Data for Coarse-grained Intrinsically Disordered Proteins

Webb, Michael; Patel, Roshan; Borca, Carlos
Issue date: 6 May 2022
Cite as:
Webb, Michael, Patel, Roshan, & Borca, Carlos. (2022). Data for Coarse-grained Intrinsically Disordered Proteins [Data set]. Princeton University. https://doi.org/10.34770/chzn-mj42
@electronic{webb_michael_2022,
  author      = {Webb, Michael and
                Patel, Roshan and
                Borca, Carlos},
  title       = {{Data for Coarse-grained Intrinsically Di
                sordered Proteins}},
  publisher   = {{Princeton University}},
  year        = 2022,
  url         = {https://doi.org/10.34770/chzn-mj42}
}
Abstract:

This distribution compiles numerous physical properties for 2,585 intrinsically disordered proteins (IDPs) obtained by coarse-grained molecular dynamics simulation. This combination comprises "Dataset A" as reported in "Featurization strategies for polymer sequence or composition design by machine learning" by Roshan A. Patel, Carlos H. Borca, and Michael A. Webb (DOI: 10.1039/D1ME00160D). The specific IDP sequences are sourced from version 9.0 of the DisProt database. The simulations were performed using the LAMMPS molecular dynamics engine. The interactions used for simulation are obtained from R. M. Regy , J. Thompson , Y. C. Kim and J. Mittal , Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins, Protein Sci., 2021, 1371 —1379.

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# Filename Description Filesize
1 README 2.74 KB
2 dataset_a_encodings.csv 117 KB
3 dataset_a_labels.csv 92 KB
4 dataset_a_sequences.txt 670 KB
More about this record
Authors Webb, Michael
Patel, Roshan
Borca, Carlos
Communities Chemical and Biological Engineering
Collection Tags Research Data Sets
Date Accessioned 6 May 2022
Issue date 6 May 2022
Date Created 3 November 2021
URI http://arks.princeton.edu/ark:/88435/dsp01765374506
URI https://doi.org/10.34770/chzn-mj42
Table of Contents README, dataset_a_sequences.txt, dataset_a_encodings.csv, dataset_a_labels.csv
Referenced by https://doi.org/10.1039/D1ME00160D
Language en_US
Publisher Princeton University
Relation - Is Referenced By https://doi.org/10.1039/D1ME00160D
Rights CC BY NC ND 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
Type Dataset
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