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Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states

Allosteric modulation provides an effective avenue for selective and potent enzyme inhibition. Here, we summarize and critically discuss recent advances on the mechanisms of allosteric partial agonists for three representative signalling enzymes activated by cyclic nucleotides: the cAMP-dependent pr...

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Autores principales: Byun, Jung Ah, VanSchouwen, Bryan, Akimoto, Madoka, Melacini, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720024/
https://www.ncbi.nlm.nih.gov/pubmed/33335680
http://dx.doi.org/10.1016/j.csbj.2020.10.026
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author Byun, Jung Ah
VanSchouwen, Bryan
Akimoto, Madoka
Melacini, Giuseppe
author_facet Byun, Jung Ah
VanSchouwen, Bryan
Akimoto, Madoka
Melacini, Giuseppe
author_sort Byun, Jung Ah
collection PubMed
description Allosteric modulation provides an effective avenue for selective and potent enzyme inhibition. Here, we summarize and critically discuss recent advances on the mechanisms of allosteric partial agonists for three representative signalling enzymes activated by cyclic nucleotides: the cAMP-dependent protein kinase (PKA), the cGMP-dependent protein kinase (PKG), and the exchange protein activated by cAMP (EPAC). The comparative analysis of partial agonism in PKA, PKG and EPAC reveals a common emerging theme, i.e. the sampling of distinct “mixed” conformational states, either within a single domain or between distinct domains. Here, we show how such “mixed” states play a crucial role in explaining the observed functional response, i.e. partial agonism and allosteric pluripotency, as well as in maximizing inhibition while minimizing potency losses. In addition, by combining Nuclear Magnetic Resonance (NMR), Molecular Dynamics (MD) simulations and Ensemble Allosteric Modeling (EAM), we also show how to map the free-energy landscape of conformational ensembles containing “mixed” states. By discussing selected case studies, we illustrate how MD simulations and EAM complement NMR to quantitatively relate protein dynamics to function. The resulting NMR- and MD-based EAMs are anticipated to inform not only the design of new generations of highly selective allosteric inhibitors, but also the choice of multidrug combinations.
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spelling pubmed-77200242020-12-16 Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states Byun, Jung Ah VanSchouwen, Bryan Akimoto, Madoka Melacini, Giuseppe Comput Struct Biotechnol J Review Allosteric modulation provides an effective avenue for selective and potent enzyme inhibition. Here, we summarize and critically discuss recent advances on the mechanisms of allosteric partial agonists for three representative signalling enzymes activated by cyclic nucleotides: the cAMP-dependent protein kinase (PKA), the cGMP-dependent protein kinase (PKG), and the exchange protein activated by cAMP (EPAC). The comparative analysis of partial agonism in PKA, PKG and EPAC reveals a common emerging theme, i.e. the sampling of distinct “mixed” conformational states, either within a single domain or between distinct domains. Here, we show how such “mixed” states play a crucial role in explaining the observed functional response, i.e. partial agonism and allosteric pluripotency, as well as in maximizing inhibition while minimizing potency losses. In addition, by combining Nuclear Magnetic Resonance (NMR), Molecular Dynamics (MD) simulations and Ensemble Allosteric Modeling (EAM), we also show how to map the free-energy landscape of conformational ensembles containing “mixed” states. By discussing selected case studies, we illustrate how MD simulations and EAM complement NMR to quantitatively relate protein dynamics to function. The resulting NMR- and MD-based EAMs are anticipated to inform not only the design of new generations of highly selective allosteric inhibitors, but also the choice of multidrug combinations. Research Network of Computational and Structural Biotechnology 2020-11-11 /pmc/articles/PMC7720024/ /pubmed/33335680 http://dx.doi.org/10.1016/j.csbj.2020.10.026 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Byun, Jung Ah
VanSchouwen, Bryan
Akimoto, Madoka
Melacini, Giuseppe
Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title_full Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title_fullStr Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title_full_unstemmed Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title_short Allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
title_sort allosteric inhibition explained through conformational ensembles sampling distinct “mixed” states
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720024/
https://www.ncbi.nlm.nih.gov/pubmed/33335680
http://dx.doi.org/10.1016/j.csbj.2020.10.026
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