Exploring 2D Graphene-Based Nanomaterials for Biomedical Applications: A Theoretical Modeling Perspective

Abstract

Two-dimensional (2D) graphene-based nanomaterials (GNMs) have shown potential in biomedical applications, including diagnostics, therapeutics, and drug delivery, due to their unique combination of properties such as mechanical strength, excellent electrical and thermal conductivity as well as high adsorption capacity which, combined with the ease of their surface functionalization, enable biocompatibility and bioactivity. Theoretical molecular modeling can advance our understanding of the biomedical potential of 2D graphene-based nanomaterials by providing insights into the structure, dynamics, and interactions of these nanomaterials with biological systems, at the level of detail that experiments alone cannot currently access. This perspective highlights recent computational modeling advances and challenges in examining the interactions of 2D graphene-based nanomaterials with physiologically relevant biomolecular systems, including aqueous solutions, peptides, proteins, nucleic acids, lipid membranes, and pharmaceutical drug molecules. Examples of the theoretical contributions to design of graphene-based biomaterials and devices are also provided.

Keywords: biomedicine; graphene nanomaterials; graphene oxide; molecular simulations; nanotoxicity.

Figure 1

Typical structure of 2D graphene‐based NMs. Graphene‐based nanoflake (NF) models were created using the VMD^{[ 480 ]} software and modeled by explicit solvent molecular dynamics. (MD) simulations.^{[ 218 ]}

Figure 2

Schematic showing relative time and length scales for modeling interactions between 2D graphene‐based NMs and biomedically important molecules using QM, classical MD and hybrid QM/MM methods, illustrated by studies of: a) PG and ions^{[ 252 ]} b,e) PG and apolipoprotein C‐II peptide fragment 60–70,^{[ 68 ]} c) nitrogen‐doped graphene and phenylalanine amino acid (AA),^{[ 481 ]} d) rGO and water,^{[ 218 ]} f) graphene nanopore and double‐stranded DNA,^{[ 112 ]} g) PG and a lipid bilayer,^{[ 69 ]} h) PG and an inverted bilayer.^{[ 167 ]} (a) Adapted with permission.^{[ 252 ]} Copyright 2017, American Chemical Society. (b,e) Adapted under terms of the CC‐BY 3.0 license.^{[ 68 ]} Copyright 2013, The Authors. Published by PLoS. (c) Reproduced with permission.^{[ 481 ]} Copyright 2016, The Royal Society of Chemistry. (d) Adapted with permission,^{[ 218 ]} https://pubs.acs.org/doi/10.1021/acsomega.8b00866. Copyright 2018, American Chemical Society. Any further permissions related to this material should be directed to the American Chemical Society. (f) Adapted with permission.^{[ 112 ]} Copyright 2011, American Chemical Society. (g) Adapted with permission.^{[ 69 ]} Copyright 2015, The Royal Society of Chemistry. (h) Adapted under terms of the CC‐BY 4.0 license.^{[ 167 ]} Copyright 2017, The Authors. Published by American Chemical Society.

Figure 3

All‐atom MD simulations of spreading of a water droplet on graphene surface to determine water contact angle. a) A spherical water droplet was placed on graphene, and simulations were performed until the contact angle of the droplet stabilized. b) Three‐dimensional (3D) maps of the water droplet were constructed to determine nanoscale contact angle. Adapted with permission.^{[ 211 ]} Copyright 2014, American Chemical Society.

Figure 4

Exemplar snapshots from all‐atom MD simulation investigating the influence of graphene‐based NF size and oxidation degree on their structure, dynamics, and interactions in aqueous solution. a) Water coverage fraction (%) of PG, rGO, and GO NFs of different sizes: 3 × 3, 5 × 5, and 7 × 7 nm². Water shown in blue, GNMs in gray color. b) NF–water radial distribution functions identifying hydration shells around the 7 × 7 nm² NFs. c) Quantifying the atomic roughness of graphene‐based NFs with respect to NF size and oxidation. Adapted with permission,^{[ 218 ]} https://pubs.acs.org/doi/10.1021/acsomega.8b00866, Copyright 2018, American Chemical Society. Any further permissions related to this material should be directed to the American Chemical Society.

Figure 5

CG MD simulations investigating the aggregation of 2D GNMs. a) Atomistic reference models for PG and GO (top) and mapping method used to produce the CG representation (bottom). b) Potential of mean force for GO aggregation obtained from US simulations using the atomistic (dashed line) and CG (solid line) FFs. Adapted under terms of the CC‐BY 4.0 license.^{[ 250 ]} Copyright 2020, The Authors. Published by IOP Publishing Ltd.

Figure 6

All‐atom MD simulation examining the interactions between GO, doxorubicin (DOX), and HSA for the design of a drug–GO nanocarrier system. a) Molecular snapshots of initial drug–GO systems containing GO loaded with DOX and HSA (left), and with the addition of PEG (right). b) Molecular snapshot showing the release of DOX from the DOX‐loaded GO system, driven by the DOX–HSA interaction. c) Evolution of contact area between DOX and HSA during the simulations, where a high contact area indicates the release of DOX. Adapted with permission.^{[ 263 ]} Copyright 2020, American Chemical Society.

Figure 7

The influence of AA size on graphene interactions. a) An AA interacting with PG (top) and GO (bottom) in solution. b) Reduced adsorption‐free energies (ΔA ^ads), with ΔA ^ads of Gly set to zero, as a function of reduced solvent‐accessible surface area ΔSASA^ads for all AAs over PG, revealing a linear correlation between the two variables for the neutral AAs. Adapted with permission.^{[ 276 ]} Copyright 2023, American Chemical Society.

Figure 8

All‐atom MD simulation examining the interactions between silk fibroin peptides and graphene. a) Evolution of silk fibroin peptide (P1) secondary structure without (top) and with (bottom) graphene. b) Molecular snapshot showing the interaction between P1 and graphene. AAs are colored based on their names: Ala is blue, Gly is yellow, Thr is red, and Ser is green. c) Results of tensile test showing the pulling force as a function of P1 end‐to‐end distance. d) Results of SMD simulations showing the pull‐out force as a function of peptide displacement. Adapted with permission.^{[ 301 ]} Copyright 2015, American Chemical Society.

Figure 9

Molecular snapshots at different time intervals showing graphene penetrating and cutting a preformed amyloid‐beta (Aβ) fibril composed of twenty‐four Aβ peptide segment 16–21. Adapted with permission.^{[ 83 ]} Copyright 2015, The Royal Society of Chemistry.

Figure 10

All‐atom MD simulation examining the interactions between an amyloid‐beta (Aβ) fibril and GO surfaces. a) Representative simulation models of GO varying in oxygen concentration (10, 20, and 40%). b) Schematic showing the process of Aβ fibril growth. c) Free energy profiles from US simulations showing the separation of peptide from the fibril seed along the filament axis. d) Representative structures from MD simulations of the Aβ fibril binding to GO with 10% oxygen concentration. e) Average number of monomer–seed and monomer–GO hydrogen bonds along the filament axis. Adapted with permission.^{[ 345 ]} Copyright 2021, John Wiley and Sons.

Figure 11

Representative DFT optimized structure of adenine–uracil nucleobase pair on silicon‐doped stone‐Wales defective graphene sheets showing the Si…N interaction. Adapted with permission.^{[ 366 ]} Copyright 2020, Elsevier.

Figure 12

Spontaneous transport of DNA through a water droplet over a patterned 2D graphene–hBN heterostructure. a) Center of mass (COM) distance of the droplet (black line) and DNA (yellow) with respect to time. b) Adsorbed conformation of double‐stranded DNA (dsDNA) in the droplet over the graphene–hBN surface, highlighting the interaction between the two DNA bases and hBN. c) Graphene–hBN heterostructure schematic illustrating the definition of the apex angle of the hBN isosceles triangle. Various heterostructures were created with varied apex angle (27.8, 17.9, 9.4, 4.8, and 2.5°) to investigate the impact of pattern geometry on nanodroplet transport. d) Average velocity of the droplets on the graphene–hBN surfaces varying in apex angle. e) Maximum travel distance of the droplets on the graphene–hBN surfaces varying in apex angle. Adapted with permission.^{[ 380 ]} Copyright 2024, American Chemical Society.

Figure 13

DNA transport through a charged double graphene nanopore system. a) Side view schematic of the system containing ssDNA (purple), a graphene nanopore (gray), potassium ions (blue), chloride ions (red), and the ionic solution (blue). b) Top view schematic of the system illustrating details of the graphene nanopore, including two pores of the same diameter and different charge. The ssDNA molecules are placed between the two nanopores. c) 2D potential distribution of nanopore on the X–Y plane under an electric field. d) Simulation snapshots showing the time evolution of ssDNA through the nanopore. Adapted with permission.^{[ 384 ]} Copyright 2024, American Chemical Society.

Figure 14

Graphene penetrating through a phospholipid bilayer. a) Simulation snapshots showing the membrane penetration pathway of graphene beginning at graphene's edges. b) Relationship between nanosheet orientation and position inside the membrane, shown in (a), demonstrating the three stages of the membrane insertion process. Adapted with permission.^{[ 179 ]} Copyright 2022, The Royal Society of Chemistry.

Figure 15

Molecular insights into the effects of graphene nanosheet (GN) insertion on the nanoscale ordering of lipids. a) 2D density maps showing the density of lipids when graphene is absent (left), adhered to the membrane (middle), or inserted into the membrane (right). b) Mass density profiles of lipids along the x‐, y‐ and z‐axis. Reproduced with permission.^{[ 396 ]} Copyright 2020, American Chemical Society.

Figure 16

SMD simulation snapshots at different time intervals showing the membrane indentation, withdrawal, and self‐healing process during interaction with graphene. Reproduced under terms of the CC‐BY 4.0 license.^{[ 398 ]} Copyright 2020, The Authors. Published by American Chemical Society.