This data set provides files needed to run the simulations described in the manuscript entitled "Organic contaminants and atmospheric nitrogen at the graphene–water interface: A simulation study" using the molecular dynamics software NAMD and LAMMPS. The output of the simulations, as well as scripts used to analyze this output, are also included. The files are organized into directories corresponding to the figures of the main text and supplementary information. They include molecular model structure files (NAMD psf), force field parameter files (in CHARMM format), initial atomic coordinates (pdb format), NAMD or LAMMPS configuration files, Colvars configuration files, NAMD log files, and NAMD output including restart files (in binary NAMD format) and some trajectories in dcd format (downsampled). Analysis is controlled by shell scripts (Bash-compatible) that call VMD Tcl scripts. A modified LAMMPS C++ source file is also included.This material is based upon work supported by the 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) and Stampede2 at the Texas Advanced Computing Center through allocation BIO200030, which is supported by National Science Foundation grant number ACI-1548562.
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.
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
- 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)
Adaptive biasing force calculations
- namd/eabfZRest7_graph_chp1404.1.namd (continuation of eabfZRest7_graph_chp1404.0.namd)
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.
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.
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.
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. more » « less
- Award ID(s):
- NSF-PAR ID:
- Publisher / Repository:
- Date Published:
- Edition / Version:
- Subject(s) / Keyword(s):
- ["molecular dynamics","NAMD","graphite","graphene","peptides","peptide design","graphite\u2013water interface","graphene\u2013water interface","ABF","replica exchange molecular dynamics","adaptive biasing force","Colvars","self-assembly","beta sheet"]
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Data files were used in support of the research paper titled "“Experimentation Framework for Wireless
Communication Systems under Jamming Scenarios" which has been submitted to the IET Cyber-Physical Systems: Theory & Applications journal.
Authors: Marko Jacovic, Michael J. Liston, Vasil Pano, Geoffrey Mainland, Kapil R. Dandekar
Top-level directories correspond to the case studies discussed in the paper. Each includes the sub-directories: logs, parsers, rayTracingEmulation, results.
logs: - data logs collected from devices under test
- 'defenseInfrastucture' contains console output from a WARP 802.11 reference design network. Filename structure follows '*x*dB_*y*.txt' in which *x* is the reactive jamming power level and *y* is the jaming duration in samples (100k samples = 1 ms). 'noJammer.txt' does not include the jammer and is a base-line case. 'outMedian.txt' contains the median statistics for log files collected prior to the inclusion of the calculation in the processing script.
- 'uavCommunication' contains MGEN logs at each receiver for cases using omni-directional and RALA antennas with a 10 dB constant jammer and without the jammer. Omni-directional folder contains multiple repeated experiments to provide reliable results during each calculation window. RALA directories use s*N* folders in which *N* represents each antenna state.
- 'vehicularTechnologies' contains MGEN logs at the car receiver for different scenarios. 'rxNj_5rep.drc' does not consider jammers present, 'rx33J_5rep.drc' introduces the periodic jammer, in 'rx33jSched_5rep.drc' the device under test uses time scheduling around the periodic jammer, in 'rx33JSchedRandom_5rep.drc' the same modified time schedule is used with a random jammer.
parsers: - scripts used to collect or process the log files used in the study
- 'defenseInfrastructure' contains the 'xputFiveNodes.py' script which is used to control and log the throughput of a 5-node WARP 802.11 reference design network. Log files are manually inspected to generate results (end of log file provides a summary).
- 'uavCommunication' contains a 'readMe.txt' file which describes the parsing of the MGEN logs using TRPR. TRPR must be installed to run the scripts and directory locations must be updated.
- 'vehicularTechnologies' contains the 'mgenParser.py' script and supporting 'bfb.json' configuration file which also require TRPR to be installed and directories to be updated.
rayTracingEmulation: - 'wirelessInsiteImages': images of model used in Wireless Insite
- 'channelSummary.pdf': summary of channel statistics from ray-tracing study
- 'rawScenario': scenario files resulting from code base directly from ray-tracing output based on configuration defined by '*WI.json' file
- 'processedScenario': pre-processed scenario file to be used by DYSE channel emulator based on configuration defined by '*DYSE.json' file, applies fixed attenuation measured externally by spectrum analyzer and additional transmit power per node if desired
- DYSE scenario file format: time stamp (milli seconds), receiver ID, transmitter ID, main path gain (dB), main path phase (radians), main path delay (micro seconds), Doppler shift (Hz), multipath 1 gain (dB), multipath 1 phase (radians), multipath 1 delay relative to main path delay (micro seconds), multipath 2 gain (dB), multipath 2 phase (radians), multipath 2 delay relative to main path delay (micro seconds)
- 'nodeMapping.txt': mapping of Wireless Insite transceivers to DYSE channel emulator physical connections required
- 'uavCommunication' directory additionally includes 'antennaPattern' which contains the RALA pattern data for the omni-directional mode ('omni.csv') and directional state ('90.csv')
results: - contains performance results used in paper based on parsing of aforementioned log files
http://www.charmm-gui.org, is a web‐based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM‐GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM‐GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modelerfor reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builderfor building all‐atom simulation systems in various environments; (3) PACE CG Builderand Martini Makerfor building coarse‐grained simulation systems; (4) DEER Facilitatorand MDFF/xMDFF Utilizerfor experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ‐Solver, and GCMC/BD Ion Simulatorfor implicit solvent related calculations; (6) Ligand Binderfor ligand solvation and binding free energy simulations; and (7) Drude Prepperfor preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM‐GUI, such as Glycolipid Modelerfor generation of various glycolipid structures, and LPS Modelerfor generation of lipopolysaccharide structures from various Gram‐negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM‐GUI development project. © 2016 Wiley Periodicals, Inc.
This dataset contains sequence information, three-dimensional structures (from AlphaFold2 model), and substrate classification labels for 358 short-chain dehydrogenase/reductases (SDRs) and 953 S-adenosylmethionine dependent methyltransferases (SAM-MTases).
The aminoacid sequences of these enzymes were obtained from the UniProt Knowledgebase (https://www.uniprot.org). The sets of proteins were obtained by querying using InterPro protein family/domain identifiers corresponding to each family: IPR002347 (SDRs) and IPR029063 (SAM-MTases). The query results were filtered by UniProt annotation score, keeping only those with score above 4-out-of-5, and deduplicated by exact sequence matches.
The structures were submitted to the publicly available AlphaFold2 protein structure predictor (J. Jumper et al., Nature, 2021, 596, 583) using the ColabFold notebook (https://colab.research.google.com/github/sokrypton/ColabFold/blob/v1.1-premultimer/batch/AlphaFold2_batch.ipynb, M. Mirdita, S. Ovchinnikov, M. Steinegger, Nature Meth., 2022, 19, 679, https://github.com/sokrypton/ColabFold). The model settings used were msa_model = MMSeq2(Uniref+Environmental), num_models = 1, use_amber = False, use_templates = True, do_not_overwrite_results = True. The resulting PDB structures are included as ZIP archives
The classification labels were obtained from the substrate and product annotations of the enzyme UniProtKB records. Two approaches were used: substrate clustering based on molecular fingerprints and manual substrate type classification. For the substate clustering, Morgan fingerprints were generated for all enzymatic substrates and products with known structures (excluding cofactors) with radius = 3 using RDKit (https://rdkit.org). The fingerprints were projected onto two-dimensional space using the UMAP algorithm (L. McInnes, J. Healy, 2018, arXiv 1802.03426) and Jaccard metric and clustered using k-means. This procedure generated 9 clusters for SDR substrates and 13 clusters for SAM-MTases. The SMILES representations of the substrates are listed in the SDR_substrates_to_cluster_map_2DIMUMAP.csv and SAM_substrates_to_13clusters_map_2DIMUMAP.csv files.
The following manually defined classification tasks are included for SDRs: NADP/NAD cofactor classification; phenol substrate, sterol substrate, coenzyme A (CoA) substrate. For SAM-MTases, the manually defined classification tasks are: biopolymer (protein/RNA/DNA) vs. small molecule substrate, phenol subsrates, sterol substrates, nitrogen heterocycle substrates. The SMARTS strings used to define the substrate classes are listed in substructure_search_SMARTS.docx.
This archive contains COAWST model input, grids and initial conditions, and output used to produce the results in a submitted manuscript. The files are:
model_input.zip: input files for simulations presented in this paper
ocean_rip_current.in: ROMS ocean model input file
swan_rip_current.in: SWAN wave model input file (example with Hs=1m)
coupling_rip_current.in: model coupling file
rip_current.h: model header file
model_grids_forcing.zip: bathymetry and initial condition files
hbeach_grid_isbathy_2m.nc: ROMS bathymetry input file
hbeach_grid_isbathy_2m.bot: SWAN bathymetry input file
hbeach_grid_isbathy_2m.grd: SWAN grid input file
hbeach_init_isbathy_14_18_17.nc: Initial temperature, cool surf zone dT=-1C case
hbeach_init_isbathy_14_18_19.nc: Initial temperature, warm surf zone dT=+1C case
hbeach_init_isbathy_14_18_16.nc: Initial temperature, cool surf zone dT=-2C case
hbeach_init_isbathy_14_18_20.nc: Initial temperature, warm surf zone dT=+2C case
hbeach_init_isbathy_14_18_17p5.nc: Initial temperature, cool surf zone dT=-0.5C case
hbeach_init_isbathy_14_18_18p5.nc: Initial temperature, warm surf zone dT=+0.5C case
model_output files: model output used to produce the figures
netcdf files, zipped
x_rho (cross-shore coordinate, m)
y_rho (alongshore coordinate, m)
z_rho (vertical coordinate, m)
ocean_time (time since initialization, s, output every 5 mins)
h (bathymetry, m)
temp (temperature, Celsius)
dye_02 (surfzone-released dye)
Hwave (wave height, m)
Dissip_break (wave dissipation W/m2)
ubar (cross-shore depth-average velocity, m/s, interpolated to rho-points)
Case_141817.nc: cool surf zone dT=-1C Hs=1m
Case_141819.nc: warm surf zone dT=+1C Hs=1m
Case_141816.nc: cool surf zone dT=-2C Hs=1m
Case_141820.nc: warm surf zone dT=-2C Hs=1m
Case_141817p5.nc: cool surf zone dT=-0.5C Hs=1m
Case_141818p5.nc: warm surf zone dT=+0.5C Hs=1m
Case_141817_Hp5.nc: cool surf zone dT=-1C Hs=0.5m
Case_141819_Hp5.nc: warm surf zone dT=+1C Hs=0.5m
Case_141817_Hp75.nc: cool surf zone dT=-1C Hs=0.75m
Case_141819_Hp75.nc: warm surf zone dT=+1C Hs=0.75m
COAWST is an open source code and can be download at https://coawstmodel-trac.sourcerepo.com/coawstmodel_COAWST/. Descriptions of the input and output files can be found in the manual distributed with the model code and in the glossary at the end of the ocean.in file.
Corresponding author: Melissa Moulton, firstname.lastname@example.org