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Molecular simulation insights on the in vacuo adsorption of amino acids on graphene oxide surfaces with varying surface oxygen densities

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Abstract

In this fundamental study, a series of molecular dynamics simulations were performed in vacuo to investigate the energetics and select geometries of 20 standard amino acids (AAs) on pristine graphene (PG) and graphene oxide (GO) surfaces as a function of graphene surface oxygen density. These interactions are of key interest to graphene/biomolecular systems. Our results indicate that aromatic AAs exhibit the strongest total interactions with the PG surfaces due to π-π stacking. Tryptophan (Trp) has the highest aromaticity due to its indole side chain and, hence, has the strongest interaction among all AAs (−16.66 kcal/mol). Aliphatic, polar, and charged AAs show various levels of affinity to the PG sheets depending on the strength of their side chain hydrophobic interactions. For example, arginine (Arg) with its guanidinium side chain exhibits the strongest interaction with the PG sheets (−13.81 kcal/mol) following aromatic AAs. Also, glycine (Gly; a polar AA) has the weakest interaction with the PG sheets (−7.29 kcal/mol). When oxygen-containing functional groups are added to the graphene sheets, the π-π stacking in aromatic AAs becomes disrupted and perfect parallelism of the aromatic rings is lost. Moreover, hydrogen bonding and/or electrostatic interactions become more pronounced. Charged AAs exhibit the strongest interactions with the GO surfaces. In general, the AA-GO interactions increase with increasing surface oxygen density, and the effect is more pronounced at higher O/C ratios. This study provides a quantitative measure of AA-graphene interactions for the design and tuning of biomolecular systems suitable for biosensing, drug delivery, and gene delivery applications.

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Acknowledgments

This work was sponsored by the National Science Foundation (NSF) EPSCoR: Modeling and Simulation of Complex Systems Seed Research Grant Program through Mississippi State University under the award number EPS-0903787 (CFDA 47.081).

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Authors and Affiliations

  1. Department of Chemical Engineering, University of Mississippi, University, MS, 38677, USA

    Farzin Rahmani, Sasan Nouranian & Mina Mahdavi

  2. Department of Civil Engineering, University of Mississippi, University, MS, 38677, USA

    Ahmed Al-Ostaz

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  1. Farzin Rahmani
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  2. Sasan Nouranian
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  3. Mina Mahdavi
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  4. Ahmed Al-Ostaz
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Correspondence to Sasan Nouranian.

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Rahmani, F., Nouranian, S., Mahdavi, M. et al. Molecular simulation insights on the in vacuo adsorption of amino acids on graphene oxide surfaces with varying surface oxygen densities. J Nanopart Res 18, 320 (2016). https://doi.org/10.1007/s11051-016-3631-7

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