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Theoretical Tools to Quantify Stochastic Fluctuations in Single-Molecule Catalysis by Enzymes and Nanoparticles
[Image: see text] Single-molecule microscopic techniques allow the counting of successive turnover events and the study of the time-dependent fluctuations of the catalytic activities of individual enzymes and different sites on a single heterogeneous nanocatalyst. It is important to establish theore...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798497/ https://www.ncbi.nlm.nih.gov/pubmed/36591158 http://dx.doi.org/10.1021/acsomega.2c06316 |
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author | Singh, Divya Punia, Bhawakshi Chaudhury, Srabanti |
author_facet | Singh, Divya Punia, Bhawakshi Chaudhury, Srabanti |
author_sort | Singh, Divya |
collection | PubMed |
description | [Image: see text] Single-molecule microscopic techniques allow the counting of successive turnover events and the study of the time-dependent fluctuations of the catalytic activities of individual enzymes and different sites on a single heterogeneous nanocatalyst. It is important to establish theoretical methods to obtain the statistical measurements of such stochastic fluctuations that provide insight into the catalytic mechanism. In this review, we discuss a few theoretical frameworks for evaluating the first passage time distribution functions using a self-consistent pathway approach and chemical master equations, to establish a connection with experimental observables. The measurable probability distribution functions and their moments depend on the molecular details of the reaction and provide a way to quantify the molecular mechanisms of the reaction process. The statistical measurements of these fluctuations should provide insight into the enzymatic mechanism. |
format | Online Article Text |
id | pubmed-9798497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-97984972022-12-30 Theoretical Tools to Quantify Stochastic Fluctuations in Single-Molecule Catalysis by Enzymes and Nanoparticles Singh, Divya Punia, Bhawakshi Chaudhury, Srabanti ACS Omega [Image: see text] Single-molecule microscopic techniques allow the counting of successive turnover events and the study of the time-dependent fluctuations of the catalytic activities of individual enzymes and different sites on a single heterogeneous nanocatalyst. It is important to establish theoretical methods to obtain the statistical measurements of such stochastic fluctuations that provide insight into the catalytic mechanism. In this review, we discuss a few theoretical frameworks for evaluating the first passage time distribution functions using a self-consistent pathway approach and chemical master equations, to establish a connection with experimental observables. The measurable probability distribution functions and their moments depend on the molecular details of the reaction and provide a way to quantify the molecular mechanisms of the reaction process. The statistical measurements of these fluctuations should provide insight into the enzymatic mechanism. American Chemical Society 2022-12-15 /pmc/articles/PMC9798497/ /pubmed/36591158 http://dx.doi.org/10.1021/acsomega.2c06316 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Singh, Divya Punia, Bhawakshi Chaudhury, Srabanti Theoretical Tools to Quantify Stochastic Fluctuations in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title | Theoretical Tools to Quantify Stochastic Fluctuations
in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title_full | Theoretical Tools to Quantify Stochastic Fluctuations
in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title_fullStr | Theoretical Tools to Quantify Stochastic Fluctuations
in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title_full_unstemmed | Theoretical Tools to Quantify Stochastic Fluctuations
in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title_short | Theoretical Tools to Quantify Stochastic Fluctuations
in Single-Molecule Catalysis by Enzymes and Nanoparticles |
title_sort | theoretical tools to quantify stochastic fluctuations
in single-molecule catalysis by enzymes and nanoparticles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798497/ https://www.ncbi.nlm.nih.gov/pubmed/36591158 http://dx.doi.org/10.1021/acsomega.2c06316 |
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