Přehled o publikaci
2022
CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
KUNKA, Antonín; David LACKO; Jan ŠTOURAČ; Jiří DAMBORSKÝ; Zbyněk PROKOP et al.Basic information
Original name
CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability
Authors
KUNKA, Antonín; David LACKO; Jan ŠTOURAČ; Jiří DAMBORSKÝ; Zbyněk PROKOP and Stanislav MAZURENKO
Edition
Nucleic Acids Research, Oxford, Oxford University Press, 2022, 0305-1048
Other information
Language
English
Type of outcome
Article in a journal
Country of publisher
United Kingdom of Great Britain and Northern Ireland
Confidentiality degree
is not subject to a state or trade secret
References:
Marked to be transferred to RIV
Yes
RIV identification code
RIV/00216224:14310/22:00126370
Organization
Přírodovědecká fakulta – Repository – Repository
UT WoS
EID Scopus
Keywords in English
FLUORESCENCE; CALORIMETRY; RESOLUTION; STATE
Links
EF15_003/0000469, research and development project. EF17_043/0009632, research and development project. LM2018121, research and development project. LM2018140, research and development project. 857560, interní kód Repo. ELIXIR-CZ II, large research infrastructures.
Changed: 28/2/2025 00:50, RNDr. Daniel Jakubík
Abstract
In the original language
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.