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Stochastic Kinetics on Networks: When Slow Is Fast
[Image: see text] Most chemical and biological processes can be viewed as reaction networks in which different pathways often compete kinetically for transformation of substrates into products. An enzymatic process is an example of such phenomena when biological catalysts create new routes for chemi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154737/ https://www.ncbi.nlm.nih.gov/pubmed/25140607 http://dx.doi.org/10.1021/jp506668a |
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author | Li, Xin Kolomeisky, Anatoly B. Valleriani, Angelo |
author_facet | Li, Xin Kolomeisky, Anatoly B. Valleriani, Angelo |
author_sort | Li, Xin |
collection | PubMed |
description | [Image: see text] Most chemical and biological processes can be viewed as reaction networks in which different pathways often compete kinetically for transformation of substrates into products. An enzymatic process is an example of such phenomena when biological catalysts create new routes for chemical reactions to proceed. It is typically assumed that the general process of product formation is governed by the pathway with the fastest kinetics at all time scales. In contrast to the expectation, here we show theoretically that at time scales sufficiently short, reactions are predominantly determined by the shortest pathway (in the number of intermediate states), regardless of the average turnover time associated with each pathway. This universal phenomenon is demonstrated by an explicit calculation for a system with two competing reversible (or irreversible) pathways. The time scales that characterize this regime and its relevance for single-molecule experimental studies are also discussed. |
format | Online Article Text |
id | pubmed-4154737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-41547372015-08-20 Stochastic Kinetics on Networks: When Slow Is Fast Li, Xin Kolomeisky, Anatoly B. Valleriani, Angelo J Phys Chem B [Image: see text] Most chemical and biological processes can be viewed as reaction networks in which different pathways often compete kinetically for transformation of substrates into products. An enzymatic process is an example of such phenomena when biological catalysts create new routes for chemical reactions to proceed. It is typically assumed that the general process of product formation is governed by the pathway with the fastest kinetics at all time scales. In contrast to the expectation, here we show theoretically that at time scales sufficiently short, reactions are predominantly determined by the shortest pathway (in the number of intermediate states), regardless of the average turnover time associated with each pathway. This universal phenomenon is demonstrated by an explicit calculation for a system with two competing reversible (or irreversible) pathways. The time scales that characterize this regime and its relevance for single-molecule experimental studies are also discussed. American Chemical Society 2014-08-20 2014-09-04 /pmc/articles/PMC4154737/ /pubmed/25140607 http://dx.doi.org/10.1021/jp506668a Text en Copyright © 2014 American Chemical Society Terms of Use (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) |
spellingShingle | Li, Xin Kolomeisky, Anatoly B. Valleriani, Angelo Stochastic Kinetics on Networks: When Slow Is Fast |
title | Stochastic
Kinetics on Networks: When Slow Is Fast |
title_full | Stochastic
Kinetics on Networks: When Slow Is Fast |
title_fullStr | Stochastic
Kinetics on Networks: When Slow Is Fast |
title_full_unstemmed | Stochastic
Kinetics on Networks: When Slow Is Fast |
title_short | Stochastic
Kinetics on Networks: When Slow Is Fast |
title_sort | stochastic
kinetics on networks: when slow is fast |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154737/ https://www.ncbi.nlm.nih.gov/pubmed/25140607 http://dx.doi.org/10.1021/jp506668a |
work_keys_str_mv | AT lixin stochastickineticsonnetworkswhenslowisfast AT kolomeiskyanatolyb stochastickineticsonnetworkswhenslowisfast AT vallerianiangelo stochastickineticsonnetworkswhenslowisfast |