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Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks
[Image: see text] Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047803/ https://www.ncbi.nlm.nih.gov/pubmed/33780250 http://dx.doi.org/10.1021/acs.jctc.0c01308 |
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author | Motta, Stefano Pandini, Alessandro Fornili, Arianna Bonati, Laura |
author_facet | Motta, Stefano Pandini, Alessandro Fornili, Arianna Bonati, Laura |
author_sort | Motta, Stefano |
collection | PubMed |
description | [Image: see text] Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM) revealed two distinct pathways for the mechanical unfolding of the ARNT PAS-B. In this work we used steered molecular dynamics simulations to gain new insights into this process at an atomistic level. To reconstruct and classify pathways sampled in multiple simulations, we designed an original approach based on the use of self-organizing maps (SOMs). This led us to identify two types of unfolding pathways for the ARNT PAS-B, which are in good agreement with the AFM findings. Analysis of average forces mapped on the SOM revealed a stable conformation of the PAS-B along one pathway, which represents a possible structural model for the intermediate state detected by AFM. The approach here proposed will facilitate the study of other signal transmission mechanisms involving the folding/unfolding of PAS domains. |
format | Online Article Text |
id | pubmed-8047803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-80478032021-04-16 Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks Motta, Stefano Pandini, Alessandro Fornili, Arianna Bonati, Laura J Chem Theory Comput [Image: see text] Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molecule atomic force microscopy (AFM) revealed two distinct pathways for the mechanical unfolding of the ARNT PAS-B. In this work we used steered molecular dynamics simulations to gain new insights into this process at an atomistic level. To reconstruct and classify pathways sampled in multiple simulations, we designed an original approach based on the use of self-organizing maps (SOMs). This led us to identify two types of unfolding pathways for the ARNT PAS-B, which are in good agreement with the AFM findings. Analysis of average forces mapped on the SOM revealed a stable conformation of the PAS-B along one pathway, which represents a possible structural model for the intermediate state detected by AFM. The approach here proposed will facilitate the study of other signal transmission mechanisms involving the folding/unfolding of PAS domains. American Chemical Society 2021-03-29 2021-04-13 /pmc/articles/PMC8047803/ /pubmed/33780250 http://dx.doi.org/10.1021/acs.jctc.0c01308 Text en © 2021 The Authors. Published by American Chemical Society Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Motta, Stefano Pandini, Alessandro Fornili, Arianna Bonati, Laura Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks |
title | Reconstruction of ARNT PAS-B Unfolding Pathways
by Steered Molecular Dynamics and Artificial Neural Networks |
title_full | Reconstruction of ARNT PAS-B Unfolding Pathways
by Steered Molecular Dynamics and Artificial Neural Networks |
title_fullStr | Reconstruction of ARNT PAS-B Unfolding Pathways
by Steered Molecular Dynamics and Artificial Neural Networks |
title_full_unstemmed | Reconstruction of ARNT PAS-B Unfolding Pathways
by Steered Molecular Dynamics and Artificial Neural Networks |
title_short | Reconstruction of ARNT PAS-B Unfolding Pathways
by Steered Molecular Dynamics and Artificial Neural Networks |
title_sort | reconstruction of arnt pas-b unfolding pathways
by steered molecular dynamics and artificial neural networks |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047803/ https://www.ncbi.nlm.nih.gov/pubmed/33780250 http://dx.doi.org/10.1021/acs.jctc.0c01308 |
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