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CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability

The importance of the quantitative description of protein unfolding and aggregation for the rational design of stability or understanding the molecular basis of protein misfolding diseases is well established. Protein thermostability is typically assessed by calorimetric or spectroscopic techniques...

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Autores principales: Kunka, Antonin, Lacko, David, Stourac, Jan, Damborsky, Jiri, Prokop, Zbynek, Mazurenko, Stanislav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252748/
https://www.ncbi.nlm.nih.gov/pubmed/35580052
http://dx.doi.org/10.1093/nar/gkac378
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author Kunka, Antonin
Lacko, David
Stourac, Jan
Damborsky, Jiri
Prokop, Zbynek
Mazurenko, Stanislav
author_facet Kunka, Antonin
Lacko, David
Stourac, Jan
Damborsky, Jiri
Prokop, Zbynek
Mazurenko, Stanislav
author_sort Kunka, Antonin
collection PubMed
description The importance of the quantitative description of protein unfolding and aggregation for the rational design of stability or understanding the molecular basis of protein misfolding diseases is well established. Protein thermostability is typically assessed by calorimetric or spectroscopic techniques that monitor different complementary signals during unfolding. The CalFitter webserver has already proved integral to deriving invaluable energy parameters by global data analysis. Here, we introduce CalFitter 2.0, which newly incorporates singular value decomposition (SVD) of multi-wavelength spectral datasets into the global fitting pipeline. Processed time- or temperature-evolved SVD components can now be fitted together with other experimental data types. Moreover, deconvoluted basis spectra provide spectral fingerprints of relevant macrostates populated during unfolding, which greatly enriches the information gains of the CalFitter output. The SVD analysis is fully automated in a highly interactive module, providing access to the results to users without any prior knowledge of the underlying mathematics. Additionally, a novel data uploading wizard has been implemented to facilitate rapid and easy uploading of multiple datasets. Together, the newly introduced changes significantly improve the user experience, making this software a unique, robust, and interactive platform for the analysis of protein thermal denaturation data. The webserver is freely accessible at https://loschmidt.chemi.muni.cz/calfitter.
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spelling pubmed-92527482022-07-05 CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability Kunka, Antonin Lacko, David Stourac, Jan Damborsky, Jiri Prokop, Zbynek Mazurenko, Stanislav Nucleic Acids Res Web Server Issue The importance of the quantitative description of protein unfolding and aggregation for the rational design of stability or understanding the molecular basis of protein misfolding diseases is well established. Protein thermostability is typically assessed by calorimetric or spectroscopic techniques that monitor different complementary signals during unfolding. The CalFitter webserver has already proved integral to deriving invaluable energy parameters by global data analysis. Here, we introduce CalFitter 2.0, which newly incorporates singular value decomposition (SVD) of multi-wavelength spectral datasets into the global fitting pipeline. Processed time- or temperature-evolved SVD components can now be fitted together with other experimental data types. Moreover, deconvoluted basis spectra provide spectral fingerprints of relevant macrostates populated during unfolding, which greatly enriches the information gains of the CalFitter output. The SVD analysis is fully automated in a highly interactive module, providing access to the results to users without any prior knowledge of the underlying mathematics. Additionally, a novel data uploading wizard has been implemented to facilitate rapid and easy uploading of multiple datasets. Together, the newly introduced changes significantly improve the user experience, making this software a unique, robust, and interactive platform for the analysis of protein thermal denaturation data. The webserver is freely accessible at https://loschmidt.chemi.muni.cz/calfitter. Oxford University Press 2022-05-17 /pmc/articles/PMC9252748/ /pubmed/35580052 http://dx.doi.org/10.1093/nar/gkac378 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Kunka, Antonin
Lacko, David
Stourac, Jan
Damborsky, Jiri
Prokop, Zbynek
Mazurenko, Stanislav
CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title_full CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title_fullStr CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title_full_unstemmed CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title_short CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
title_sort calfitter 2.0: leveraging the power of singular value decomposition to analyse protein thermostability
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252748/
https://www.ncbi.nlm.nih.gov/pubmed/35580052
http://dx.doi.org/10.1093/nar/gkac378
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