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1. Simulation Data for Design of Peptides that Fold and Self-Assemble on Graphite

   https://doi.org/10.5281/zenodo.6426152  

   Comer, Jeffrey ; Thakkar, Ravindra ; Velásquez-Silva, Astrid ; Miranda-Carvajal, Ingrid ( January 2022 , Zenodo)

   This data set for the manuscript entitled "Design of Peptides that Fold and Self-Assemble on Graphite" includes all files needed to run and analyze the simulations described in the this manuscript in the molecular dynamics software NAMD, as well as the output of the simulations. The files are organized into directories corresponding to the figures of the main text and supporting information. They include molecular model structure files (NAMD psf or Amber prmtop format), force field parameter files (in CHARMM format), initial atomic coordinates (pdb format), NAMD configuration files, Colvars configuration files, NAMD log files, and NAMD output including restart files (in binary NAMD format) and trajectories in dcd format (downsampled to 10 ns per frame). Analysis is controlled by shell scripts (Bash-compatible) that call VMD Tcl scripts or python scripts. These scripts and their output are also included.

   Version: 2.0

   Changes versus version 1.0 are the addition of the free energy of folding, adsorption, and pairing calculations (Sim_Figure-7) and shifting of the figure numbers to accommodate this addition.

   
   Conventions Used in These Files
   ===============================

   Structure Files
   ----------------
   - graph_*.psf or sol_*.psf (original NAMD (XPLOR?) format psf file including atom details (type, charge, mass), as well as definitions of bonds, angles, dihedrals, and impropers for each dipeptide.)

   - graph_*.pdb or sol_*.pdb (initial coordinates before equilibration)
   - repart_*.psf (same as the above psf files, but the masses of non-water hydrogen atoms have been repartitioned by VMD script repartitionMass.tcl)
   - freeTop_*.pdb (same as the above pdb files, but the carbons of the lower graphene layer have been placed at a single z value and marked for restraints in NAMD)
   - amber_*.prmtop (combined topology and parameter files for Amber force field simulations)
   - repart_amber_*.prmtop (same as the above prmtop files, but the masses of non-water hydrogen atoms have been repartitioned by ParmEd)

   Force Field Parameters
   ----------------------
   CHARMM format parameter files:
   - par_all36m_prot.prm (CHARMM36m FF for proteins)
   - par_all36_cgenff_no_nbfix.prm (CGenFF v4.4 for graphene) The NBFIX parameters are commented out since they are only needed for aromatic halogens and we use only the CG2R61 type for graphene.
   - toppar_water_ions_prot_cgenff.str (CHARMM water and ions with NBFIX parameters needed for protein and CGenFF included and others commented out)

   Template NAMD Configuration Files
   ---------------------------------
   These contain the most commonly used simulation parameters. They are called by the other NAMD configuration files (which are in the namd/ subdirectory):
   - template_min.namd (minimization)
   - template_eq.namd (NPT equilibration with lower graphene fixed)
   - template_abf.namd (for adaptive biasing force)

   Minimization
   -------------
   - namd/min_*.0.namd

   Equilibration
   -------------
   - namd/eq_*.0.namd

   Adaptive biasing force calculations
   -----------------------------------
   - namd/eabfZRest7_graph_chp1404.0.namd
   - namd/eabfZRest7_graph_chp1404.1.namd (continuation of eabfZRest7_graph_chp1404.0.namd)

   Log Files
   ---------
   For each NAMD configuration file given in the last two sections, there is a log file with the same prefix, which gives the text output of NAMD. For instance, the output of namd/eabfZRest7_graph_chp1404.0.namd is eabfZRest7_graph_chp1404.0.log.

   Simulation Output
   -----------------
   The simulation output files (which match the names of the NAMD configuration files) are in the output/ directory. Files with the extensions .coor, .vel, and .xsc are coordinates in NAMD binary format, velocities in NAMD binary format, and extended system information (including cell size) in text format. Files with the extension .dcd give the trajectory of the atomic coorinates over time (and also include system cell information). Due to storage limitations, large DCD files have been omitted or replaced with new DCD files having the prefix stride50_ including only every 50 frames. The time between frames in these files is 50 * 50000 steps/frame * 4 fs/step = 10 ns. The system cell trajectory is also included for the NPT runs are output/eq_*.xst.

   Scripts
   -------
   Files with the .sh extension can be found throughout. These usually provide the highest level control for submission of simulations and analysis. Look to these as a guide to what is happening. If there are scripts with step1_*.sh and step2_*.sh, they are intended to be run in order, with step1_*.sh first.

   
   CONTENTS
   ========

   The directory contents are as follows. The directories Sim_Figure-1 and Sim_Figure-8 include README.txt files that describe the files and naming conventions used throughout this data set.

   Sim_Figure-1: Simulations of N-acetylated C-amidated amino acids (Ac-X-NHMe) at the graphite–water interface.

   Sim_Figure-2: Simulations of different peptide designs (including acyclic, disulfide cyclized, and N-to-C cyclized) at the graphite–water interface.

   Sim_Figure-3: MM-GBSA calculations of different peptide sequences for a folded conformation and 5 misfolded/unfolded conformations.

   Sim_Figure-4: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

   Sim_Figure-5: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 295 K.

   Sim_Figure-5_replica: Temperature replica exchange molecular dynamics simulations for the peptide cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) with 20 replicas for temperatures from 295 to 454 K.

   Sim_Figure-6: Simulation of the peptide molecule cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) in free solution (no graphite).

   Sim_Figure-7: Free energy calculations for folding, adsorption, and pairing for the peptide CHP1404 (sequence: cyc(GTGSGTG-GPGG-GCGTGTG-SGPG)). For folding, we calculate the PMF as function of RMSD by replica-exchange umbrella sampling (in the subdirectory Folding_CHP1404_Graphene/). We make the same calculation in solution, which required 3 seperate replica-exchange umbrella sampling calculations (in the subdirectory Folding_CHP1404_Solution/). Both PMF of RMSD calculations for the scrambled peptide are in Folding_scram1404/. For adsorption, calculation of the PMF for the orientational restraints and the calculation of the PMF along z (the distance between the graphene sheet and the center of mass of the peptide) are in Adsorption_CHP1404/ and Adsorption_scram1404/. The actual calculation of the free energy is done by a shell script ("doRestraintEnergyError.sh") in the 1_free_energy/ subsubdirectory. Processing of the PMFs must be done first in the 0_pmf/ subsubdirectory. Finally, files for free energy calculations of pair formation for CHP1404 are found in the Pair/ subdirectory.

   Sim_Figure-8: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) where the peptides are far above the graphene–water interface in the initial configuration.

   Sim_Figure-9: Two replicates of a simulation of nine peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

   Sim_Figure-9_scrambled: Two replicates of a simulation of nine peptide molecules with the control sequence cyc(GGTPTTGGGGGGSGGPSGTGGC) at the graphite–water interface at 370 K.

   Sim_Figure-10: Adaptive biasing for calculation of the free energy of the folded peptide as a function of the angle between its long axis and the zigzag directions of the underlying graphene sheet.

    

   This material is based upon work supported by the US National Science Foundation under grant no. DMR-1945589. A majority of the computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CHE-1726332, CNS-1006860, EPS-1006860, and EPS-0919443. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562, through allocation BIO200030. 

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2. Insights into the behavior of nonanoic acid and its conjugate base at the air/water interface through a combined experimental and theoretical approach

   https://doi.org/10.1039/D0SC02354J  

   Luo, Man ; Wauer, Nicholas A. ; Angle, Kyle J. ; Dommer, Abigail C. ; Song, Meishi ; Nowak, Christopher M. ; Amaro, Rommie E. ; Grassian, Vicki H. ( October 2020 , Chemical Science)

   null (Ed.)

   The partitioning of medium-chain fatty acid surfactants such as nonanoic acid (NA) between the bulk phase and the air/water interface is of interest to a number of fields including marine and atmospheric chemistry. However, questions remain about the behavior of these molecules, the contributions of various relevant chemical equilibria, and the impact of pH, salt and bulk surfactant concentrations. In this study, the surface adsorption of nonanoic acid and its conjugate base is quantitatively investigated at various pH values, surfactant concentrations and the presence of salts. Surface concentrations of protonated and deprotonated species are dictated by surface-bulk equilibria which can be calculated from thermodynamic considerations. Notably we conclude that the surface dissociation constant of soluble surfactants cannot be directly obtained from these experimental measurements, however, we show that molecular dynamics (MD) simulation methods, such as free energy perturbation (FEP), can be used to calculate the surface acid dissociation constant relative to that in the bulk. These simulations show that nonanoic acid is less acidic at the surface compared to in the bulk solution with a p K a shift of 1.1 ± 0.6, yielding a predicted surface p K a of 5.9 ± 0.6. A thermodynamic cycle for nonanoic acid and its conjugate base between the air/water interface and the bulk phase can therefore be established. Furthermore, the effect of salts, namely NaCl, on the surface activity of protonated and deprotonated forms of nonanoic acid is also examined. Interestingly, salts cause both a decrease in the bulk p K a of nonanoic acid and a stabilization of both the protonated and deprotonated forms at the surface. Overall, these results suggest that the deprotonated medium-chain fatty acids under ocean conditions can also be present within the sea surface microlayer (SSML) present at the ocean/atmosphere interface due to the stabilization effect of the salts in the ocean. This allows the transfer of these species into sea spray aerosols (SSAs). More generally, we present a framework with which the behavior of partially soluble species at the air/water interface can be predicted from surface adsorption models and the surface p K a can be predicted from MD simulations. 

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3. Polarity‐Driven Atomic Displacements at the 2D Mg 2 TiO 4 ‐MgO (001) Oxide Interface for Hosting Potential Interlayer Excitons

   https://doi.org/10.1002/admi.202202320  

   Shin, Kidae ; Eltinge, Stephen ; Lee, Sangjae ; Shin, Hyungki ; Jiang, Juan ; Hong, Hawoong ; Davidson, Bruce A. ; Zou, Ke ; Ismail‐Beigi, Sohrab ; Ahn, Charles H. ; et al ( March 2023 , Advanced Materials Interfaces)

   Interlayer excitons in solid‐state systems have emerged as candidates for realizing novel platforms ranging from excitonic transistors and optical qubits to exciton condensates. Interlayer excitons have been discovered in 2D transition metal dichalcogenides, with large exciton binding energies and the ability to form various van der Waals heterostructures. Here, an oxide system consisting of a single unit cell of Mg₂TiO₄on MgO (001) is proposed as a platform for hosting interlayer excitons. Using a combination of density functional theory (DFT) calculations, molecular beam epitaxy growth, and in situ crystal truncation rod measurements, it is shown that the Mg₂TiO₄‐MgO interface can be precisely controlled to yield an internal electric field suitable for hosting interlayer excitons. The atoms in the polar Mg₂TiO₄layers are observed to be displaced to reduce polarity at the interface with the non‐polar MgO (001) surface. Such polarity‐driven atomic displacements strongly affect electrostatics of the film and the interface, resulting in localization of filled and empty band‐edge states in different layers of the Mg₂TiO₄film. The DFT calculations suggest that the electronic structure is favorable for localization of photoexcited electrons in the bottom layer and holes in the top layer, which may bind to form interlayer exciton states.

    

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4. Rapid and Real-Time Measurement of Membrane Potential Through Intramembrane Field Compensation

   https://doi.org/10.1115/SMASIS2020-2352  

   El-Beyrouthy, Joyce ; Freeman, Eric C. ( September 2020 , Smart Materials, Adaptive Structures, and Intelligent Systems 2020)

   null (Ed.)

   Synthetic lipid membranes are self-assembled biomolecular double layers designed to approximate the properties of living cell membranes. These membranes are employed as model systems for studying the interactions of cellular envelopes with the surrounding environment in a controlled platform. They are constructed by dispersing amphiphilic lipids into a combination of immiscible fluids enabling the biomolecules to self-assemble into ordered sheets, or monolayers at the oil-water interface. The adhesion of two opposing monolayer sheets forms the membrane, or the double layer. The mechanical properties of these synthetic membranes often differ from biological ones mainly due to the presence of residual solvent in between the leaflets. In fact, the double layer compresses in response to externally applied electrical field with an intensity that varies depending on the solvent present. While typically viewed as a drawback associated with their assembly, in this work the elasticity of the double layer is utilized to further quantify complex biophysical phenomena. The adsorption of charged molecules on the surface of a lipid bilayer is a key property to decipher biomolecule interactions at the interface of the cell membrane, as well as to develop effective antimicrobial peptides and similar membrane-active molecules. This adsorption generates a difference in the boundary potentials on either side of the membrane which may be tracked through electrophysiology. The soft synthetic membranes produced in the laboratory compress when exposed to an electric field. Tracking the minimum membrane capacitance allows for quantifying when the intrinsic electric field produced by the asymmetry is properly compensated by the supplied transmembrane voltage. The technique adopted in this work is the intramembrane field compensation (IFC). This technique focuses on the current generated by the bilayer in response to a sinusoidal voltage with a DC component, VDC. Briefly, the output sinusoidal current is divided into its harmonics and the second harmonic equals zero when VDC compensates the internal electric field. In this work, we apply the IFC technique to droplet interface bilayers (DIB) enabling the development of a biological sensor. A certain membrane elasticity is needed for accurate measurements and is tuned through the solvent selection. The asymmetric DIBs are formed, and an automated PID-controlled IFC design is implemented to rapidly track and compensate the membrane asymmetry. The closed loop system continuously reads the current and generates the corresponding voltage until the second harmonic is abated. This research describes the development and optimization of a biological sensor and examines how varying the structure of the synthetic membrane influences its capabilities for detecting membrane-environment interactions. This platform may be applied towards studying the interactions of membrane-active molecules and developing models for the associated phenomena to enhance their design.

    

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5. Interfacial water and ion distribution determine ζ potential and binding affinity of nanoparticles to biomolecules

   https://doi.org/10.1039/D0NR03792C  

   Liang, Dongyue ; Dahal, Udaya ; Zhang, Yongqian ; Lochbaum, Christian ; Ray, Dhiman ; Hamers, Robert J. ; Pedersen, Joel A. ; Cui, Qiang ( September 2020 , Nanoscale)

   The molecular features that dictate interactions between functionalized nanoparticles and biomolecules are not well understood. This is in part because for highly charged nanoparticles in solution, establishing a clear connection between the molecular features of surface ligands and common experimental observables such as ζ potential requires going beyond the classical models based on continuum and mean field models. Motivated by these considerations, molecular dynamics simulations are used to probe the electrostatic properties of functionalized gold nanoparticles and their interaction with a charged peptide in salt solutions. Counterions are observed to screen the bare ligand charge to a significant degree even at the moderate salt concentration of 50 mM. As a result, the apparent charge density and ζ potential are largely insensitive to the bare ligand charge densities, which fall in the range of ligand densities typically measured experimentally for gold nanoparticles. While this screening effect was predicted by classical models such as the Manning condensation theory, the magnitudes of the apparent surface charge from microscopic simulations and mean-field models are significantly different. Moreover, our simulations found that the chemical features of the surface ligand ( e.g. , primary vs. quaternary amines, heterogeneous ligand lengths) modulate the interfacial ion and water distributions and therefore the interfacial potential. The importance of interfacial water is further highlighted by the observation that introducing a fraction of hydrophobic ligands enhances the strength of electrostatic binding of the charged peptide. Finally, the simulations highlight that the electric double layer is perturbed upon binding interactions. As a result, it is the bare charge density rather than the apparent charge density or ζ potential that better correlates with binding affinity of the nanoparticle to a charged peptide. Overall, our study highlights the importance of molecular features of the nanoparticle/water interface and underscores a set of design rules for the modulation of electrostatic driven interactions at nano/bio interfaces. 

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