Glassy dynamics and memory effects in an intrinsically disordered protein construct
Cite this dataset
Morgan, Ian et al. (2021). Glassy dynamics and memory effects in an intrinsically disordered protein construct [Dataset]. Dryad. https://doi.org/10.25349/D9RC86
Abstract
Glassy, nonexponential relaxations in globular proteins are typically attributed to conformational behaviors that are missing from intrinsically disordered proteins. Yet, we show that single molecules of a disordered-protein construct display two signatures of glassy dynamics, logarithmic relaxations and a Kovacs memory effect, in response to changes in applied tension. We attribute this to the presence of multiple independent local structures in the chain, which we corroborate with a model that correctly predicts the force-dependence of the relaxation. The mechanism established here likely applies to other disordered proteins.
Methods
The data were collected using a custom-built magnetic tweezer as described in Ribeck et al. (2008) https://doi.org/10.1063/1.2981687. The force on each polymer was determined as described in Lansdorp et al. (2012) https://doi.org/10.1063/1.3687431.
Usage notes
GENERAL INFORMATION
1. Title of Dataset: Glassy dynamics in an IDP constuct dataset
2. Author Information
A. Researcher Contact Information
Name: Ian L. Morgan
Institution: University of California, Santa Barbara
Email: ilmorgan@ucsb.edu
B. Principal Investigator Contact Information
Name: Omar A. Saleh
Institution: University of California, Santa Barbara
Email: saleh@ucsb.edu
3. Information about funding sources that supported the collection of the data:
This work was supported by the National Science Foundation under Award 1715627.
METHODOLOGICAL INFORMATION
1. Description of methods used for collection/generation of data:
The data were collected using a custom-built magnetic tweezer as described in Ribeck et al. (2008) https://doi.org/10.1063/1.2981687. The force on each polymer was determined as described in Lansdorp et al. (2012) https://doi.org/10.1063/1.3687431.
2. Instrument- or software-specific information needed to interpret the data:
Data were analyzed using python 3.7 with the following packages:
numpy
scipy
pandas
matplotlib
pathlib
uncertainties
re
os
datetime
3. Environmental/experimental conditions:
All data were collected at T = 20 C in a 20mM pH 7 MES buffer with 10mM NaCl and 0.05% Tween-20.
FOLDERS/FILES
data
Relaxationddata_04_20_20
supp_kovacs_data
Fig1cdata.csv
Fig2bdata.csv
Relaxationfits_04-20-2020.csv
Fig3data_04-22-2020.csv
Fig3_bootstrap_results_04-20-2020
WLC_FJC_elasticity_fits_04-27-2020
analysis
Fig3_bootstrap.py
Fig3data.py
fit_relaxations.py
WLC-FJC_elasticity_fits.py
functions
__init__.py
fitting.py
utilities.py
plotting
__init__.py
default.mplstyle
Fig1c_plot.py
Fig2b_plot.py
Fig3_plot.py
Fig3_inset_plot.py
SIFig7_scaling_plot.py
DATA-SPECIFIC INFORMATION FOR: Relaxationdata_04_20_20
Files:
NFL_logrelax_polyx.csv
where x denotes the polymer number from 0-15
Description:
Relaxation data for 16 polymers at high force (f1) and low force (f2)
Variables:
relaxation - index marking each seperate trace
time_s - time in seconds since reaching constant force
mp_mm - magnetic position in mms
length_nm - polymer length in nms
f_pN - force in pN on polymer/bead
DATA-SPECIFIC INFORMATION FOR: supp_kovacs_data
Files:
NFL_kovacs_forces.csv
NFL_kovacs_polyx.csv
where x denotes the polymer number from 0-7
Description:
Supplementary kovacs data for 8 polymers at intermediate force (f3)
Variables:
NFL_kovacs_forces.csv
polymer - index indicating the polymer
f1_pN - high force (f1) value
f2_pN - low force (f2) value
f3_pN - intermediate force (f2) value
NFL_kovacs_polyx.csv
time_s - time in seconds since reaching constant force
length_nm - polymer length in nms
DATA-SPECIFIC INFORMATION FOR: Fig1cdata.csv
Description:
Example relaxation data at various quench (f2) forces
Variables:
time_s - time in seconds since reaching constant force
length_um - polymer length in microns
DATA-SPECIFIC INFORMATION FOR: Fig2bdata.csv
Description:
Example kovacs data at intermediate (f3) force
Variables:
time_s - time in seconds since reaching constant force
length_um - polymer length in microns
FILE-SPECIFIC INFORMATION FOR: Fig3_bootstrap.py
Description:
Bootstraps fits for Fig3 data (normalized w/ worm-like chain elasticity)
by polymer
FILE-SPECIFIC INFORMATION FOR: Fig3data.py
Description:
Loads logarithmic fits of relaxation data and calculates information
for Fig. 3 data, e.g., fbar and bbar. Outputs Fig3data_x.csv file
with x as the current date
FILE-SPECIFIC INFORMATION FOR: fit_relaxations.py
Description:
Performs logarithmic fits of relaxation data and outputs
Relaxationfits_x.csv with x as current date.
FILE-SPECIFIC INFORMATION FOR: WLC-FJC_elasticity_fits.py
Description:
Performs bbar normalization with a more nuanced model that accounts for
the elasticity of both the coil and structured state.
Outputs WLC_FJC_elasticity_fits_x.csv with x as current date.
FOLDER-SPECIFIC INFORMATION FOR: fitting
Description:
Includes the scripts and style file to produce the major plots in the paper.
Funding
National Science Foundation, Award: 1715627