Error-based extraction of states and energy landscapes from experimental single-molecule time-series

Scientific Reports
J Nicholas TaylorTamiki Komatsuzaki

Abstract

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. Here we present a method to extract the underlying state sequences from experimental SM time-series. Taking into account empirical error and the finite sampling of the time-series, the method extracts a steady-state network which provides an approximation of the underlying effective free energy landscape. The core of the method is the application of rate-distortion theory from information theory, allowing the individual data points to be assigned to multiple states simultaneously. We demonstrate the method's proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system.

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Citations

Dec 22, 2015·Current Opinion in Structural Biology·Satoshi TakahashiHiroyuki Oikawa
Dec 8, 2015·The Journal of Physical Chemistry. B·Yutaka NagahataTamiki Komatsuzaki
Jul 6, 2016·The Journal of Physical Chemistry. B·Jixin ChenChristy F Landes
Apr 2, 2018·The Journal of Chemical Physics·J Nicholas TaylorTamiki Komatsuzaki
Dec 19, 2015·Nature Communications·Chun-Biu LiTamiki Komatsuzaki
Jan 3, 2018·Physical Chemistry Chemical Physics : PCCP·Yuji TamiyaTamiki Komatsuzaki
Jun 30, 2019·FEBS Letters·Khalifa Mohammad HelalTamiki Komatsuzaki
May 1, 2019·The Journal of Physical Chemistry. B·J Nicholas TaylorTamiki Komatsuzaki
Dec 13, 2018·The Journal of Physical Chemistry. B·Sudeshna ChatterjeeChristy F Landes

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Methods Mentioned

BETA
FRET

Software Mentioned

SCISM
TRDG

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