Protein Translocation through a MoS2 Nanopore:A ... - ACS Publications

Subscriber access provided by READING UNIV

Article 2

Protein translocation through a MoS Nanopore: A Molecular Dynamics Study Huang Chen, Libo Li, Tao Zhang, Zhiwei Qiao, Jinhui Tang, and Jian Zhou J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b07842 • Publication Date (Web): 03 Jan 2018 Downloaded from http://pubs.acs.org on January 3, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

The Journal of Physical Chemistry C is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The Journal of Physical Chemistry

Protein translocation through a MoS2 Nanopore: A Molecular Dynamics Study

Huang Chena, Libo Li*, a, Tao Zhanga, Zhiwei Qiaoa,b, Jinhui Tanga, and Jian Zhou*, a

a

School of Chemistry and Chemical Engineering, Guangdong Provincial Key Lab for Green Chemical Product Technology, South China University of Technology, Guangzhou 510640, P. R. China b School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, P. R. China

* Corresponding author.

Tel./fax: +8613902325164. E-mail address: [email protected], [email protected]. 1

ACS Paragon Plus Environment

The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT. Single molecule protein sequencing is essential for a wide range of research and application fields, where the recently emerging 2D (two-dimensional) nanopores have open unprecedented possibilities. The protein translocating through a 2D nanopore plays vital roles in the nanopore-based analysis, where various detection or sequencing method could be employed. It is critically important to study the protein translocating through various 2D nanopores, which may help design efficient nanopore devices. However, few 2D materials other than graphene has been studied in this context yet. In this work, molecular dynamics (MD) simulations were employed to investigate the feasibility of single-molecule protein sequencing with a MoS2 nanopore. Both phenylalanine-glycine repeat peptides and a peptide with the sequence taken from the thioredoxin protein were studied in their extended unfolded state, which adsorbed onto the MoS2 membrane spontaneously. These peptides kept adsorbing onto MoS2 and permeated unidirectionally through the MoS2 nanopore, driven by either an electric field or hydrostatic pressure gradient. Their translocation process was stepwise, and the speed sensitively depended on the electric field, hydrostatic pressure, the charge density or hydrophobicity of the peptides. The stepwise peptide translocation yielded ionic current blockades correlating with the sequence of peptide fragment in the nanopore. This work provides with insights for designing a protein sequencing device with a MoS2 nanopore.

2


Page 2 of 38

Page 3 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1. INTRODUCTION Protein sequencing is of prominent significance, since the amino acid sequence determines how a protein folds and functions. Recently, single molecule protein sequencing has become even more critical for identifying protein biomarkers and diagnosing various human diseases.1-3 Common protein sequencing methods, however, are subject to limitations:4-5 mass spectrometry does not provide the complete sequence information for a protein and will become computationally demanding to reassemble the sequence when the protein size increases; Edman degradation can only handle peptides of 30-50 residues long without modified or buried N-terminal amino acid; etc. Particularly, the sensitivity of these sequencing methods is usually insufficient for single molecule analysis.5 Nanopore analysis has recently emerged as a promising single-molecule analysis method for a wide range of analytes, e.g., ions, amino acids, DNA and proteins. These analytes, including protein, are forced to translocate through a nanopore by some external field (e.g., electric field, fluid flow, atomic force microscope (AFM), molecular motor, etc.),6-9 so that various signals could be detected to analyze them: electrical signals (e.g., the blockage of the ionic current through the nanopore, the change of the transverse current), force or optical signals.6,8,10 Nanopore DNA sequencing technology is approaching commercialization,11 and recent studies suggested single-molecule protein sequencing could be possible by measuring the ionic current and ionic current state dwell times when pulling a protein through a nanopore with a molecular motor (AAA+ unfoldase CIpX).9 In comparison with

3



Page 4 of 38

conventional protein sequencing methods, nanopores show a range of advantages: single-molecule resolution,12 simple and miniature instruments, can analyze unfragmented protein strands and detect protein phosphorylation in a single-molecular and site-specific manner.13 There are mainly two categories of nanopores: bio-nanopores and solid-state nanopores. Solid-state nanopores are quite appealing, because they show high mechanical or chemical robustness, are easy to tune the physical and chemical properties (e.g., size, surface, etc.),14 and are capable of mass production and integration.15-16 In very recent works, a single unfolded protein molecule was pulled through a 10 nm-thick silicon nitride nanopore by an electric field4

(the protein was

coupled to negatively charged SDS molecules) or AFM,8 and the residue substitutions are readily detected by measuring the residue volume to a precision of 0.1 nm 3. However, most solid-state membranes are much thicker than the size of amino acids, which considerably limits the analysis sensitivity or resolution.17 The recently emerging nanopores based on 2D materials such as graphene,18 h-BN19-20 and MoS2,21-22 open unprecedented possibilities to sequencing biopolymers. These nanopores share similar merits like traditional solid state nanopores, yet are as thin as a single nucleobase or amino acid to yield high spatial resolution. Current studies mainly focus on sequencing DNA with graphene nanopores. Experimentally, the transmembrane voltage driven translocation of DNA through a graphene nanopore has been reported, and the associating ionic current was measured to characterize the DNA translocations.23-24 MD simulations were also performed to study the

4


Page 5 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


translocation mechanism,25 the ionic current blockade mechanism,26 and how to improve the device performance by adjusting the analysis parameters: the voltage, salt concentration, membrane thickness, nanopore size and shape, etc.27-30 The possibility to detect31 or sequence32 peptides with graphene nanopore was also studied very recently. These studies indicated that the structure of 2D materials could affect the bio-polymers translocating through the nanopore, and the sequencing performance considerably. For instance, the graphene nanopore could be engineered to slow the translocation rate to accommodate currently available detection methods. 33 Also, the surface could be modified to tune the translocation rate or the surface adsorption of biopolymers, which would consequently improve the analysis performance.34 Although most current 2D nanopore studies are carried out with graphene membranes, the interactions between graphene and proteins are quite strong and complex,34 posing considerable difficulties in sequencing proteins. Thus, to study various 2D materials thoroughly could yield insights for tuning the biopolymer translocation and designing efficient nanopore-based analysis devices. However, very few 2D nanopores have been studied for biopolymer, especially proteins translocation or sequencing, at present. Molybdenum disulfide (MoS2) is a new 2D material showing various desirable properties.35-38 Its thickness (~ 1nm) and mechanical stability are moderate, helping reduce the signal noise.22,37 In comparison with graphene and h-BN, the non-specific adhesion of biopolymers to MoS2 is considerably weaker due to the hydrophilic Mo sites,21 which may lead to feasible performance improvement via controlling the

5



biopolymer motion on the MoS2 surface.39 In addition, MoS2 has a band gap of 1.8 eV, a significant advantage for sensing applications.37 There have been many simulation studies on MoS2 nanosheets.40-44 And MoS2 nanopore has recently been studied to analyze DNA via both experiments21,45 and simulations22,46, but has not been studied to sequence or detect protein yet. In this paper, all-atom molecular dynamics (MD) simulations were employed to study protein translocating through a MoS2 nanopore in KCl solution. The MoS2 nanopore was characterized by ionic current, ionic conductance, electrostatic potential map, and the average electrostatic potential across the pore, respectively. Unfolded peptides were driven by transmembrane bias or hydrostatic pressure to translocate through the MoS2 nanopore. Their stepwise motion character and the influencing factors were studied. Furthermore, the ionic current through the MoS2 nanopore during the peptides translocation process was investigated. 2. METHODS 2.1. System set up A circular nanopore with a diameter of 2.20 nm was drilled in the center of a 6.01 nm×6.02 nm monolayer MoS2 membrane by removing all atoms satisfying the condition x2 + y2 < R2，where x and y were the coordinates of the atoms and R was the pore radius, 1.10 nm in this work. The radius of 1.10 nm was chosen in this work because it was neither too small (the ionic current would be too low, see Figure S2, Supporting Information) nor too large (the amino acid in the pore would affect the ionic current insignificantly because it could only occupy a small fraction of the pore

6


Page 6 of 38

Page 7 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


area28). A typical simulation system consisted of a 48-residue unfolded peptide, a MoS2 membrane with a 2.20 nm diameter nanopore, and 1 M KCl aqueous solution. Most peptides consisted of FG-nucleoporin (FG-Nup) repeating units, such as (FKFG)12 (+12e), (FGFG)12 (0e), and (FDFG)12 (-12e), etc. The amino acid sequences of these peptides were denoted with the one letter code, and the charge was denoted by a number in the following parenthesis where 'e' referred to the charge of a proton. These phenylalanine-glycine repeat peptides (FG-Nups) are abundant in the nuclear pore complexes of eukaryotic cells with significant biological functions.47-48 A peptide with the sequence (N'-SDKIIHLTDDSFDTDVLKADGAILVDFWAEWCGPCKMIA PILDEIADE-C') taken from the thioredoxin (Trx) protein (PDB file: 2TRX49) was also studied, which was denoted as Trx1-48. These peptides were initially threaded through the nanopore with an extended unfolded conformation, so that their secondary or tertiary structures would not confound the protein sequencing (see Figure 2a). In protein sequencing experiments, proteins are usually denatured to unfolded conformations by heating or denaturants. The model protein chains, such as (FKFG)12, (FGFG)12 and (FKFG)12 peptides, were constructed by using the Avogadro software (Version 1.2.0).50 The protein-MoS2 system was solvated in a 60.05×60.21×120.00 Å3 water box with TIP3P51 water molecules, and then ionized and neutralized to 1 M K Cl, which is usually employed in nanopore sensing experiments.3 The numbers of K+ and Cl- ions were different to neutralize the system containing ~ 45 K atoms when the net charge of the peptide was non-zero. The periodic boundary conditions (PBC) were applied in all three dimensions.

7



2.2. MD Simulations. All MD simulations were carried out using the GROMACS 4.6.7 package.52 The visualization and analysis were performed with the VMD software53 and the GROMACS utilities. The parameters for proteins and ions were taken from the CHARMM27 force filed.54 LINCS algorithm55 was used to constraint the bonds involving hydrogen atoms, and SETTLE algorithm56 was employed to constraint water geometry. The parameters of MoS2 were taken from the literature,35,57 which yielded water contact angle (70.4°±0.4°) in close agreement with the experimental result (69.0°±3.8°),58 (see the Supporting Information for details of water contact angle calculation59-60). Taking into account the rigidity of MoS2, the atoms were frozen in the simulation as other simulation works do.22,61 For the nonbonded interactions, the Lorentz-Berthelot mixing rule was used to obtain the LJ parameters. A switching function starting at 1.1 nm and reaching zero at 1.2 nm was used to truncate the LJ interactions, and a long-range analytical dispersion correction was applied to the energy and pressure to account for the truncation.62 The electrostatic interactions were calculated by the particle-mesh Ewald (PME) method with a cut-off distance of 1.2 nm.63 For a typical simulation, a 5000-step steep descent energy minimization was performed in the beginning, and a harmonic potential with a force constant of 1000 kJ/mol/nm2 was applied to the backbone atoms of the protein. The system was then equilibrated in the NPT ensemble for 10 ns to obtain proper water density. The temperature was kept at 300 K by the V-rescale thermostat64 and the pressure was kept

8


Page 8 of 38

Page 9 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


at 1.0 bar by applying the semi-isotropic Berendsen barostat65 to the z direction. The final length of the system along this dimension was taken as the average value over the last 8 ns of the equilibration. Upon NPT equilibration, the system was further equilibrated in NVT ensemble for 120 ns, with the temperature maintained at 300 K by the V-rescale algorithm. During the above NPT and NVT equilibrium process, one backbone atom of the protein in the nanopore was harmonically restrained with a force constant of 1000 kJ/mol/nm2. The production simulation was carried out in the NVT ensemble by applying an external electric field along the z direction, and all restraints were removed from the protein. The integration time step was 2 fs and the data were stored every 2 ps for analysis. The external electric fields could also be reported in terms of a transmembrane voltage difference V   ELz , where E is the electric filed strength and Lz is the length of the simulation system along the z direction.26 Other simulation details could be found in our previous publications.66-67 2.3. Analysis The number of amino acids adhered to the MoS2 membrane was calculated by counting the number of amino acid residues whose center of mass (COM) was located within 7 Å of the nearest S atom of the MoS2 membrane. The minimum distance was calculated as the minimum distance between any pair of atoms from the MoS2 membrane and the peptide. The number of contacts was calculated as the number of atom pairs from the MoS2 membrane and the peptide with distance below 6 Å. The number of translocated amino acids Np was calculated by counting the number of amino acid residues beneath the MoS2 membrane during the MD trajectory. In a

9



Page 10 of 38

few simulations where the peptide moved upward, Np was also calculated as the number of amino acid residues beneath the MoS2 membrane for the sake of consistency. The permeation rate was calculated as the slope of Np over the simulation time. The diffusion coefficient of K+ or Cl- ions was calculated with the Einstein relation:

| r(t  t ' )  r(t ) |2  D  lim t ' 6t '

(1)

where | r(t  t ' )  r(t ) |2  is the mean square displacement (MSD) for a given relative simulation time t’. The last 15 ns of a 20 ns simulation was taken as the 'production' period to calculate the diffusion coefficient The time-dependent ionic current I (t ) through the MoS2 nanopore was calculated as

I (t ) 

1 t LZ

N

 q Z t  t   Z t  i 1

i

i

i

(2)

where the sum was over all ions, (t ) was 2 ps, Z i and qi are the z coordinate, the charge of ion i , and N is the total number of ions. The time series of current was block-averaged over 0.4 ns to decrease the noise, as other similar works did.26 The ionic conductance was defined as the reciprocal of the ionic resistance:27

S

I av UZ

(3)

where I av is the average of ionic current ( I (t ) ). 3. RESULTS AND DISCUSSION 3.1. I-V Characteristic and Electrostatic Potential Map of Open MoS2 Nanopore The ionic conductance of a MoS2 nanopore describes the ions (e.g., K+ or Cl-) 10


Page 11 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


permeating through the nanopore under an applied voltage, and directly affects the magnitude of the ionic current signal. To characterize the ionic conductance of a 2.20-nm diameter open MoS2 nanopore (the analyte was absent from the system), the nanopore with applied voltage varying from -4.8 V to 4.8 V was simulated for 20 ns and the ionic current was calculated (see Figure 1a). The ionic currents showed a good linear relationship with the voltages (see Figure 1a), and the linear fitting (I = 5.80 V, R2 = 0.99, linearly fitting I-V curve at the whole voltage range) yielded an ionic conductance of ~ 5.80 nS for the nanopore. Other experimental studies also reported ionic conductance of 7 nS68 or 11 nS35 for MoS2 nanopore of ~2.20 nm diameter. Taking into account that, the experimental parameters (e.g., pH, temperature) may not be exactly the same, and the experimental MoS2 nanopores may not be ideal circles, our simulated conductance should be quite close to the experimental values. In addition, the contributions of K+ or Cl- ion movement to the ionic current were close: e.g., when the applied voltage was 1.2 V, K+ contributed 47% while Cl- contributed the rest 53% of ionic current. The similar contribution of K+ and Cl- ions agreed with their transference numbers69 and their similar diffusion coefficients (calculated under 1.2 V applied voltage): 29.18 (+/- 9.03) (1e-5 cm2/s) (K+), 35.69 (+/- 10.02) (1e-5 cm2/s) (Cl-), and a recent graphene nanopore simulation study70 which used the same water, K+ and Cl- parameters.

11



Figure 1. (a) I-V characteristic for the MoS2 nanopore with 2.2 nm diameter. (b) Electrostatic potential map of the MoS2 nanopore under an external transmembrane bias of 2.4 V. All point charges were approximated by Gaussian spheres with an inverse width β = 0.25 Å-1. (c) The average electrostatic potential profile across the pore along the z axis of the MoS2 nanopore at 2.4 V bias. The background image shows the nanopore with normal aligned with the z direction.

The instantaneous electrostatic potential map for the MoS2 nanopore under a transmembrane bias of 2.4 V was showed in Figure 1b, with point charges approximated by Gaussian spheres.71 Furthermore, the electrostatic potential profile across the pore along the direction of electric field, i.e., the z axis, was calculated by averaging the total potential over the pore along x and y directions (see Figure 1c). Figure 1b,c showed that the potential dropped primarily across the nanopore and did not change significantly in the electrolyte far from the nanopore. 3.2. Unfolded Peptides Adhere to MoS2 Membrane To study the translocation process of unfolded peptides through a MoS2 nanopore, more than 10 all-atom simulation systems (see Tables S1-3 for details in the 12


Page 12 of 38

Page 13 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Supporting Information) were built in this work. In a typical simulation system, a 48-residue unfolded peptide was initially threaded through a 2.20 nm diameter MoS2 nanopore with an extended unfolded conformation, which was solvated in 1 M KCl aqueous solution (see 'Methods' section for details). All simulation systems were minimized and equilibrated before an electric bias was applied. The equilibration process of three simulation systems would be discussed in details in this section, and the corresponding peptides were (FDFG)12 (-12e), (FGFG)12 (0e) and (FKFG)12 (+12e). During the 120 ns equilibration process (without applied electric field), the three model peptides behaved similarly. They collapsed from the initially extended conformation and adsorbed onto the MoS2 surface within 30 ns. The adherence process of (FDFG)12 to MoS2 nanosheet was shown in Figure 2a, and similar adsorption process was reported in a recent simulation study,72 where polyalanine model peptides adsorbed onto MoS2 surface within 20 ns. To quantitatively characterize the protein adhesion, the number of residues adhered to MoS2 and the number of contacts (see 'Methods' section for calculation details) between the peptides and MoS2 were calculated as shown in Figure 2b,c. These two values were quite similar (the number of adhered residues ~ 30, contact number ~ 400) among the three peptides after 60 ns simulation time. The minimum distance between the peptides and MoS2 (see Figure S3, Supporting Information) were also calculated: the minimum distance of (FDFG)12 or (FKFG)12 to the MoS2 membrane was about 0.25nm while (FGFG)12 fluctuated between 0.20 and 0.25 nm. The smaller distance of (FGFG)12 to MoS2 might be attributed to that, (FGFG)12 could move close to MoS2

13



due to the smaller steric hindrance between glycine residue and MoS2. The interaction energies of these three peptides with MoS2 were shown in Figure S4 in the Supporting Information. The van der Waals (vdW) interaction energies (~ -1000 kJ/mol) dominated the interaction energies, and were quite close among the three peptides, leading to similar total interaction energies (~ -1150 kJ/mol). Such similarity was quite expected, since the three peptides all contained 24 phenylalanine residues. The vdW energies of the three peptides could mainly be attributed to phenylalanine residues, since the vdW interaction energies of phenylalanine residues with MoS2 were much stronger than other residues, as shown in Figure S5a (Supporting Information; please note that, the vdW interaction energy per residue of phenylalanine was also considerably stronger, Figure S5b). Furthermore, phenylalanine residues were more inclined to adsorb onto the MoS2 surface: during the period of 60~120ns simulation time, ~74% of F residues adsorbed onto the MoS2 surface (the distance between the residue's COM and MoS2 was below 0.7 nm); while less than 40% of the charged residues (D or K) adsorbed onto MoS2. All these results indicate that the degree of adsorption of these peptides may not significantly depend on their charge, while hydrophobic phenylalanine residues may play more important roles.73-74 In addition, in following voltage-driven peptide translocation simulations, the bias voltage would be applied after a 120 ns equilibrium period if not otherwise specified, since the zero-electric-field system could reach equilibrium after 60 ns as indicated by the interaction energies, the adhesion number and the contact number.

14


Page 14 of 38

Page 15 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2. The conformations of unfolded peptides threaded through a 2.2 nm MoS2 nanopore. (a) The snapshots of the equilibration process of the (FDFG)12 peptide. MoS2 nanopore is shown as a gray transparent molecular surface. The peptide is shown in the licorice representation, with phenylalanine shown in magenta, aspartic acid shown in red, and glycine shown in white. (b) The number of amino acids adhered to the MoS2 membrane for negatively charged (FDFG)12, neutral (FGFG)12, and positively charged (FKFG)12. Each data point in this plot corresponds to a 200 ps block average of data. (c) The number of contacts within 6 Å between any pair of atoms from the peptide and MoS2 membrane, respectively.

3.3. Stepwise Voltage-Driven Transport of Charged Peptides through the MoS2 Nanopore MD simulations were performed to study how the charged peptides moved through the 2.20-nm diameter MoS2 nanopore under an external electric field. These charged peptides consisted of charged residues (e.g., aspartic acid, lysine, etc.) interspersed with neutral ones (e.g., phenylalanine, glycine, etc.). The initial conformations of these simulations were taken from the end of the equilibration simulations, after the peptides adsorbed onto both sides of the MoS2 membrane, as illustrated in Figure 2a.

15



The translocation simulation of each peptide was repeated three times (see Tables S1-3, Supporting Information). The translocation traces (defined as the number of residues that have transported through the midplane of the MoS2 membrane, N(residue), changing with the simulation time) of these peptides were shown in Figure S6 (Supporting Information), with average translocation speed and standard deviation listed in Table S4 (Supporting Information). The snapshot of the (FDFD)12 (-24e) simulation system under an external bias voltage of 600 mV (a positive voltage corresponded to an upward electric field) was shown in Figure 3a. As driven by the bias voltage, the negatively charged (FDFD)12 peptide moved against the electric field direction and adhered to the MoS2 membrane during the whole transmembrane process (see Movie S1, Supporting Information). According to Figure 3b, the transmembrane process showed a stepwise character, which consisted of long stationary periods interspersed with short, quick steps (see Movie S1). Such simulation was repeated three times (see Figure 3b). A positively charged peptide (FKFK)12 (+24e) was also simulated three times under a 1.2 V transmembrane bias (see Figure 3c), which moved in opposite direction (upward). All these simulations showed similar stepwise character. Such stepwise movement of biopolymers through nanopores was observed in a range of other studies, where DNA or protein passed through solid-state nanopores25-26 or bio-nanopores.75-76 To evaluate the effect of the applied bias voltage on the peptide transportation speed, the (FDFD)12 (-24e) and (FGDG)12 (-12e) simulations were also performed at 1.2 V and 2.4 V bias voltage (see Figure 3d,e). The translocation speed of (FDFD)12

16


Page 16 of 38

Page 17 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(-24e) at 1.2 V and 2.4 V were ~4.4 times and ~25.4 times faster than that at 600 mV, respectively (The translocation speed reported in this work was the average speed from three simulations if not otherwise specified, see Table S4 in the Supporting Information). The transmembrane voltage showed even greater influence on the transportation speed of the (FGDG)12 (-12e) peptide, which increased by ~16.3 times and ~48.8 times at 1.2 V and 2.4 V, respectively. The peptide translocation at 1.2 and 2.4 V showed stepwise character similar to that at 0.6 V, but with larger translocation steps and faster speed. The stepwise motion of peptide through the nanopore indicates the promising potential for protein sequencing applications. First, when the peptide translocation simulation, e.g., (FDFD)12 or (FKFK)12 (see Figure 3b,c), was repeated for three times, the peptide translocation usually paused after the same number of amino acids had permeated through the nanopore. Such influence of peptide sequence on the translocation rate could be employed to deduce the peptide sequence, which would be discussed in following sections 3.4 & 3.5. Furthermore, the long pause during the translocation process might yield well-defined signals for reading the content in the nanopore. The pause time shown in Figure 3 was tens of ns, and could be extended to μs at lower transmembrane bias. Various detection methods could be employed to read the peptide sequence, among which ionic current measurement would be discussed as a proof of concept implementation in section 3.6.

17



Figure 3. Stepwise voltage-driven transport of charged peptides. (a) A representative snapshot of the (FDFD)12 system. Mo and S atoms of the MoS2 surface are drawn as pink and yellow balls, respectively. The (FDFD)12 peptide is drawn as sticks, with phenylalanine shown in magenta, aspartic acid shown in red. The water box is depicted with cyan transparent surface, and K+ and Cl- ions are shown as blue and red spheres, respectively. The red arrow represents the electric field direction. (b, c) Translocation traces of (b) the (FDFD)12 peptide at 600 mV bias and (c) the (FKFK)12 peptide at 1.2 V bias, respectively. (d, e) Permeation traces of the (FDFD)12 and (FGDG)12 peptides at 600 mV (d, top), 1.2 V (d, bottom) and (e) 2.4 V bias. N(residue) means the number of translocated residues, calculated by counting the number of residues that have transported through the midplane of the MoS 2 membrane. A positive N(residue), the number of translocated residues, indicates the translocation direction is opposite to the applied electric field, while a negative N(residue) indicates translocation in the direction of the applied electric field. Only 18


Page 18 of 38

Page 19 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


one translocation trace for each simulation system was shown in panels (d)&(e) for the sake of clarity. See Figure S6 in Supporting Information for more translocation traces.

3.4. The Effect of Peptide Sequence on the Translocation Speed Proteins show huge sequence diversity due to the combination of twenty amino acids. Thus, the influence of the peptide sequence on its voltage-driven translocation was systematically studied in this section. First, the dependence of translocation speed on the peptide charge density was investigated. Six peptides consisting of glycine and aspartic acid, with glycine:aspartate ratio varying from 1:1 to 8:1 were simulated. These peptides are (DGDG)12,

(DGG)16,

(DGGG)12,

(DGGGG)9DGG,

(DGGGGG)8

and

(DGGGGGGGG)5DGG, respectively. A typical simulation system, (DGGG)12 system, was shown in Figure 4a. Each simulation system was equilibrated for more than 60 ns, and then was simulated three times under a 600 mV external bias to drive the peptide chain through the MoS2 nanopore. The translocation traces of these peptides with different glycine:aspartate ratios were shown in Figure 4b, which yielded the permeation rates (see Figure 4c). These results indicate that the translocation speed of these peptides positively correlates with their charge density well: the higher charge density, the faster the translocation (see Figure 4b,c). Other peptides, e.g., (FDFD) 12 and (FDFG)12, were also simulated at 1.2 V bias, showing similar trend: (FDFD)12 (-24e) moved through the nanopore ~17 times faster than (FDFG)12 (-12e), while

19



(FKFK)12 (+24e) translocated through the nanopore ~16.4 times faster than (FKFG)12 (+12e) (see Figure 5a). Such dependence could be explained by that, the charged residues of peptides with higher charge density would wander into the nanopore more frequently to be pulled through the nanopore by the external bias (note the voltage drop mainly occurs in the nanopore, Figure 1c). The charged residues play important roles in the voltage-driven translocation process. The z coordinate of Asp19 in (DGGGGG)8 was plotted as a function of simulation time in Figure S7, which indicated two types of Asp19 motions: 1. diffusion on the MoS2 surface to approach the nanopore (0-87 ns); 2. permeation through the nanopore as driven by the transmembrane bias (87-120 ns). The Asp19 translocation through the nanopore (red arrow) coincided with the second translocation step (blue arrow) of the (DGGGGG)8 peptide (Figure S7), while most of other residues (e.g., Asp13, Asp25) fluctuated around the equilibrium positions. This agreed with Movie S2 that, the peptide kept adsorbing on the MoS2 surface during the translocation process, and indicated that the peptide had to overcome an energy barrier of unbinding from the MoS2 surface during this process. The diffusion motion of charged resides played more significant roles in the case of rather sparely charged peptides, where the charged part of the peptides would eventually approach the nanopore by diffusion and moved through the nanopore by the electrophoretic pull (see Movie S2, Supporting Information). The energy barrier of peptide unbinding from the MoS2 surface and the diffusion motion of the charged residue approaching the nanopore may explain the stepwise character of the peptide translocation. A very

20


Page 20 of 38

Page 21 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


recent study also showed peptides kept adsorbing onto graphene surface when translocating stepwisely through a graphene nanopore with speed quite close to us.32 The adsorption of peptides to MoS2 or graphene surface played important roles in shaping the stepwise character of the peptide translocation.25,77

Figure 4. The effect of peptide charge density on the translocation speed. (a) A snapshot of a representative simulation system, (DGGG)12 system. The (DGGG)12 peptide chain is shown in the licorice representation, with glycine shown in green, aspartic acid shown in red. The water box is depicted with cyan transparent surface, and K+ and Cl- ions are shown as blue and red balls, respectively. (b) Permeation traces of six peptides with glycine/aspartate ratio varying from 1:1 to 8:1 (each peptide contains 48 amino acids) at 600 mV bias. (c) The average permeation rate of the six peptides, calculated from (b).

Second, peptides with the same charge density but different sequence were systematically simulated to move through the MoS2 nanopore under a 1.2 V applied bias. According to these simulations, replacing aspartate residue with the one-carbon longer residue, E (e.g., (FDFG)12 vs (FEFG)12), did not change the translocation speed 21



much. The effect of replacing D with K (e.g., (FDFD)12 vs (FKFK)12; (FDFG)12 vs (FKFG)12) on the translocation speed was not significant neither (see Figure 5a), though such mutation even changed the peptides' charge and their movement direction. To the contrary, replacing F with G, e.g., (GDGD)12 vs (FDFD)12 and (FGDG)12 vs (FDFG)12 did increase the speed by more than 10 times (see Figure 5b,c). The effect of such mutations, which did not change the charge density, on the translocation speed might be attributed to the vdW interactions between the peptide and the MoS 2 membrane to some extent. Similar vdW interaction energies of peptides with MoS 2 usually lead to similar translocation speed: e.g., the vdW interaction energies of (FDFG)12 and (FEFG)12 were both ~ -1000 kJ/mol (see Figure S8, Supporting Information); while smaller (less negative) vdW interaction energies would yield higher speed: e.g., the vdW interaction energies of (GDGD)12 and (FDFD)12 were ~ -570 kJ/mol and ~ -950 kJ/mol, respectively (see Figure S9, Supporting Information). The translocation speed also negatively correlated with the number of hydrophobic phenylalanine residue, which retarded the translocation process quite significantly. Phenylalanine residue has been known to adsorb onto various surfaces (e.g., MoS 2, graphene, and carbon nanotube) with hydrophobic interactions, and play important roles in the protein-surface interactions.73,78-79 Finally, we note that, sometimes peptides may move through the nanopore extremely slowly or even do not move unidirectionally under electric field, e.g., sparsely charged peptides or peptides containing opposite charged side chains. In such cases, various methods could be employed to facilitate the unidirectional permeation

22


Page 22 of 38

Page 23 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


of the peptides: tuning the residues' protonation state and their charge by adjusting the solution pH value, coupling the peptide to polyanions (e.g., oligonucleotides)80 or charged surfactants (e.g., SDS)4, pulling the peptide through the nanopore by AFM8, molecular motor9 or water flow81, as would be discussed in the following section.

Figure 5. The effect of peptide sequence on the translocation of peptide through MoS 2 nanopore at 1.2 V bias. (a) The translocation traces of the peptides with different charge. (b) The translocation traces of the peptides with mutation from aspartic acid (magenta) to glutamic acid (cyan) (top), and from glycine (pale blue) to hydrophobic phenylalanine (magenta) (bottom). (c) The translocation traces of (FGDG)12 (magenta) and (FDFG)12 (cyan) peptides.

3.5. Peptides Translocation through the MoS2 Nanopore Driven by Water Flow Peptides containing very few or oppositely charged residues may move through a nanopore extremely slowly or even do not move unidirectionally under a given electric field. Besides attaching polyanions or charged surfactants to the peptides to facilitate the electric field-driven transportation, other force or field may also be employed to drive the peptides translocate through the nanopore. In experiments, hydrostatic pressure gradient has been employed in the single molecule nanopore

23



analysis of protein7 and DNA81, thus this section would discuss transporting peptides through the MoS2 nanopore with water flow generated a hydrostatic pressure gradient. In this section, three downward constant accelerations: -0.0001 nm/ps-2, -0.05 nm/ps-2, -0.1 nm/ps-2 were exerted to each water molecule to create water flows accelerating the transmembrane process of (FGFG)12 peptide (see Figure 6b-d) and Trx protein fragment (Trx1-48) (see Figure 6f-h). When the water flow was absent (Figure 6a,e) or the acceleration was no larger than 0.0001 nm/ps2 (Figure 6b,f), (FGFG)12 and Trx1-48 peptides did not permeate substantially, with translocation trace fluctuating, even though the transmembrane bias was as high as 1.2 V. When the acceleration was above 0.05 nm/ps2, the two peptides permeated through the MoS2 nanopore along the water flow direction (downward). With the acceleration increasing from 0.05 nm/ps2 to 0.1 nm/ps2, the translocation rate of (FGFG)12 rose from 0.044 res/ns to 0.708 res/ns, while that of Trx1-48 rose from 0.181 res/ns to 0.375 res/ns. The peptide permeation driven by the water flow, either 0.05 nm/ps2 or 0.1 nm/ps2, showed stepwise character (Figure 6c-d,g-h) similar to that driven by transmembrane voltage (section 3.3), with the peptide absorbed onto the MoS2 membrane during the whole process (see Movie S3, Supporting Information). Therefore, uncharged or sparsely charged peptides could move through a MoS2 nanopore stepwisely driven by a water flow or hydrostatic pressure gradient. The translocation speed could be tuned by adjusting the hydrostatic pressure difference across the MoS2 membrane. This offers alternative possibility, other than transmembrane bias, to drive peptides through the MoS2 nanopore so that the content

24


Page 24 of 38

Page 25 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


of the peptide fragment in the nanopore can be analyzed.

Figure 6. Water flow controlled peptides translocation through the MoS2 nanopore. (a,e) The translocation traces of a neutral (FGFG)12 peptide and a Trx protein fragment (Trx1-48) at 1.2 V, respectively. (b-d) and (f-h) The traces of water flow-induced (FGFG)12 and Trx1-48 peptides translocation through the MoS2 nanopore at different acceleration of water molecules: (b, f) 0.0001 nm/ps2, (c, g) 0.05 nm/ps2, (d, h) 0.1 nm/ps2, respectively. There is no water flow in panels a and e, and no applied voltage in panels (b-d) & (f-h).

3.6. Identification of the Amino Acid Type in MoS2 Nanopore by Ionic Current In this section, the feasibility of sequencing a peptide, or reading the content in the MoS2 nanopore, was investigated by measuring the ionic current through the nanopore (the "resistive pulse sensing" scheme) by MD simulations. This detection method is quite simple, yet has been widely used.82 (FDFD)12 (-24e) system and (FKFK)12 (+24e) system were simulated at 600 mV and 1.2 V, respectively, with translocation traces and ionic current blockades shown in Figure 7. There were several long pauses in the stepwise translocation trace, which 25



yielded well-defined ionic current values. The ionic current varied as the peptide translocated and the content in the MoS2 nanopore changed. The peptide fragment conformation in the nanopore for each translocation pause was shown in Figure 7c,f. Significant changes could be spotted between the third (yellow, the amino acid fragment in the nanopore was FDF, ionic current = 5.04 nA) and the fourth pause (orange, DFD, 4.29 nA) in the (FDFD)12 system (see Figure 7a); among the third (yellow, FKF, 7.48 nA), fourth (red, FKFK, 5.25 nA) and fifth pauses (orange, FK, 8.42 nA) in the (FKFK)12 system (see Figure 7d). The same content in the nanopore usually lead to similar currents: e.g., the first (cyan, DFD, 5.31 nA) and second (green, DFD, 5.38 nA) pauses in the (FDFD)12 system; the second (green, FKF, 7.49 nA) and third (yellow, FKF, 7.48 nA) pauses in the (FKFK)12 system. Nevertheless, there are also some exceptions, which could be attributed to the dependence of ionic current on the peptide fragment conformation in the nanopore. Such dependence was also reported in recent studies where peptide permeated through a nanopore.32

26


Page 26 of 38

Page 27 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 7. Ionic current blockages produced by peptide translocating through a 2.2-nm diameter MoS2 nanopore. (a) The translocation trace of the (FDFD)12 peptide at a 600 mV bias. The colored horizontal lines highlight individual translocation steps, and the corresponding amino acid fragment in the nanopore is indicated in the above bracket. (b) The ionic current passing through a MoS2 nanopore as the (FDFD)12 peptide permeates through the nanopore. The stock lines present the background fluctuating currents. The colored horizontal lines indicate the average ionic current for each translocation step, the color and the length of the line matches that from the translocation trace (panel (a)). (c) The snapshots of the representative conformations of the (FDFD)12 peptide at the first, second, third and fourth translocation pauses indicated by cyan, green, yellow and orange rectangles, respectively. Phenylalanine is shown in magenta and aspartic acid is shown in red. (d-f) Same as in panels (a-c) but for the (FKFK)12 peptide under a 1.2 V external bias. Panel (f) shows the peptide conformations at the first (cyan), second (green), third (yellow) and fifth (orange) translocation pauses; phenylalanine is shown in magenta and lysine is shown in cyan; the enlargement factor of the snapshots in panel (f) is slightly larger than that in panel (c) for the sake of clarity. N(count) means the number of translocated residues, calculated by counting the number of residues that have transported through the

27



midplane of the membrane. A positive N(count) indicates the translocation direction is opposite to the applied electric field, while a negative N(count) indicates translocation in the direction of the applied electric field. Positively charged peptide, (FKFK)12, moved in the direction of the electric field, and negatively charged peptide, (FDFD)12, moved against the electric field. The above calculations indicated the stepwise translocation of a peptide through a MoS2 nanopore could yield well defined blockade ionic current to identify the amino acid sequence. The pause time in the simulations was on the order of tens ns, but could be extended to microseconds by lowering the applied bias in the experiment. The experimental ionic current would be even more well defined, not only because the measuring time is prolonged, but also because the experimental system is much larger than the simulation one. Stretching the peptide, electric filed83, local heating84 or smaller nanopore8 can be used to control the peptide conformation in the nanopore so that the amino acid sequence can be solved solely from the ionic current.85 4. CONCLUSIONS In this work, the translocation of peptides through a MoS2 nanopore and the associating ionic current was studied with MD simulations. The open pore current of the MoS2 nanopore correlated linearly with the transmembrane bias, which mainly dropped in the nanopore region. The unfolded peptide adsorbed onto the MoS2 membrane and permeated stepwisely through the nanopore when a transmembrane bias or hydrostatic pressure gradient was applied. The translocation could readily be tuned by the applied bias or hydrostatic pressure gradient. Such stepwise peptide

28


Page 28 of 38

Page 29 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


translocation may yield various well-defined signals for protein sequencing, e.g., ionic current blockages could be generated by a transmembrane bias, which correlated with the content of the peptide fragment in the MoS2 nanopore. Overall, this proof of concept study showed encouraging prospect of protein sequencing with a MoS2 nanopore, while there is still plenty of room to improve this technique: adjusting the experimental parameters (e.g., transmembrane bias, hydrostatics pressure, nanopore size and salt solution); attaching polyanions or charged surfactants to the peptide to facilitate the voltage-driven translocation; pulling the protein chain through the nanopore by AFM or a molecular motor; controlling the peptide conformation in the nanopore by stretching; employing other analysis methods (e.g., AFM, measuring the transverse current); etc. ASSOCIATED CONTENT Supporting Information Supplementary tables, figures, and movies, including the essential details of all simulations (Table S1-3); the statistic data of the translocation speed (Table S4); the I-V characteristics of the 1.00 nm and 2.20 nm MoS2 nanopore (Figure S2); the minimum distances (Figure S3); interaction energies between MoS2 and peptides (Figure S4-5, S8-9); the translocation traces (repeated three times) of some peptides (Figure S6); the translocation trace and the time evolution of the residues z coordinate of (DGGGGG)8 peptide (Figure S7); and the translocation movies (Movie S1-3) for the (FDFD)12, (DGGGG)9DGG and (FGFG)12 peptides. The calculation of the water contact angle of MoS2 nanosheet.

29



AUTHOR INFORMATION Corresponding Author *E-mail: [email protected] (L. Li). *E-mail: [email protected] (J. Zhou) Phone: +8613902325164. ORCID Libo Li: 0000-0001-7699-4484 Zhiwei Qiao: 0000-0002-1264-3762 Jian Zhou: 0000-0002-3033-7785 Notes The authors declare no competing financial interest. ACKNOWLEDGEMENTS Financial support from the National Science Foundation of China (21506066 and 21676094), Guangzhou Technology Project (2018-1002-SF-0525), the Guangdong Science Foundation (2014A030310260), and the Fundamental Research Funds for the Central Universities SCUT (2017ZD069 and 2017MS083) and China Postdoctoral Science Foundation (2016M590781 and 2017T100631) are gratefully acknowledged. CPU hours allocated by the Guangzhou Supercomputer Center of China and SCUTGrid at South China University of Technology are gratefully acknowledged. REFERENCES (1) Reiner, J. E.; Balijepalli, A.; Robertson, J. W.; Campbell, J.; Suehle, J.; Kasianowicz, J. J., Disease Detection and Management Via Single Nanopore-Based Sensors. Chem. Rev. 2012, 112, 6431-6451. 30


Page 30 of 38

Page 31 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(2) Wang, Y.; Zheng, D.; Tan, Q.; Wang, M. X.; Gu, L. Q., Nanopore-Based Detection of Circulating Micrornas in Lung Cancer Patients. Nat. Nanotechnol. 2011, 6, 668-674. (3) Freedman, K. J.; Bastian, A. R.; Chaiken, I.; Kim, M. J., Solid-State Nanopore Detection of Protein Complexes: Applications in Healthcare and Protein Kinetics. Small 2013, 9, 750-759. (4) Kennedy, E.; Dong, Z.; Tennant, C.; Timp, G., Reading the Primary Structure of a Protein with 0.07 nm3 Resolution Using a Subnanometre-Diameter Pore. Nat. Nanotechnol. 2016, 11, 968-976. (5) Chandramouli, K.; Qian, P. Y., Proteomics: Challenges, Techniques and Possibilities to Overcome Biological Sample Complexity. Hum. Genomics Proteomics 2009, 2009, 239204. (6) Kowalczyk, S. W.; Hall, A. R.; Dekker, C., Detection of Local Protein Structures Along DNA Using Solid-State Nanopores. Nano Lett. 2010, 10, 324-328. (7) Li, J.; Hu, R.; Li, X.; Tong, X.; Yu, D.; Zhao, Q., Tiny Protein Detection Using Pressure through Solid-State Nanopores. Electrophoresis 2017, 38, 1130-1138. (8) Dong, Z.; Kennedy, E.; Hokmabadi, M.; Timp, G., Discriminating Residue Substitutions in a Single Protein Molecule Using a Sub-Nanopore. ACS Nano 2017, 11, 5440-5452. (9) Nivala, J.; Marks, D. B.; Akeson, M., Unfoldase-Mediated Protein Translocation through an Alpha-Hemolysin Nanopore. Nat. Biotechnol. 2013, 31, 247-250. (10) McNally, B.; Singer, A.; Yu, Z.; Sun, Y.; Weng, Z.; Meller, A., Optical Recognition of Converted DNA Nucleotides for Single-Molecule DNA Sequencing Using Nanopore Arrays. Nano Lett. 2010, 10, 2237-2244. (11)Mikheyev, A. S.; Tin, M. M., A First Look at the Oxford Nanopore Minion Sequencer. Mol. Ecol. Resour. 2014, 14, 1097-1102. (12) Gu, L. Q.; Shim, J. W., Single Molecule Sensing by Nanopores and Nanopore Devices. Analyst 2010, 135, 441-451. (13) Rosen, C. B.; Rodriguez-Larrea, D.; Bayley, H., Single-Molecule Site-Specific Detection of Protein Phosphorylation with a Nanopore. Nat. Biotechnol. 2014, 32, 179-181. (14) Dekker, C., Solid-State Nanopores. Nat. Nanotechnol. 2007, 2, 209-215. (15) Kim, M. J.; Wanunu, M.; Bell, D. C.; Meller, A., Rapid Fabrication of Uniformly Sized Nanopores and Nanopore Arrays for Parallel DNA Analysis. Adv. Mater. 2006, 18, 3149-3153. 31



(16) Yang, J.; Ferranti, D. C.; Stern, L. A.; Sanford, C. A.; Huang, J.; Ren, Z.; Qin, L. C.; Hall, A. R., Rapid and Precise Scanning Helium Ion Microscope Milling of Solid-State Nanopores for Biomolecule Detection. Nanotechnology 2011, 22, 285310. (17) Talaga, D. S.; Li, J., Single-Molecule Protein Unfolding in Solid State Nanopores. J. Am. Chem. Soc. 2009, 131, 9287-9297. (18) Al-Dirini, F.; Mohammed, M. A.; Hossain, M. S.; Hossain, F. M.; Nirmalathas, A.; Skafidas, E., Tuneable Graphene Nanopores for Single Biomolecule Detection. Nanoscale 2016, 8, 10066-10077. (19)Liu, S., et al., Boron Nitride Nanopores: Highly Sensitive DNA Single-Molecule Detectors. Adv. Mater. 2013, 25, 4549-4554. (20) Gu, Z.; Zhang, Y.; Luan, B.; Zhou, R., DNA Translocation through Single-Layer Boron Nitride Nanopores. Soft Matter 2016, 12, 817-823. (21) Liu, K.; Feng, J.; Kis, A.; Radenovic, A., Atomically Thin Molybdenum Disulfide Nanopores with High Sensitivity for DNA Translocation. ACS nano 2014, 8, 2504-2511. (22) Farimani, A. B.; Min, K.; Aluru, N. R., DNA Base Detection Using a Single-Layer MoS2. Acs Nano 2014, 8, 7914-7922. (23) Schneider, G. F.; Kowalczyk, S. W.; Calado, V. E.; Pandraud, G.; Zandbergen, H. W.; Vandersypen, L. M.; Dekker, C., DNA Translocation through Graphene Nanopores. Nano Lett. 2010, 10, 3163-3167. (24) Heerema, S. J.; Dekker, C., Graphene Nanodevices for DNA Sequencing. Nat. Nanotechnol. 2016, 11, 127-136. (25) Qiu, H.; Sarathy, A.; Leburton, J. P.; Schulten, K., Intrinsic Stepwise Translocation of Stretched Ssdna in Graphene Nanopores. Nano Lett. 2015, 15, 8322-8330. (26) Wells, D. B.; Belkin, M.; Comer, J.; Aksimentiev, A., Assessing Graphene Nanopores for Sequencing DNA. Nano Lett. 2012, 12, 4117-4123. (27) Sathe, C.; Zou, X.; Leburton, J.-P.; Schulten, K., Computational Investigation of DNA Detection Using Graphene Nanopores. ACS nano 2011, 5, 8842-8851. (28) Liang, L.; Cui, P.; Wang, Q.; Wu, T.; Ågren, H.; Tu, Y., Theoretical Study on Key Factors in DNA Sequencing with Graphene Nanopores. RSC Adv. 2013, 3, 2445. (29) Lv, W.; Chen, M.; Wu, R. a., The Impact of the Number of Layers of a Graphene Nanopore 32


Page 32 of 38

Page 33 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


on DNA Translocation. Soft Matter 2013, 9, 960-966. (30) Zhang, Z.; Shen, J.; Wang, H.; Wang, Q.; Zhang, J.; Liang, L.; Agren, H.; Tu, Y., Effects of Graphene Nanopore Geometry on DNA Sequencing. J. Phys. Chem. Lett. 2014, 5, 1602-1607. (31) Barati Farimani, A.; Heiranian, M.; Min, K.; Aluru, N. R., Antibody Subclass Detection Using Graphene Nanopores. J. Phys. Chem. Lett. 2017, 8, 1670-1676. (32) Wilson, J.; Sloman, L.; He, Z.; Aksimentiev, A., Graphene Nanopores for Protein Sequencing. Adv. Funct. Mater. 2016, 26, 4830-4838. (33) Paulechka, E.; Wassenaar, T. A.; Kroenlein, K.; Kazakov, A.; Smolyanitsky, A., Nucleobase-Functionalized Graphene Nanoribbons for Accurate High-Speed DNA Sequencing. Nanoscale 2016, 8, 1861-1867. (34) Shan, Y. P., et al., Surface Modification of Graphene Nanopores for Protein Translocation. Nanotechnology 2013, 24, 495102. (35)Feng, J.; Graf, M.; Liu, K.; Ovchinnikov, D.; Dumcenco, D.; Heiranian, M.; Nandigana, V.; Aluru, N. R.; Kis, A.; Radenovic, A., Single-Layer MoS2 Nanopores as Nanopower Generators. Nature 2016, 536, 197-200. (36) Heiranian, M.; Farimani, A. B.; Aluru, N. R., Water Desalination with a Single-Layer MoS2 Nanopore. Nat. Commun. 2015, 6, 8616. (37) Radisavljevic, B.; Radenovic, A.; Brivio, J.; Giacometti, V.; Kis, A., Single-Layer MoS2 Transistors. Nat. Nanotechnol. 2011, 6, 147-150. (38) Yang, X.; Li, Q.; Hu, G.; Wang, Z.; Yang, Z.; Liu, X.; Dong, M.; Pan, C., Controlled Synthesis of High-Quality Crystals of Monolayer MoS2 for Nanoelectronic Device Application. Sci. China Mater. 2016, 59, 182-190. (39) Fan, H.; Zhao, D.; Li, Y.; Zhou, J., Lysozyme Orientation and Conformation on MoS2 Surface: Insights from Molecular Simulations. Biointerphases 2017, 12, 02D416. (40) Govind Rajan, A.; Sresht, V.; Padua, A. A.; Strano, M. S.; Blankschtein, D., Dominance of Dispersion Interactions and Entropy over Electrostatics in Determining the Wettability and Friction of Two-Dimensional MoS2 Surfaces. ACS Nano 2016, 10, 9145-9155. (41) Varshney, V.; Patnaik, S. S.; Muratore, C.; Roy, A. K.; Voevodin, A. A.; Farmer, B. L., Md Simulations of Molybdenum Disulphide (MoS2): Force-Field Parameterization and Thermal Transport Behavior. Comput. Mater. Sci. 2010, 48, 101-108. 33



(42) Nicolini, P.; Polcar, T., A Comparison of Empirical Potentials for Sliding Simulations of MoS2. Comput. Mater. Sci. 2016, 115, 158-169. (43) Luan, B.; Zhou, R., Wettability and Friction of Water on a MoS2 Nanosheet. Appl. Phys. Lett. 2016, 108, 131601. (44) Stewart, J. A.; Spearot, D. E., Atomistic Simulations of Nanoindentation on the Basal Plane of Crystalline Molybdenum Disulfide (MoS2). Modell. Simul. Mater. Sci. Eng. 2013, 21, 045003. (45) Feng, J.; Liu, K.; Bulushev, R. D.; Khlybov, S.; Dumcenco, D.; Kis, A.; Radenovic, A., Identification of Single Nucleotides in MoS2 Nanopores. Nat. Nanotechnol. 2015, 10, 1070-1076. (46) Smolyanitsky, A.; Yakobson, B. I.; Wassenaar, T. A.; Paulechka, E.; Kroenlein, K., A MoS2-Based Capacitive Displacement Sensor for DNA Sequencing. ACS Nano 2016, 10, 9009-9016. (47) Terry, L. J.; Wente, S. R., Flexible Gates: Dynamic Topologies and Functions for FG Nucleoporins in Nucleocytoplasmic Transport. Eukaryot Cell 2009, 8, 1814-1827. (48)Yamada, J.; Phillips, J. L.; Patel, S.; Goldfien, G.; Calestagne-Morelli, A.; Huang, H.; Reza, R.; Acheson, J.; Krishnan, V. V.; Newsam, S., A Bimodal Distribution of Two Distinct Categories of Intrinsically Disordered Structures with Separate Functions in FG Nucleoporins. Mol. Cell. Proteomics 2010, 9, 2205-2224. (49) Katti, S. K.; LeMaster, D. M.; Eklund, H., Crystal Structure of Thioredoxin from Escherichia Coli at 1.68 Å Resolution. J. Mol. Biol. 1990, 212, 167-184. (50) Hanwell, M. D.; Curtis, D. E.; Lonie, D. C.; Vandermeersch, T.; Zurek, E.; Hutchison, G. R., Avogadro: An Advanced Semantic Chemical Editor, Visualization, and Analysis Platform. J. Cheminf. 2012, 4, 17. (51) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L., Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926-935. (52) Hess, B.; Kutzner, C.; Van Der Spoel, D.; Lindahl, E., Gromacs 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435-447. 34


Page 34 of 38

Page 35 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(53) Humphrey, W.; Dalke, A.; Schulten, K., Vmd: Visual Molecular Dynamics. J. Mol. Graphics 1996, 14, 33-38. (54) Mackerell, A. D., Jr.; Feig, M.; Brooks, C. L., 3rd, Extending the Treatment of Backbone Energetics in Protein Force Fields: Limitations of Gas-Phase Quantum Mechanics in Reproducing Protein Conformational Distributions in Molecular Dynamics Simulations. J. Comput. Chem. 2004, 25, 1400-1415. (55) Hess, B.; Bekker, H.; Berendsen, H. J.; Fraaije, J. G., Lincs: A Linear Constraint Solver for Molecular Simulations. J. Comput. Chem. 1997, 18, 1463-1472. (56) Miyamoto, S.; Kollman, P. A., Settle: An Analytical Version of the Shake and Rattle Algorithm for Rigid Water Models. J. Comput. Chem. 1992, 13, 952-962. (57) Liang, T.; Phillpot, S. R.; Sinnott, S. B., Parametrization of a Reactive Many-Body Potential for Mo–S Systems. Phys. Rev. B 2009, 79, 245110. (58) Kozbial, A.; Gong, X.; Liu, H.; Li, L., Understanding the Intrinsic Water Wettability of Molybdenum Disulfide (MoS2). Langmuir 2015, 31, 8429-8435. (59) Cheng, G.; Liao, M.; Zhao, D.; Zhou, J., Molecular Understanding on the Underwater Oleophobicity of Self-Assembled Monolayers: Zwitterionic Versus Nonionic. Langmuir 2017, 33, 1732-1741. (60) Liao, M.; Cheng, G.; Zhou, J., Underwater Superoleophobicity of Pseudozwitterionic Sams: Effects of Chain Length and Ionic Strength. J. Phys. Chem. C 2017, 121, 17390-17401. (61) Qiu, H.; Sarathy, A.; Schulten, K.; Leburton, J.-P., Detection and Mapping of DNA Methylation with 2D Material Nanopores. npj 2D Materials and Applications 2017, 1, 3. (62) Shirts, M. R.; Mobley, D. L.; Chodera, J. D.; Pande, V. S., Accurate and Efficient Corrections for Missing Dispersion Interactions in Molecular Simulations. J. Phys. Chem. B 2007, 111, 13052-13063. (63) Darden, T.; York, D.; Pedersen, L., Particle Mesh Ewald: An N⋅ log (N) Method for Ewald Sums in Large Systems. J. Chem. Phys. 1993, 98, 10089-10092. (64) Bussi, G.; Donadio, D.; Parrinello, M., Canonical Sampling through Velocity Rescaling. J. Chem. Phys. 2007, 126, 014101. (65) Berendsen, H. J.; Postma, J. v.; van Gunsteren, W. F.; DiNola, A.; Haak, J., Molecular Dynamics with Coupling to an External Bath. J. Chem. Phys. 1984, 81, 3684-3690. 35



(66) Li, L.; Fennell, C. J.; Dill, K. A., Field-Sea: A Model for Computing the Solvation Free Energies of Nonpolar, Polar, and Charged Solutes in Water. J. Phys. Chem. B 2014, 118, 6431-6437. (67) Wang, Y.; Li, L.; Wei, Y.; Xue, J.; Chen, H.; Ding, L.; Caro, J.; Wang, H., Water Transport with Ultralow Friction through Partially Exfoliated g-C3N4 Nanosheet Membranes with Self-Supporting Spacers. Angew. Chem. Int. Ed. Engl. 2017, 56, 8974-8980. (68) Waduge, P.; Bilgin, I.; Larkin, J.; Henley, R. Y.; Goodfellow, K.; Graham, A. C.; Bell, D. C.; Vamivakas, N.; Kar, S.; Wanunu, M., Direct and Scalable Deposition of Atomically Thin Low-Noise MoS2 Membranes on Apertures. ACS Nano 2015, 9, 7352-7359. (69) Longsworth, L., Transference Numbers of Aqueous Solutions of Potassium Chloride, Sodium Chloride, Lithium Chloride and Hydrochloric Acid at 25°by the Moving Boundary Method1. J. Am. Chem. Soc. 1932, 54, 2741-2758. (70) Liang, L.; Zhang, Z.; Shen, J.; Zhe, K.; Wang, Q.; Wu, T.; Ågren, H.; Tu, Y., Theoretical Studies on the Dynamics of DNA Fragment Translocation through Multilayer Graphene Nanopores. RSC Adv. 2014, 4, 50494-50502. (71) Aksimentiev, A.; Schulten, K., Imaging Alpha-Hemolysin with Molecular Dynamics: Ionic Conductance, Osmotic Permeability, and the Electrostatic Potential Map. Biophys. J. 2005, 88, 3745-3761. (72) Gu, Z.; Li, W.; Hong, L.; Zhou, R., Exploring Biological Effects of MoS2 Nanosheets on Native Structures of Alpha-Helical Peptides. J. Chem. Phys. 2016, 144, 175103. (73) Gu, Z.; Yang, Z.; Kang, S. G.; Yang, J. R.; Luo, J.; Zhou, R., Robust Denaturation of Villin Headpiece by MoS2 Nanosheet: Potential Molecular Origin of the Nanotoxicity. Sci Rep 2016, 6, 28252. (74) Ling, Y.; Gu, Z.; Kang, S.-g.; Luo, J.; Zhou, R., Structural Damage of a β-Sheet Protein Upon Adsorption onto Molybdenum Disulfide Nanotubes. J. Phys. Chem. C 2016, 120, 6796-6803. (75) Chu, J.; Gonzalez-Lopez, M.; Cockroft, S. L.; Amorin, M.; Ghadiri, M. R., Real-Time Monitoring of DNA Polymerase Function and Stepwise Single-Nucleotide DNA Strand Translocation through a Protein Nanopore. Angew. Chem. Int. Ed. Engl. 2010, 49, 10106-10109. 36


Page 36 of 38

Page 37 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(76) Bond, P. J.; Guy, A. T.; Heron, A. J.; Bayley, H.; Khalid, S., Molecular Dynamics Simulations of DNA within a Nanopore: Arginine-Phosphate Tethering and a Binding/Sliding Mechanism for Translocation. Biochemistry 2011, 50, 3777-3783. (77) Barati Farimani, A.; Dibaeinia, P.; Aluru, N. R., DNA Origami-Graphene Hybrid Nanopore for DNA Detection. ACS Appl. Mater. Interfaces 2016, 9, 92-100. (78) Wang, C.; Li, S.; Zhang, R.; Lin, Z., Adsorption and Properties of Aromatic Amino Acids on Single-Walled Carbon Nanotubes. Nanoscale 2012, 4, 1146-1153. (79) Rajesh, C.; Majumder, C.; Mizuseki, H.; Kawazoe, Y., A Theoretical Study on the Interaction of Aromatic Amino Acids with Graphene and Single Walled Carbon Nanotube. J. Chem. Phys. 2009, 130, 124911. (80) Rotem, D.; Jayasinghe, L.; Salichou, M.; Bayley, H., Protein Detection by Nanopores Equipped with Aptamers. J. Am. Chem. Soc. 2012, 134, 2781-2787. (81) Lu, B.; Hoogerheide, D. P.; Zhao, Q.; Zhang, H.; Tang, Z.; Yu, D.; Golovchenko, J. A., Pressure-Controlled Motion of Single Polymers through Solid-State Nanopores. Nano Lett. 2013, 13, 3048-3052. (82) Shi, W.; Friedman, A. K.; Baker, L. A., Nanopore Sensing. Anal. Chem. 2017, 89, 157-188. (83) Freedman, K. J.; Haq, S. R.; Edel, J. B.; Jemth, P.; Kim, M. J., Single Molecule Unfolding and Stretching of Protein Domains inside a Solid-State Nanopore by Electric Field. Sci Rep 2013, 3, 1638. (84) Belkin, M.; Maffeo, C.; Wells, D. B.; Aksimentiev, A., Stretching and Controlled Motion of Single-Stranded DNA in Locally Heated Solid-State Nanopores. ACS nano 2013, 7, 6816-6824. (85) Comer, J.; Aksimentiev, A., Predicting the DNA Sequence Dependence of Nanopore Ion Current Using Atomic-Resolution Brownian Dynamics. J. Phys. Chem. C 2012, 116, 3376-3393.

37



TOC Graphic

38


Page 38 of 38

Protein Translocation through a MoS2 Nanopore:A ... - ACS Publications

Recommend Documents