Table · dataset · 2025
Computational and experimental reference data: Molecular dynamics of the intrinsically disordered protein COR15A – A force field validation on structure and dynamics
Listed in Edmond
This dataset includes the computational and experimental data for the publication: "Molecular Dynamics of the Intrinsically Disordered Protein COR15A – A Force Field Validation on Structure and Dynamics".
Description
We provide the simulation trajectory files and the corresponding scripts for system set-up, MD prodcution runs and analysis of results. REMARK: For better overview, you can switch to "Tree view" in the "Files section": Files > Change View > Tree ABSTRACT: Intrinsically disordered proteins (IDPs) pose a challenge for structural characterization, as experimental methods lack the subnanometer/sub-nanosecond resolution to capture their dynamic conformational ensembles.
Molecular dynamics (MD) simulations can, in principle, provide this information, but for the simulation of IDPs dedicated protein and water force fields are needed, as traditional MD models for folded proteins prove inadequate for IDPs. Substantial effort was invested to develop IDP-specific force fields, but their per- formance in describing IDPs that undergo conformational changes—such as those induced by molecular partner binding or changes in solution environment—remains underexplored.
Read the rest (3 more)
In this study, we investigated the ability of 20 MD models to accurately simulate structural and dynamic aspects of COR15A, an IDP just on the verge of folding, with a particular focus on their ability to capture subtle structural differences. We employ a two-step approach: (i) validation of short 200 ns simulations against small-angle X-ray scattering (SAXS) data, and (ii) detailed evaluation of the six best-performing MD models through extended 1.2 μs MD simulations against nuclear magnetic resonance (NMR) data, including a single-point mutant with slightly increased helicity.
Only DES-amber and ff99SBws capture helicity differences between wild-type and mutant, but ff99SBws overestimates helicity. Notably, only DES-amber adequately reproduces the COR15A dynamics, as assessed by NMR relaxation times at two different magnetic field strengths. Among the tested force fields, DES-amber emerges as the best MD model for the simulation of COR15A.
Its application provides insights into its dynamic conformational landscape, albeit not perfectly reproducing all experimental data. Our study highlights the need for rigorous force field validation for IDPs, and identifies remaining discrepancies in need of fur ther force-field development.
Links
Where it is published
- Dataverse dataset page edmond.mpg.de/dataset.xhtml?persistentId=doi%3A10.17617%2F3.4I538Z ↗
landing page · from edmond mpdl mpg de
- DOI doi.org/10.17617/3.4i538z ↗
DOI / persistent id · from edmond mpdl mpg de
Catalogue records · 1
- Dataverse API edmond.mpg.de/api/datasets/:persistentId/?persistentId=doi%3A10.17617%2F3.4I… ↗
metadata API · from edmond mpdl mpg de
Topics
- Stated by source
- Biology · Biology · Chemistry · Chemistry · Computer Science, Systems and Electrical Engineering · Computer Science, Systems and Electrical Engineering
- From keywords
- Astronomy & Astrophysics · Chemistry · Chemistry · Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Engineering · Humanities · Life Sciences · Life Sciences · Materials Science · Medicine & Health · Ocean & Atmospheric Science · Physics · Social Science
- Inferred from text
- Magnetic resonance imaging 65% · Medicinal and biomolecular chemistry 75% · Simulation 75%
Provenance · 2 source records, 32 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Edmond | doi:10.17617/3.4I538Z | 8 d ago | JSON v1 |
| Edmond | doi:10.17617/3.4I538Z | 7 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3404 | enrichment · edmond mpdl mpg de | taxonomy-embedding@1.0.0 | title+keywords+description (75%) |
| concepts[field].dataverse_subject:biology | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:biology | source · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:chemistry | source · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:chemistry | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:computer-science-systems-and-electrical-engineering | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:computer-science-systems-and-electrical-engineering | source · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:astronomy | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:materials-science | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:physics | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · edmond mpg de | connector:edmond_mpg_de@1.0.0 | /subjects |
| concepts[method].local:method:simulation | enrichment · edmond mpdl mpg de | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:mri | enrichment · edmond mpdl mpg de | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | |
| description | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /description |
| publication_date | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | |
| title | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | /name |
| updated_date | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 | |
| version_label | source · edmond mpdl mpg de | connector:edmond_mpdl_mpg_de@1.0.0 |