Back

Kinetic Interval Measurement: A Tool to Characterize Thermal Reversion Dynamics of Light-switchable Fluorescent Proteins

von Trotha, T.; Johr, R.; Fischer, J.; Schendel, L. C.; Gaub, H. E.; Kluger, C.

2021-02-20 biophysics
10.1101/2021.02.20.432101 bioRxiv
Show abstract

Light-switchable proteins like Light-Oxygen-Voltage (LOV) domains can be used to control protein interactions and have been applied in vivo to manipulate cell behavior. The switching between dark and light state of LOV domains depends on temperature or their chemical microenvironment and can be tuned by point mutations. Here, we present a method called Kinetic Interval Measurement (KIM) to quantify the thermal reversion dynamics of light-switchable proteins by using a custom microplate reader. We show that this versatile method can be used to determine the reversion half-life of the excited state of LOV proteins in a reproducible, fast and simple manner consuming only small amounts of protein. The sensitivity of the method allows to report on changes in temperature and imidazole concentration as well as the photoswitching dynamics of LOV proteins in living cells.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Analytical Chemistry
● 218 papers in training set
Top 0.4%
8.5%
Similar papers in this journal
2
ACS Sensors
● 49 papers in training set
Top 0.1%
7.5%
Similar papers in this journal
3
Nature Communications
○ 5641 papers in training set
Top 26%
6.0%
Similar papers in this journal
4
Protein Science
○ 246 papers in training set
Top 0.8%
5.2%
5
Scientific Reports
○ 3612 papers in training set
Top 17%
5.2%
6
The Journal of Physical Chemistry B
● 167 papers in training set
Top 0.5%
5.2%
Similar papers in this journal
7
Biophysical Reports
○ 37 papers in training set
Top 0.1%
5.2%
Similar papers in this journal
8
Chemical Communications
● 25 papers in training set
Top 0.1%
4.1%
9
Nano Letters
● 71 papers in training set
Top 0.3%
3.9%
50% of probability mass above
10
Journal of the American Chemical Society
● 217 papers in training set
Top 1%
3.1%
11
Biophysical Journal
○ 631 papers in training set
Top 2%
3.1%
12
The Journal of Physical Chemistry Letters
● 63 papers in training set
Top 0.2%
3.0%
13
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 19%
2.7%
14
ChemBioChem
○ 55 papers in training set
Top 0.5%
2.3%
15
Communications Biology
○ 993 papers in training set
Top 12%
2.0%
16
ACS Nano
● 113 papers in training set
Top 1%
2.0%
17
The FEBS Journal
○ 93 papers in training set
Top 0.6%
1.8%
18
JACS Au
● 43 papers in training set
Top 0.4%
1.6%
19
Biochemistry
● 148 papers in training set
Top 2%
1.4%
20
ACS Synthetic Biology
● 287 papers in training set
Top 2%
1.3%
21
Chemical Science
● 73 papers in training set
Top 1%
1.1%
22
ACS Photonics
● 13 papers in training set
Top 0.2%
1.0%
23
Journal of Biological Chemistry
○ 690 papers in training set
Top 8%
1.0%
24
iScience
○ 1154 papers in training set
Top 33%
0.9%
25
Nanoscale
● 42 papers in training set
Top 0.7%
0.9%
26
ACS Chemical Biology
● 167 papers in training set
Top 2%
0.9%
27
SLAS Discovery
○ 25 papers in training set
Top 0.3%
0.8%
28
Advanced Biology
○ 29 papers in training set
Top 0.9%
0.8%
29
PLOS ONE
● 5266 papers in training set
Top 61%
0.8%
30
RSC Chemical Biology
● 39 papers in training set
Top 0.9%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.