simulations have a significant computational cost, are technically challenging to perform, and produce results with very large error estimates. In contrast, the determination of the adsorption free-energy/enthalpy of individual AAs [39][40][41]44,51 can achieved more readily. While the interplay between the peptide sequence, adsorbed conformation(s), and peptideinterface binding means we cannot simply assume that a residue within a peptide will adsorb in the same manner as the corresponding AA, 18,30,66,67 such data do provide a valuable benchmark that can be used to interpret results from both simulation and experiment.…”

Section: Introductionmentioning

confidence: 99%

“…[36][37][38][39][40][41][42][43][44] In all of these cases, the FF used captured the interaction between the adsorbates and the graphitic interface solely through van der Waals interactions, i.e. neglecting polarisation effects.…”

Section: Introductionmentioning

confidence: 99%

“…While the interplay between the peptide sequence, adsorbed conformation(s), and peptideinterface binding means we cannot simply assume that a residue within a peptide will adsorb in the same manner as the corresponding AA, 18,30,66,67 such data do provide a valuable benchmark that can be used to interpret results from both simulation and experiment. A number of studies have recently reported calculations of the adsorption enthalpies of all twenty AAs to graphene under aqueous conditions, using a variety of different FFs, [39][40][41] none of which are polarisable. However, to the authors knowledge, the only reported free-energies of adsorption for AAs are in our previous study outlining the development of the GRAPPA FF, 51 where free energies of adsorption where calculated for eight AAs (Ala, Arg, Asp, Gly, HisA, Phe, Tyr and Trp).…”

Section: Introductionmentioning

confidence: 99%

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What makes a good graphene-binding peptide? Adsorption of amino acids and peptides at aqueous graphene interfaces

2015

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Investigation of the non-covalent interaction of biomolecules with aqueous graphene interfaces is a rapidly expanding area. However, reliable exploitation of these interfaces in many applications requires that the links between the sequence and binding of the adsorbed peptide structures be clearly established. Molecular dynamics (MD) simulations can play a key role in elucidating the conformational ensemble of peptides adsorbed at graphene interfaces, helping to elucidate these rules in partnership with experimental characterisation. We apply our recently-developed polarisable force-field for biomolecule-graphene interfaces, GRAPPA, in partnership with advanced simulation approaches, to probe the adsorption behaviour of peptides at aqueous graphene. First we determine the free energy of adsorption of all twenty naturally occurring amino acids (AAs) via metadynamics simulations, providing a benchmark for interpreting peptide-graphene adsorption studies. From these free energies, we find that strong-binding amino acids have flat and/or compact side chain groups, and we relate this behaviour to the interfacial solvent structuring. Second, we apply replica exchange with solute tempering simulations to efficiently and widely sample the conformational ensemble of two experimentally-characterised peptide sequences, P1 and its alanine mutant P1A3, in solution and adsorbed on graphene. For P1 we find a significant minority of the conformational ensemble possesses a helical structure, both in solution and when adsorbed, while P1A3 features mostly extended, random-coil conformations. In solution this helical P1 configuration is stabilised through favourable intra-peptide interactions, while the adsorbed structure is stabilised via interaction of four strongly-binding residues, identified from our metadynamics simulations, with the aqueous graphene interface. Our findings rationalise the performance of the P1 sequence as a known graphene binder.

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Section: Adsorption Free Energy Of Amino Acidsmentioning

confidence: 82%

Section: Adsorption Free Energy Of Amino Acidsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

What makes a good graphene-binding peptide? Adsorption of amino acids and peptides at aqueous graphene interfaces

2015

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Rational Design of Peptide Biorecognition Elements on Carbon Nanotubes for Sensing Volatile Organic Compounds

Sim

Kuang

Sant'Anna

et al. 2022

Adv Materials Inter

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compounds. Exhaled breath is one of the most accessible and zero-invasive samples to monitor human health and performance. For example, recent studies have demonstrated that analyzing the exhaled breath is practical for fast-diagnosing of COVID-19. [1,2] Volatile organic compounds (VOCs) [3][4][5][6] in the exhaled breath serve as performance-related biomarkers providing rich information on human physiological/physical statuses [7][8][9][10][11] such as psychological stress and fatigue level. A miniaturized sensor is key to building a wearable sensing suite with the capability to monitor human breath. Conventional VOC detection tools are either bulky or non-selective. For example, gas chromatography-mass spectrometry (GC-MS) is accepted as a gold standard for measuring breath VOCs. [12][13][14] However, GC-MS is bulky due to its heating and vacuum systems and requires a long operation time due to the VOC sampling and separation process. Photo-ionized detectors (PIDs) are another commercial off-the-shelf, portable VOC sensors commonly applied to gas sensing. [15,16] These sensors (VOC-TRAQ, MOCON, Inc., Minneapolis, MN, USA) range their dimensions Carbon nanotube (CNT) chemiresistors have emerged as miniaturized platforms for wearable volatile organic compound (VOC) sensors. As a promising biorecognition element (BRE), a short peptide can functionalize CNT to be sensitive and selective to target VOCs. However, unveiling the VOCoptimized peptide-CNT pair for gas-phase sensing remains unclear. Here, a novel multimodal molecular toolset for designing, building, and probing suitable BRE-CNT sensors using machine learning, molecular dynamics, and near-edge X-ray absorption fine structure spectroscopy is presented. This computational and experimental suite predicts the peptide conformation on the CNT surface and probes how the peptide-CNT interfaces affect the VOC sensing. Then, peptide-functionalized CNT chemiresistors are tested against various VOCs to confirm the efficacy of the toolkit. The results show that the vertically oriented peptide on the CNT surface hinders VOC access to the peptide-CNT interface, resulting in a significantly lower sensor signal than the CNT chemiresistor with the horizontally oriented peptide. The interactive computational and experimental results strongly indicate that a peptide conformation plays an important role in VOC sensing sensitivity.

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Predictions of Pattern Formation in Amino Acid Adlayers at the In Vacuo Graphene Interface: Influence of Termination State

Awuah

Walsh

2019

Small

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Controlled self‐assembly of biomolecules on graphene offers a pathway for realizing its full potential in biological applications. Microscopy has revealed the self‐assembly of amino acid adlayers into dimer rows on nonreactive substrates. However, neither the spontaneous formation of these patterns, nor the influence of amino acid termination state on the formation of patterns has been directly resolved to date. Molecular dynamics simulations, with the ability to reveal atomic level details and exert full control over the termination state, are used here to model initially disordered adlayers of neutral, zwitterionic, and neutral–zwitterionic mixtures for two types of amino acids, tryptophan and methionine, adsorbed on graphene in vacuo. The simulations of the zwitterion‐containing adlayers exhibit the spontaneous emergence of dimer row ordering, mediated by charge‐driven intermolecular interactions. In contrast, adlayers containing only neutral species do not assemble into ordered patterns. It is also found that the presence of trace amounts of water reduces the interamino acid interactions in the adlayers, but does not induce or disrupt pattern formation. Overall, the findings reveal the balance between the lateral interamino acid interactions and amino acid–graphene interactions, providing foundational insights for ultimately realizing the predictable pattern formation of biomolecules adsorbed on unreactive surfaces.

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Favorable adsorption of capped amino acids on graphene substrate driven by desolvation effect

Cited by 38 publications

References 45 publications

What makes a good graphene-binding peptide? Adsorption of amino acids and peptides at aqueous graphene interfaces

What makes a good graphene-binding peptide? Adsorption of amino acids and peptides at aqueous graphene interfaces

Rational Design of Peptide Biorecognition Elements on Carbon Nanotubes for Sensing Volatile Organic Compounds

Predictions of Pattern Formation in Amino Acid Adlayers at the In Vacuo Graphene Interface: Influence of Termination State

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