Molecular Dynamics Simulation Data of FAT10

DOI

This data set contains molecular dynamics simulations of the ubiquitin-like signaling protein FAT10 (Ubiquitin-D). It is composed of 150 simulation trajectories with 200 ns simulated time and a time interval between frames of of 100ps. The dataset contains three replicates of 50 different simulation conditions - 2 different ion concentrations and 25 different starting conformations. The ion conditions are "no NaCl" and "150 mM NaCl". The starting conformations were generated by rotating the Phi-angle of residue Asp85 by 360° in 25 steps. This angle in the flexible linker of FAT10 modifies the relative orientation of its two ubiquitin-like domains. The simulations were performed using the GROMACS simulation package version 2018, 2020 and 2021 and the GROMOS96 54/A7 force field. This dataset accompanies a publication which proposes a clustering framework for the applying of network formalisms to flexible protein systems (analysis code available under: https://github.com/AG-Peter/Clustering_Networks, publication available under: https://doi.org/10.1021/acs.jcim.5c01298 ). Please cite this work if you are using the dataset in a publication.

Identifier
DOI https://doi.org/10.48606/gx4q9ureeuzxsndv
Related Identifier IsSupplementTo https://doi.org/10.1021/acs.jcim.5c01298
Related Identifier IsSupplementedBy https://github.com/AG-Peter/Clustering_Networks
Metadata Access https://www.radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=datacite&identifier=10.48606/gx4q9ureeuzxsndv
Provenance
Creator Franke, Leon (ORCID: 0000-0002-8877-438X)
Publisher University of Konstanz
Contributor RADAR
Publication Year 2025
Funding Reference Deutsche Forschungsgemeinschaft https://ror.org/018mejw64 ROR INST 37/935-1 FUGG ; Deutsche Forschungsgemeinschaft https://ror.org/018mejw64 ROR INST 35/1134-1 FUGG
Rights Open Access; Creative Commons Attribution 4.0 International; info:eu-repo/semantics/openAccess; https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Representation
Language English
Resource Type MD Simulations; Dataset
Format application/x-tar
Discipline Chemistry; Natural Sciences
Temporal Coverage 2020-2023