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Biophysical Chemistry, Biomolecules, and Biomaterials; Surfactants and Membranes

Chemical-Potential-Gradient-Driven Transport of Unfolded Proteins through Graphene-MoS$_2$ Heterostructure Nanopores Binquan Luan, and Ruhong Zhou J. Phys. Chem. Lett., Just Accepted Manuscript • DOI: 10.1021/acs.jpclett.8b01340 • Publication Date (Web): 05 Jun 2018 Downloaded from http://pubs.acs.org on June 5, 2018

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The Journal of Physical Chemistry Letters

Mo S2 Gra phe ne

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Highlights: Driven by the chemical potential difference, an Aβ42 protein transits the graphene-MoS2 heterostructure nanopore. After about two decades of research and development, the nanopore-based DNA sequencing method 1–3 has been significantly improved and is generally accepted as the next-generation sequencing method. Recently, benefited from its accurate and ultra-long read of single stranded DNA (ssDNA), the MinION nanopore was successfully applied to sequence and assemble a human genome. 4 Driven by the triumph of DNA sequencing, nanopore platforms have been proposed 5 to sequence proteins that can be viewed as “nanomachines” working concertedly together to maintain the viability of biological cells. Mutations or modifications (such as insertions or deletions) of amino acids in a protein can seriously affect its biological functions and often lead to diseases, such as breast cancer, Huntington’s and Alzheimer’s diseases. Therefore, promising to be low-cost and high-throughput, nanopore technologies might dramatically change the landscape of protein analysis in the healthcare and life science. Nanopore sensors generally allow to detect of a single biological molecule and characterize its physical properties (such as the size, shape and charge) by electric signals of ionic current blockages caused by molecule’s transport. Typically, when nanopores (such as solid-state nanopores 2

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with diameters ∼5-10 nm) are larger than target proteins, folded or partially folded proteins can transit the pore in a bias electric field. According to protein-translocation induced current blockages and/or blockage durations (i.e. translocation velocities), nanopores have been proven to be sensitive for detecting various proteins. 6–11 With a bilayer-coating on solid-state nanopore surface, 12 even the rotational diffusion coefficient and dipole momentum of a protein can be determined. 13 By covalently tethering phenylalanine-glycine nucleoporins to a solid-state nanopore surface, the selectivity of protein transport through nuclear pore complexes in eukaryotic cells can be studied in a biomimetic nanopore platform. 14 Other chemical modifications of nanopore surfaces have enabled studies of binding between a protein and a molecular receptor 15 /recognition-agent. 16 Benefited from enhanced high-bandwidth ion current measurements, even conformational changes of a protein inside nanopores can be characterized. 10,17,18 Similar to the degradation process in a cell where a target (or damaged) protein is driven through a protease’s central nanochannel for recycling, 19 sequencing proteins requires the transport of an unfolded protein in a single file manner through nanopores. This was realized previously by driving an unfolded target protein through the α-haemolysin nanopore (smaller than the target protein), where the driving force can be either electric due to a linked oligonucleotide chain in a bias electric field 20 or mechanic due to ATP-powered pulling by the AAA+ unfoldase ClpX. 21 Additionally, the dynamics of protein unfolding and transport through an aerolysin nanopore has also been demonstrated. 22,23 Similarly, the electric transport of unfolded proteins through solid state nanopores has been studied in experiment recently. 24–26 However, regular solid-state nanopores (e.g. those made of Si3 N4 ) are normally much larger than protein nanopores, preventing the transport of unfolded proteins in a single file format (required for protein sequencing). In addition, lengths of regular solid-state nanopores range from 5 to 30 nm (determined by the host-membrane thickness), which forbids the sensing of just one or a few amino acids. To implement potential protein sequencing, nanopores on two-dimensional (2D) nanosheets are promising candidates given that each pore is only atomically-long and 1 to 2 nm in diameter. To date, 2D nanopores can be drilled on graphene, 27–29 MoS2 , 30–32 hexagonal boron nitride 33,34

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and tungsten disulfide (WS2 ) 35 nanosheets. A few theoretical studies have already demonstrated the feasibility of transporting uniformly/highly charged protein through a reduced graphene-oxide nanopore 36 or a MoS2 nanopore 37 in a bias electric field. However, when applying a bias electric field across a nanopore, the electric field is highly localized inside and near the pore, which imposes difficulties for driving any unfolded protein chain. Namely, in a fixed bias electric field a protein segment inside/near a 2D nanopore can be neutral, positively charged or negatively charged, corresponding to a trapped, facilitated or hindered transport respectively. Thus, the electrophoretic transport cannot be effective. When a pore surface is charged, proteins might be captured and/or driven through the pore via an electroosmotic flow as shown for large nanopores. 10,38,39 However, an electroosmotic water flow in a 1-2 nm nanopore, without additional treatments such as the pH gradent, 40 may suffer from the increased water viscosity (resulted from the enhanced hydrogenbond network in a small and charged nanopore) and from the boundary friction from a pore surface. Alternatively, a water flow might be driven by a pressure difference across a nanopore, but a single graphene nanosheet might be fragile and the previous experiment showed that a 5-nm-thick graphene layer is required to allow the pressure-driven transport of proteins through a 15-nm-indiameter graphene nanopore. 41 Thus, in order to sequence proteins in a narrow 2D nanopore, a non-conventional method allowing to drive any protein chain through the nanopore in a single file manner is therefore highly sought after. Recent experiments have shown the feasibility to incorporate two distinct 2D materials into an integral van der Waals (vdW) heterostructure. 42 Remarkably, a plethora of 2D materials can be vertically stacked together via the vdW attraction. 42–45 Due to the strong vdW interaction, proteins can unfold and lie intimately on a 2D nanosheet (e.g. graphene 46 or MoS2 47 ). Given the fact that a protein typically interacts more weakly with the MoS2 surface than with the graphene surface, 48 we conjectured that those differential vdW interactions might be harnessed to drive any protein molecule through a tiny (quasi-2D) nanopore drilled on a heterostructure (e.g. stacked together by a graphene and a MoS2 nanosheets). To prove the principle, we carried out molecular dynamics simulations to demonstrate that it is feasible to transport an unfolded protein chain through a

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graphene-MoS2 -heterostructure nanopore, which might be combined with other amino-acide sensing techniques 49,50 to enable protein sequencing.

a

b

c

Figure 1: MD simulation of the Aβ 42 protein’s transport through a graphene-MoS2 -heterostructure nanopore. a) The perspective top view of the simulation system. Atoms in the MoS2 sheet are shown as vdW spheres (Mo: pink; S: yellow); the graphene sheet (cyan) is in the bond representation; the protein is in the vdW representation with each element colored differently (C:cyan, O:red, H:white, N:blue, and S:yellow); water and ions are not shown for clarity. b,c) The top and side views of the simulation system. The protein is in the cartoon representation; water (gray) is shown transparently; K+ and Cl− ions are shown as tan and cyan dots in (c) only.

To model the transport process of a protein molecule through the heterostructure pore, we performed all-atom molecular dynamics (MD) simulations using the program NAMD. 51 following our previous protocols. 52,53 Detailed simulation methods are described in the Supporting Information. Figure 1a illustrates the simulation system. Stacked together on top of each other with a 5


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separation distance of 3.4 Å, 54 the graphene sheet and the monolayer MoS2 sheet measured about 9.88×9.22 nm2 . A 2-nm-in-diameter nanopore was “drilled” through the heterostructure by removing any atoms within 1 nm from the z axis (perpendicular to 2D surfaces). The heterostructure nanopore was further solvated in a water box containing 26,900 water molecules. K+ and Cl− ions were added to neutralize the entire system and yield a 1 M KCl electrolyte. Two intrinsically disordered proteins (IDPs) were selected for transport studies: (1) the amyloid β peptide 1-42 (Aβ42 ) that is the pathological hallmark of Alzheimer’s disease containing representative charged, polor and hydrophobic segments; (2) the polyglutamine (polyQ) Q42 peptide , an elongated polyQ protein associated with another neuron degenerative Huntington’s disease. Each IDPs was initially placed near the MoS2 surface with its C-terminal threaded through the pore, so that two amino acids were above the graphene surface (Figure 1b). During the equilibration, the protein segment on the MoS2 side was adsorbed onto the MoS2 surface with about four extra amino acids moved above the graphene surface (Figure 1c). Experimentally, how to initiate the entry of one protein end into the pore is discussed in the Supporting Information. We carried out simulations at various temperatures T =300, 350 and 400 K. At an elevated temperature of 400 K, it was observed in four independent MD simulations that within hundreds of nano-seconds (ns) amino acids in the protein strand moved consecutively through the heterostructure nanopore (Figure 2). Typically, as shown in Figure 2a, both the transported segment and the remaining one were adsorbed on the graphene and on the MoS2 , respectively. However, the transported segment was observed to have more intimate (or flatter) contacts with the graphene surface. Occasionally, a helix could be formed on the MoS2 surface (Figure 1c) but was never found on the graphene surface, which suggests that the protein interacted more strongly with graphene than with MoS2 . Figure 2b shows the time-dependent centers of mass (COM) of the entire protein molecule, ZCOM , projected on the z-axis (perpendicular to the heterostructure surfaces). For the Langevin thermostat (see method for details) used in four independent simulations, the damping rate of 0.5 ps−1 was applied to two of them (labeled by Sim-1 and Sim-2); the damping rates of 1.0 and 2.0

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a

b -5

Z (Å)

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-10

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Figure 2: Spontaneous transport of the Aβ 42 protein through the heterostructure nanopore (T =400 K). a) A snapshot of the system when the protein transited about halfway through the nanopore. The protein is in the stick representation with its backbone (cartoon representation) colored in red. Atoms in the heterostructure are shown as vdW spheres (C:cyan, S:yellow and Mo:yellow). b) Time-dependent centers of mass (ZCOM , projected on the z axis) of the entire protein, during the transport.

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ps−1 were applied to the rest two (labeled by Sim-3 and Sim-4 respectively). Starting from mainly being adsorbed on the MoS2 surface (ZCOM ∼ −18.5 Å), the protein chain underwent stick-slip motions through the pore and toward the graphene surface as indicated by the step-wise increase in ZCOM . Each increase in ZCOM signifies that an amino acid moved from the MoS2 surface to the graphene surface through the nanopore. At the end of each simulation, all amino acids in the protein chain were present on the graphene surface (ZCOM = −5 Å). By varying the damping rate of the Langevin thermostat, we effectively changed the viscosity of the electrolyte to alter the overall transport speed. As expected, the transport process is slower in the more viscous solution (with a larger damping rate γ in the thermostat). Additionally, the stickslip nature of protein transport through the pore indicates that there might exist sequence-dependent trapping (e.g. due to the interaction between amino acids and the pore surface). From the trajectory analysis, we found that a hydrophobic patch containing Ala21, Phe20, Phe19, Val18 and Leu17 can interact strongly with the pore surface and consequently the transport stalled temporarily ( see the “stick” state when Zcom ∼ -13.5 Å in Figure 2b). Later, the protein molecule moved toward more hydrophobic graphene surface after the thermal activation of the hydrophobic patch from a trapped state, i.e. the transport process resumed. Note that such neutral segment cannot be driven by an electric field through a nanopore. Due to the stochastic process of thermal activation, the protein might be trapped in the same “stick” state for different amounts of time in different MD simulations. Thus, entire transport times for Sim-1 and Sim-2 differ by a factor of ∼2 (even with the same γ); on the other hand, the transport times for Sim-3 and Sim-4 are close even though values of γ differ by two times. It is worth noting that the success rate of the transpport is 100% (i.e. four out of four), suggesting that the transport is deterministic. To qualitatively understand the driving force for protein transport from the MoS2 surface to the graphene surface, we calculated time-dependent potential energies for the protein molecule (when transiting the nanopore) from the simulation trajectories. Because of charge neutrality of each nanosheet in the heterostructure, the vdW potential energy dominates the electrostatic one. Figure 3a shows the pair-wise vdW energies (between the protein molecule and the heterostructure)

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normalized by the number of entire amino acids inside the protein molecule. During the protein transport through the heterostructure nanopore, the vdW energy was gradually reduced when more amino acids in the protein molecule moved from the MoS2 surface to the graphene surface. Unanimously from all four simulations, the net change of vdW potential energies per amino acid is about -7.6 kB T. Therefore, the transport was mainly driven by the difference of adsorption energies (or chemical potentials) for the protein molecule on two different types of 2D surfaces. The weaker interaction between a protein molecule and the MoS2 nanosheet was manifested in a previous study, 48 showing that the helix structure of the first 17 residues in the exon-1 of the Huntingtin protein was preserved on the MoS2 surface but was destroyed on the graphene surface. Consistently, because of the strong vdW interaction, the folded structure of a villin headpiece cannot be maintained after being adsorbed onto the graphene surface. 46 Here, from the simulation trajectory, we found that on the MoS2 surface a local helical structure can be formed (see Figure 3b). However, on the graphene surface, side chains of most amino acids lay down and form intimate contacts (Figure 3c and Figure S1 in Supporting Information), indicating an stronger vdW interaction with the graphene. After all amino acids in the protein molecule were transported through the pore, the entire protein meandered and diffused freely on the graphene surface (Figure 3d and Movie S1 in Supporting Information). We emphasize that, in practice, this spontaneous process will stop once the graphene surface is covered completely by the transported proteins, and it requires removal of these proteins in order to have this transportation process to continue again. To highlight the dynamics of protein transport, in Figure 4 we show at various temperatures the time-dependent number m of amino acids being transported through the pore (i.e. residing on the graphene surface). When T =400 K, the protein molecule can be thermally activated from a “stick” state and move forward by several to ten amino acids. When the temperature was reduced to 350 K and 300 K, the overall transport process slowed down accordingly (Figure 4), assuring that the step-wise transport was thermally activated from time to time. At lower temperatures, notably, m increased in a more step-wise fashion. In each “stick” state, m remained constant and the duration become longer, suggesting that the thermal activation from a “stick” state become more difficult at

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E (kcal/mol)

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Figure 3: Energetics of the Aβ 42 protein transport through the heterostructure nanopore. a) Timedependent interaction energies (normalized by the total number of amino acids) between the protein and the heterostructure. b) A snapshot of the protein segment remained on the MoS2 surface. c) A snapshot of the protein segment transported to the graphene surface. d) A snapshot of the protein on the graphene surface after the transport completed.

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lower temperatures. It took more than 1 µs for the protein molecule to completely transit the pore at 350 K. The process was even slower at 300 K and we observed a partial (∼50%) transport of the entire protein molecule after about 2 µs. Thus, we expect that the entire transport at the room temperature could be observed at a larger (e.g. milli-seconds) timescale in experiment.

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20 400 K Sim-1 Sim-2 Sim-3 Sim-4

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Figure 4: Transport of the Aβ 42 protein at various temperatures, 300 K (cyan), 350 K (magenta) and 400 K (blue, orange, green and black).

To further demonstrate this non-electrically driven transport, we studied the transport dynamics of another IDP Q42 that contains 42 repeats of the polar glutamine (Gln) amino acid. It is worth noting that Q42 cannot be electrically driven through a nanopore due to Gln’s charge neutrality. Starting from a conformation similar to the initial one of Aβ42 on the heterostructure (Figure 1), Q42 was also observed to transit the heterostructure pore in two independent simulations at 400 K and another two independent simulations at 350 K (γ=0.5 ps−1 , Figure 5). Overall, the transport dynamics of Q42 is very similar to that of Aβ42 showing the stick-slip process. Averagely, the vdW potential per amino acid for Q42 decreased by about 6.8 kB T after the transport, less than 7.6 kB T 11


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for the Aβ42 case. However, the transport speed (e.g. at 350 K) for Q42 is about two times faster than that for Aβ42 , likely due to its sequence homogeneity and relatively weak interaction with the nanopore (see trapping energy below). The inset of Figure 5 shows a snapshot of the simulation system when Q42 moved about half-way through the nanopore. The adsorbed conformation of Q42 on the graphene surface after its transport is illustrated in Figure S2 in the Supporting Information.

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Figure 5: Transport of the Q42 protein through the heterostructure pore, when T =350 K (brown and red) and T =400 K (blue and orange). Inset: A snapshot of the simulation system during the transport of Q42 .

During the protein transport through a heterostructure pore, there are three factors that can affect the free energy landscape. The first one is the entropy of a protein molecule; the second one is the chemical potential difference of the protein on different 2D surfaces and the third one is the attraction between amino acids and the pore surface (resulting in a “stick” state). With the entropy contribution derived for a polymer chain 55,56 (containing N monomers with m of them being transported to the other side of nanopore), the free energy F for an IDP transiting the heterostructure

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nanopore can be written as, j

F(m) = (1 − γ)kB T ln[m(N − m)] + m∆U + ∑ U0 (m + i)

(1)

i=1

where the surface entropic exponent γ= 0.92 for a self-avoiding 2D polymer-chain near a wall; 57 ∆U is the mean chemical potential difference per amino acid and is negative if the protein molecule transits the pore from the MoS2 surface to the graphene surface; U0 (m + i) is the interaction energy between the pore surface and the (m + i)th, or the instant trapping energy for the entire protein molecule. 37 j is the number of amino acids inside the pore and is typically 2 or 3 in our simulations. Note that the value of j can be smaller if the pore size is reduced and/or the heterostructure is thinner, such as the stacking of a graphene and a hexagonal boron nitride (hBN) nanosheets. The entropy term suggests that the free energy is maximal when m=N/2, i.e. when the protein molecule moved halfway through the pore. Analytically, the corresponding barrier height is (1γ)kB Tln(N/4). For N=42, the predicted barrier height is only 0.19 kB T; even for N=4200 (an enormously large protein), the barrier height is only 0.56 kB T. As shown in Figure 3, the mean value of ∆U is about 7kB T , and the estimated trapping energy is about 5-10 kB T . Therefore, the entropy term is negligible when compared with the other two terms in Eq. 1. The trapping energy U0 (m) is sequence-dependent and can vary significantly for all twenty types of amino acids. For example, for the Aβ 42 protein, Phe19 and Phe20 can interact with the pore surface strongly via the vdW interaction, while charged amino acids such as Asp23 and Lys28 typically orient their side chains toward water (inside the pore) and thus only interact with the pore surface weakly. Because of varying trapping energy, residence times for various amino acids inside the pore can differ. As shown in Figure 4, some amino acids were trapped inside the pore for about tens of ns at 400 K and even hundreds of ns at 300 K before they can be thermally activated and transported to the graphene surface, while other amino acids with weak interactions with the pore surface can move through the pore quickly (i.e. “slip” states). On the free energy landscape, the contribution of the chemical potential difference m∆U is

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j

to tilt (and thus reduce) the trapping potential barrier imposed by ∑i=1 U0 (m + i), allowing the continuous transport of the protein molecule. If −∆U > U0 (m + 1) +U0 (m + 2) when j=2, driven by the chemical potential difference, the protein molecule can move through the pore without a “stick” state. On the other hand, when −∆U is smaller, the transport requires the thermal activation and the protein molecule can be trapped in many “stick” states. It can be expected that if −∆U is too small the protein molecule might be permanently arrested (e.g. −∆U=0 for an extreme grapheneon-graphene case and thus no protein transport is allowed). With many newly discovered 2D vdW materials, 42 the value of −∆U could be adjusted/optimized via the combination of any two of them (and/or further functionalizations), so that the ideal protein transport is stick-slip-like and during each “stick” state the sensing of a trapped amino acid inside the nanopore can be performed. Several protein sequencing methods have been developed that might work readily with the our method for protein’s translocation through narrow nanopores. For example, the ionic current blockade signals might be sensitive to specific moieties in proteins during its transport through nanopores. 58 Theoretically, the distributions of ionic blockade-currents (through an intersecting perpendicular nanochannels, similar to the nanopore confinement) of each amino acid can be statistically different. 50 Remarkably, measuring electron tunnel currents can distinguish many amino acids trapped between two molecule-coated electrodes that can be integrated into the nanopore platform. 49 It was also shown that the nanopore mass spectrometer is capable of analyzing DNA bases as well as protein amino acids. 59 Note that our suggested protein transport through a heterostructure nanopore can sequentially bring amino acids to a sensor, mimicking a biological process where an enzyme (e.g. RNA polymerases) can sequentially feed amino acids (or generally monomers in a polymer chain) to the reaction site. In summary, we proposed a heterostructure nanopore platform that is composed of two distinct 2D materials stacked together vertically. Currently, the most widely used method for transporting protein molecules through nanopores is to apply a bias electric field. When the pore is larger than a folded protein, charged or neutral proteins can respectively transit nanopores electrophoretically or electroosmotically (or both). While large nanopores are useful to analyze physical properties of

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a folded protein, narrow nanopores are required to analyze the sequence of a protein that should assume an unfolded and single-file conformation inside nanopores. For this purpose, the bias electric field (that is highly focused inside/near a nanopore) may stall, facilitate and retard the transport depending on the net charge of a protein fragment inside the pore. This difficulty can be circumvented by using the heterostructure nanopore where the drive force comes from different chemical potentials ∆U of a protein molecule on two different 2D surfaces. By adjusting the value of ∆U relative to the trapping energy due to the interaction between amino acids and the pore surface, the transport of a protein molecule can be step-wise or in a stickslip manner. When the step size is reduced, ideally, the transport could be residue-by-residue, allowing analysis of each amino acid (or protein sequencing). By optimizing the thickness, shape and size of a heterostructure nanopore, we hope that this new platform when combined with electric sensing methods can facilitate the protein sequencing applications in future.

Acknowledgement The authors gratefully acknowledge the financial support from the IBM Bluegene Science Program (Grant number: W1258591, W1464125, W1464164).

Supporting Information Available MD simulation methods; discussion of methods for the initial entry of one protein end into a nanopore; illustration of adsorbed amino acids in Aβ42 and Q42 on the graphene surface; the movie (MoS2GPH-AB42.mpg) illustrating the transport dynamics of Aβ42 through the heterostructure pore. This material is available free of charge via the Internet at http://pubs.acs.org/.

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