Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

299

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

299 results for “MD simulation”

Learn how ShareScore rates datasets ↗
zenodo32/100

CHARMM36 pure POPC MD simulation (300 K - 300ns - 1 bar)

<p>CHARMM36 POPC pure bilayer simulation (300 K, starting structure from CHARMM-GUI with 256 POPC lipids fully hydrated with 34 water molecules per lipid). The trajectory contains the whole simulation from 0 to 300 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids project (on the time window 50-300 ns).</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2018View details →
zenodo32/100

Berger POPC/POPE (50:50 ratio) MD simulation (300 K - 400ns - 1 bar)

<p>Berger POPC/POPE (50:50 ratio) bilayer simulation (300 K, with 128 POPC and 128 POPE lipids fully hydrated with 43 water molecules per lipid). The trajectory contains the whole simulation from 0 to 400 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no global net charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids IV project (on the time window 100-300 ns).<br> It should be noted that for this specific simulation, using PE lipids, the Berger forcefield was modified to add a repulsive potential onto the ethanolamine hydrogens.</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo32/100

Berger pure POPC MD simulation (300 K - 300ns - 1 bar)

<p>Berger POPC pure bilayer simulation (300 K, with 256 POPC lipids fully hydrated with 40 water molecules per lipid). The trajectory contains the whole simulation from 0 to 300 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no global net charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids IV project (on the time window 100-300 ns).</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo32/100

Berger POPC/DOPE (50:50 ratio) MD simulation (300 K - 300ns - 1 bar)

<p>Berger POPC/DOPE (50:50 ratio) bilayer simulation (300 K, with 128 POPC and 128 DOPE lipids fully hydrated with 40 water molecules per lipid). The trajectory contains the whole simulation from 0 to 300 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no global net charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids IV project (on the time window 100-300 ns).<br> It should be noted that for this specific simulation, using PE lipids, the Berger forcefield was modified to add a repulsive potential onto the ethanolamine hydrogens.</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo32/100

Berger DOPC/DOPE (50:50 ratio) MD simulation (300 K - 300ns - 1 bar)

<p>Berger DOPC/DOPE (50:50 ratio) bilayer simulation (300 K, with 128 DOPC and 128 DOPE lipids fully hydrated with 43 water molecules per lipid). The trajectory contains the whole simulation from 0 to 300 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no global net charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids IV project (on the time window 100-300 ns).<br> It should be noted that for this specific simulation, using PE lipids, the Berger forcefield was modified to add a repulsive potential onto the ethanolamine hydrogens.</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo32/100

Berger pure DOPC MD simulation (300 K - 300ns - 1 bar)

<p>Berger DOPC pure bilayer simulation (300 K, with 256 DOPC lipids fully hydrated with 43 water molecules per lipid). The trajectory contains the whole simulation from 0 to 300 ns skipped every 100 ps and centered on the P atoms. No ions were added as there is no global net charge in the system. This bilayer was used to calculate the order parameter and the area per lipid for the NMRlipids IV project (on the time window 100-300 ns).</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo32/100

MD simulations of bilayers containing PC/PS mixtures and CaCl_2: 250POPC_50POPS_neutral

<p>NMRLipids IV project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>250 POPC lipids, 50 POPS lipids, 73521 Atoms</p>

opencc-by-4.0Jan 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PS mixtures and CaCl_2: 150POPC_150POPS_neutral

<p>NMRLipids IV project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>150 POPC lipids, 150 POPS lipids, 71655 Atoms</p>

opencc-by-4.0Jan 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PS mixtures and CaCl_2: 250POPC_50POPS_1MCaCl_2

<p>NMRLipids IV project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>250 POPC lipids, 50 POPS lipids, 73964 Atoms</p>

opencc-by-4.0Jan 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PS mixtures and CaCl_2: 250POPC_50POPS_0.15MCaCl_2

<p>NMRLipids IV project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K</p> <p>250 POPC lipids, 50 POPS lipids, 73529 Atoms</p>

opencc-by-4.0Jan 2019View details →
zenodo32/100

Dataset to reproduce MD simulations described in "An atomistic view of the YiiP structural changes upon zinc(II) binding"

<p>Here are collected topologies, parameters, distance restraints, starting coordinates and trajectories for all the simulations reported in the manuscript entitled &quot;An atomistic view of the YiiP structural changes upon zinc(II) binding&quot;&nbsp;</p>

opencc-by-4.0May 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PG mixtures and CaCl_2: 250POPC_250POPG_0.15MCaCl_2

<p>NMRLipids IVb project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>250 POPC lipids, 250 POPG lipids, 127778&nbsp;Atoms</p>

opencc-by-4.0Oct 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PG mixtures and CaCl_2: 250POPC_250POPG_1MCaCl_2

<p>NMRLipids IVb project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>250 POPC lipids, 250 POPG lipids, 120677&nbsp;Atoms</p>

opencc-by-4.0Oct 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PG mixtures and CaCl_2: 250POPC_250POPG_neutral

<p>NMRLipids IVb project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>250 POPC lipids, 250 POPG lipids, 119974 Atoms</p>

opencc-by-4.0Oct 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PG mixtures and CaCl_2: 400POPC_100POPG_neutral

<p>NMRLipids IVb project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>400 POPC lipids, 100 POPG lipids, 122392 Atoms</p>

opencc-by-4.0Oct 2019View details →
zenodo32/100

MD simulations of bilayers containing PC/PG mixtures and CaCl_2: 400POPC_100POPG_1MCaCl_2

<p>NMRLipids IVb project (nmrlipids.blogspot.fi)</p> <p>Gromacs, CHARMM36 FF, 1 atm, 298K, 200ns (no pre-equilibration)</p> <p>400 POPC lipids, 100 POPG lipids, 123398 Atoms</p>

opencc-by-4.0Oct 2019View details →
zenodo32/100

The AF2 predicted structures and MD simulation results for the paper "In-situ structural insights into activity regulation of mammalian pyruvate dehydrogenase complex"

<p>Thank you for your interest in our work. You can discover content that interests you within the respective compressed packages, accompanied by &ldquo;readme&rdquo; files.</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

MD simulations files for: Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning

<p>Here's a rephrased version of the README file:</p> <p>#### Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning</p> <p>**Authors:** Mingyuan Zhang, Hao Wu, Yong Wang</p> <p>This repository contains the official implementation for the paper "Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning" by Mingyuan Zhang, Hao Wu, and Yong Wang. Included are all trajectories from our MD simulations in the form of PLUMED COLVAR files, as well as all analysis scripts and files needed to replicate the results and figures presented in both the main text and Supporting Information (SI) of the paper.</p> <p>The paper features two examples: Ala2 and Ala10. For each, we have organized all the associated simulation files as they were during our automated simulation pipeline. The directory structure is the same for both examples. Here, we use Ala2, found in the `Ala2` folder, as an example:</p> <p>### Key Components</p> <p>- **Automated Pipeline Implementation:** The pipeline is implemented in `Ala2/7-adaptive-40ps/ala2.ipynb`. This implementation is ready to use once all required packages are installed, and gmx/gmx_mpi/plumed are callable within the notebook. After configuring the environment and specifying parameters like `gpu_id`, `ntomp`, and `n_sim` according to your hardware, running the blocks will replicate the entire pipeline.</p> <p>- **Analysis Scripts:** The scripts to replicate the results or figures from the main text or SI are organized in three files: `Ala2/7-adaptive-40ps/AdaptiveSamplingAnalysis.ipynb`, `Ala2/7-adaptive-40ps/compare_with_msm.ipynb`, and `Ala2/7-adaptive-40ps/opes/COLVAR/analysis.ipynb`.</p> <p>### Directory Structure</p> <p>Under the `Ala2` main directory, there are seven subdirectories:</p> <p>- **`Ala2/1-topol/`**: Contains files generated during system construction, including the final Gromacs topology file `topol.top`, which is necessary for running the automated simulation script.</p> <p>- **`Ala2/2-em/`, `Ala2/3-nvt/`, `Ala2/4-npt/`**: These directories store files generated during energy minimization and NVT/NPT equilibration. The `Ala2/4-npt/npt.gro` file is required to run the automated simulation script.</p> <p>- **`Ala2/mdp/`**: Contains all mdp files used, including `Ala2/mdp/md_detail.mdp`, which is necessary for running the automated simulation script.</p> <p>- **`Ala2/7-adaptive-40ps/`**: Contains all simulation and analysis scripts, along with files required to replicate the study related to the automated pipeline.</p> <p>&nbsp; 1. **`Ala2/7-adaptive-40ps/CV/`**: Stores all COLVAR files from adaptive sampling simulations.<br>&nbsp;&nbsp;<br>&nbsp; 2. **`Ala2/7-adaptive-40ps/opes/`**: Contains all files related to OPES simulations, including raw data for the final FES plots found in `Ala2/7-adaptive-40ps/opes/COLVAR/`. The script for replicating OPES and FES estimation figures is located in `Ala2/7-adaptive-40ps/opes/COLVAR/analysis.ipynb`.<br>&nbsp;&nbsp;<br>&nbsp; 3. **`Ala2/7-adaptive-40ps/figures/`**: Includes all original figures from the main text and SI, saved at 600 dpi.<br>&nbsp;&nbsp;<br>&nbsp; 4. **`Ala2/7-adaptive-40ps/traj_and_dat/`**: Stores all PLUMED `*.dat` files for the `DRIVER` utility in adaptive sampling simulations, a topology file `input.pdb` for PLUMED `MOLINFO`, and a topology file `seed_ref.pdb` for MDAnalysis adaptive sampling seed `*.gro` generation. Note that all `*.xtc` files from adaptive sampling were deleted to reduce the package size.<br>&nbsp;&nbsp;<br>&nbsp; 5. **Seed Index Files:** Seed indices for each round are stored as `Ala2/7-adaptive-40ps/round{i}_seed.txt`, necessary for figure replication.<br>&nbsp;&nbsp;<br>&nbsp; 6. **Automated Pipeline Notebook:** Implemented in `Ala2/ala2.ipynb`. Ensure that all imported packages are installed and gromacs (both gmx and gmx_mpi)/plumed can be called within the Jupyter notebook.<br>&nbsp;&nbsp;<br>&nbsp; 7. **Adaptive Sampling Analysis:** Scripts for analyzing adaptive sampling trajectories are found in `Ala2/AdaptiveSamplingAnalysis.ipynb`. This notebook contains scripts to replicate all figures related to adaptive sampling.<br>&nbsp;&nbsp;<br>&nbsp; 8. **MSM Comparison:** Analysis scripts for MSM comparison are located in `Ala2/compare_with_msm.ipynb`. This notebook contains scripts to replicate figures used for MSM/OPES comparison.</p> <p>- **`Ala2/8-adaptive-400ps/`**: Contains all simulation files (except xtc) for an additional adaptive sampling dataset computed for MSM comparison.</p> <p>### Contact Information</p> <p>We are continuing to test and improve the pipeline, so a tutorial is not yet available. Please feel free to reach out with any questions related to the implementation via email at mingyuanzhang@zju.edu.cn or by raising an issue on our GitHub page: https://github.com/yongwangCPH/papers/tree/main/2024/ALICE.</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

MD simulations for "Molecular basis of neurosteroid and anticonvulsant regulation of TRPM3"

<p>MD simulations for the publication "<strong>&shy;&shy;&shy;</strong><strong>Molecular basis of neurosteroid and anticonvulsant regulation of TRPM3</strong>" in Nature Structural and Molecular Biology. Initial system setup (<em>step5_input.psf/crd</em>) and trajectories of the 4 simulation systems are provided, with each simulation system having 3 replicas (<em>rep0/1/2</em>). The assembly names mentioned in the publication and the corresponding alias are as follows:&nbsp;<br><br>1) TRPM3-PregS/CIM with CIM in pose I: "<em>trpm3-cim1</em>";<br>2) TRPM3-PregS/CIM with CIM in pose II: "<em>trpm3-cim2</em>";<br>3) TRPM3-CHS: "<em>trpm3-apo-chs</em>";<br>4) TRPM3-Cholesterol: "<em>trpm3-apo-chol</em>".&nbsp;&nbsp;</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

Input files for MD simulations of VP40 matrix protein dimer-dimer structure for WT, G198R, and G201R

<p>For AA simulations, the inp files need to have the path for the toppar folder and the corresponding pdb/psf files need to be renamed.</p>

opencc-by-4.0Aug 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record