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Quantifying the two-state facilitated diffusion model of protein–DNA interactions

The current report extends the facilitated diffusion model to account for conflict between the search and recognition binding modes adopted by DNA-binding proteins (DBPs) as they search DNA and subsequently recognize and bind to their specific binding site. The speed of the search dynamics is govern...

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Autores principales: Leven, Itai, Levy, Yaakov
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582340/
https://www.ncbi.nlm.nih.gov/pubmed/31045207
http://dx.doi.org/10.1093/nar/gkz308
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author Leven, Itai
Levy, Yaakov
author_facet Leven, Itai
Levy, Yaakov
author_sort Leven, Itai
collection PubMed
description The current report extends the facilitated diffusion model to account for conflict between the search and recognition binding modes adopted by DNA-binding proteins (DBPs) as they search DNA and subsequently recognize and bind to their specific binding site. The speed of the search dynamics is governed by the energetic ruggedness of the protein–DNA landscape, whereas the rate for the recognition process is mostly dictated by the free energy barrier for the transition between the DBP’s search and recognition binding modes. We show that these two modes are negatively coupled, such that fast 1D sliding and rapid target site recognition probabilities are unlikely to coexist. Thus, a tradeoff occurs between optimizing the timescales for finding and binding the target site. We find that these two kinetic properties can be balanced to produce a fast timescale for the total target search and recognition process by optimizing frustration. Quantification of the facilitated diffusion model by including a frustration term enables it to explain several experimental observations concerning search and recognition speeds. The extended model captures experimental estimate of the energetic ruggedness of the protein–DNA landscape and predicts how various molecular properties of protein–DNA binding affect recognition kinetics. Particularly, point mutations may change the frustration and so affect protein association with DNA, thus providing a means to modulate protein–DNA affinity by manipulating the protein’s association or dissociation reactions.
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spelling pubmed-65823402019-06-21 Quantifying the two-state facilitated diffusion model of protein–DNA interactions Leven, Itai Levy, Yaakov Nucleic Acids Res Computational Biology The current report extends the facilitated diffusion model to account for conflict between the search and recognition binding modes adopted by DNA-binding proteins (DBPs) as they search DNA and subsequently recognize and bind to their specific binding site. The speed of the search dynamics is governed by the energetic ruggedness of the protein–DNA landscape, whereas the rate for the recognition process is mostly dictated by the free energy barrier for the transition between the DBP’s search and recognition binding modes. We show that these two modes are negatively coupled, such that fast 1D sliding and rapid target site recognition probabilities are unlikely to coexist. Thus, a tradeoff occurs between optimizing the timescales for finding and binding the target site. We find that these two kinetic properties can be balanced to produce a fast timescale for the total target search and recognition process by optimizing frustration. Quantification of the facilitated diffusion model by including a frustration term enables it to explain several experimental observations concerning search and recognition speeds. The extended model captures experimental estimate of the energetic ruggedness of the protein–DNA landscape and predicts how various molecular properties of protein–DNA binding affect recognition kinetics. Particularly, point mutations may change the frustration and so affect protein association with DNA, thus providing a means to modulate protein–DNA affinity by manipulating the protein’s association or dissociation reactions. Oxford University Press 2019-06-20 2019-05-02 /pmc/articles/PMC6582340/ /pubmed/31045207 http://dx.doi.org/10.1093/nar/gkz308 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Leven, Itai
Levy, Yaakov
Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title_full Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title_fullStr Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title_full_unstemmed Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title_short Quantifying the two-state facilitated diffusion model of protein–DNA interactions
title_sort quantifying the two-state facilitated diffusion model of protein–dna interactions
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582340/
https://www.ncbi.nlm.nih.gov/pubmed/31045207
http://dx.doi.org/10.1093/nar/gkz308
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