Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches

Abstract Metabolic pathway modeling plays an increasing role in drug design by allowing better understanding of the underlying regulation and controlling networks in the metabolism of living organisms. However, despite rapid progress in this area, pathway modeling can become a real nightmare for res...

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Autores principales:	Ophélie Lo-Thong, Philippe Charton, Xavier F. Cadet, Brigitte Grondin-Perez, Emma Saavedra, Cédric Damour, Frédéric Cadet
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3a136d7e4cb74fb8882a1b9f52cfe5f0
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spelling	oai:doaj.org-article:3a136d7e4cb74fb8882a1b9f52cfe5f02021-12-02T16:43:42ZIdentification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches10.1038/s41598-020-70295-52045-2322https://doaj.org/article/3a136d7e4cb74fb8882a1b9f52cfe5f02020-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-70295-5https://doaj.org/toc/2045-2322Abstract Metabolic pathway modeling plays an increasing role in drug design by allowing better understanding of the underlying regulation and controlling networks in the metabolism of living organisms. However, despite rapid progress in this area, pathway modeling can become a real nightmare for researchers, notably when few experimental data are available or when the pathway is highly complex. Here, three different approaches were developed to model the second part of glycolysis of E. histolytica as an application example, and have succeeded in predicting the final pathway flux: one including detailed kinetic information (white-box), another with an added adjustment term (grey-box) and the last one using an artificial neural network method (black-box). Afterwards, each model was used for metabolic control analysis and flux control coefficient determination. The first two enzymes of this pathway are identified as the key enzymes playing a role in flux control. This study revealed the significance of the three methods for building suitable models adjusted to the available data in the field of metabolic pathway modeling, and could be useful to biologists and modelers.Ophélie Lo-ThongPhilippe ChartonXavier F. CadetBrigitte Grondin-PerezEmma SaavedraCédric DamourFrédéric CadetNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-19 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ophélie Lo-Thong Philippe Charton Xavier F. Cadet Brigitte Grondin-Perez Emma Saavedra Cédric Damour Frédéric Cadet Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
description	Abstract Metabolic pathway modeling plays an increasing role in drug design by allowing better understanding of the underlying regulation and controlling networks in the metabolism of living organisms. However, despite rapid progress in this area, pathway modeling can become a real nightmare for researchers, notably when few experimental data are available or when the pathway is highly complex. Here, three different approaches were developed to model the second part of glycolysis of E. histolytica as an application example, and have succeeded in predicting the final pathway flux: one including detailed kinetic information (white-box), another with an added adjustment term (grey-box) and the last one using an artificial neural network method (black-box). Afterwards, each model was used for metabolic control analysis and flux control coefficient determination. The first two enzymes of this pathway are identified as the key enzymes playing a role in flux control. This study revealed the significance of the three methods for building suitable models adjusted to the available data in the field of metabolic pathway modeling, and could be useful to biologists and modelers.
format	article
author	Ophélie Lo-Thong Philippe Charton Xavier F. Cadet Brigitte Grondin-Perez Emma Saavedra Cédric Damour Frédéric Cadet
author_facet	Ophélie Lo-Thong Philippe Charton Xavier F. Cadet Brigitte Grondin-Perez Emma Saavedra Cédric Damour Frédéric Cadet
author_sort	Ophélie Lo-Thong
title	Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
title_short	Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
title_full	Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
title_fullStr	Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
title_full_unstemmed	Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
title_sort	identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/3a136d7e4cb74fb8882a1b9f52cfe5f0
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Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches

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