Cargando…

KinMod database: a tool for investigating metabolic regulation

The ability of current kinetic models to simulate the phenotypic behaviour of cells is limited since cell metabolism is regulated at different levels including enzyme regulation. The small molecule regulation network (SMRN) enables cells to respond rapidly to environmental fluctuations by controllin...

Descripción completa

Detalles Bibliográficos
Autores principales: Haddadi, Kiandokht, Ahmed Barghout, Rana, Mahadevan, Radhakrishnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554645/
https://www.ncbi.nlm.nih.gov/pubmed/36222201
http://dx.doi.org/10.1093/database/baac081
_version_ 1784806745691914240
author Haddadi, Kiandokht
Ahmed Barghout, Rana
Mahadevan, Radhakrishnan
author_facet Haddadi, Kiandokht
Ahmed Barghout, Rana
Mahadevan, Radhakrishnan
author_sort Haddadi, Kiandokht
collection PubMed
description The ability of current kinetic models to simulate the phenotypic behaviour of cells is limited since cell metabolism is regulated at different levels including enzyme regulation. The small molecule regulation network (SMRN) enables cells to respond rapidly to environmental fluctuations by controlling the activity of enzymes in metabolic pathways. However, SMRN is not as well studied relative to metabolic networks. The main contributor to the lack of knowledge on this regulatory system is the sparsity of experimental data and the absence of a standard framework for representing available information. In this paper, we introduce the KinMod database that encompasses more than 2 million data points on the metabolism and metabolic regulation network of 9814 organisms KinMod database employs a hierarchical data structure to: (i) signify relationships between kinetic information obtained through in-vitro experiments and proteins, with an emphasis on SMRN, (ii) provide a thorough insight into available kinetic parameters and missing experimental measurements of this regulatory network and (iii) facilitate machine learning approaches for parameter estimation and accurate kinetic model construction by providing a homogeneous list of linked omics data. The hierarchical ontology of the KinMod database allows flexible exploration of data attributes and investigation of metabolic relationships within- and cross-species. Identifying missing experimental values suggests additional experiments required for kinetic parameter estimation. Linking multi-omics data and providing data on SMRN encourages the development of novel machine learning techniques for predicting missing kinetic parameters and promotes accurate kinetic model construction of cells metabolism by providing a comprehensive list of available kinetic measurements. To illustrate the value of KinMod data, we develop six analyses to visualize associations between data classes belonging to separate sections of the metabolism. Through these analyses, we demonstrate that the KinMod database provides a unique framework for biologists and engineers to retrieve, evaluate and compare the functional metabolism of species, including the regulatory network, and discover the extent of available and missing experimental values of the metabolic regulation. Database URL: https://lmse.utoronto.ca/kinmod/KINMOD.sql.gz
format Online
Article
Text
id pubmed-9554645
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-95546452022-10-12 KinMod database: a tool for investigating metabolic regulation Haddadi, Kiandokht Ahmed Barghout, Rana Mahadevan, Radhakrishnan Database (Oxford) Original Article The ability of current kinetic models to simulate the phenotypic behaviour of cells is limited since cell metabolism is regulated at different levels including enzyme regulation. The small molecule regulation network (SMRN) enables cells to respond rapidly to environmental fluctuations by controlling the activity of enzymes in metabolic pathways. However, SMRN is not as well studied relative to metabolic networks. The main contributor to the lack of knowledge on this regulatory system is the sparsity of experimental data and the absence of a standard framework for representing available information. In this paper, we introduce the KinMod database that encompasses more than 2 million data points on the metabolism and metabolic regulation network of 9814 organisms KinMod database employs a hierarchical data structure to: (i) signify relationships between kinetic information obtained through in-vitro experiments and proteins, with an emphasis on SMRN, (ii) provide a thorough insight into available kinetic parameters and missing experimental measurements of this regulatory network and (iii) facilitate machine learning approaches for parameter estimation and accurate kinetic model construction by providing a homogeneous list of linked omics data. The hierarchical ontology of the KinMod database allows flexible exploration of data attributes and investigation of metabolic relationships within- and cross-species. Identifying missing experimental values suggests additional experiments required for kinetic parameter estimation. Linking multi-omics data and providing data on SMRN encourages the development of novel machine learning techniques for predicting missing kinetic parameters and promotes accurate kinetic model construction of cells metabolism by providing a comprehensive list of available kinetic measurements. To illustrate the value of KinMod data, we develop six analyses to visualize associations between data classes belonging to separate sections of the metabolism. Through these analyses, we demonstrate that the KinMod database provides a unique framework for biologists and engineers to retrieve, evaluate and compare the functional metabolism of species, including the regulatory network, and discover the extent of available and missing experimental values of the metabolic regulation. Database URL: https://lmse.utoronto.ca/kinmod/KINMOD.sql.gz Oxford University Press 2022-10-12 /pmc/articles/PMC9554645/ /pubmed/36222201 http://dx.doi.org/10.1093/database/baac081 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Haddadi, Kiandokht
Ahmed Barghout, Rana
Mahadevan, Radhakrishnan
KinMod database: a tool for investigating metabolic regulation
title KinMod database: a tool for investigating metabolic regulation
title_full KinMod database: a tool for investigating metabolic regulation
title_fullStr KinMod database: a tool for investigating metabolic regulation
title_full_unstemmed KinMod database: a tool for investigating metabolic regulation
title_short KinMod database: a tool for investigating metabolic regulation
title_sort kinmod database: a tool for investigating metabolic regulation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554645/
https://www.ncbi.nlm.nih.gov/pubmed/36222201
http://dx.doi.org/10.1093/database/baac081
work_keys_str_mv AT haddadikiandokht kinmoddatabaseatoolforinvestigatingmetabolicregulation
AT ahmedbarghoutrana kinmoddatabaseatoolforinvestigatingmetabolicregulation
AT mahadevanradhakrishnan kinmoddatabaseatoolforinvestigatingmetabolicregulation