J 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:

URL

Marked to be transferred to RIV

Yes

RIV identification code

RIV/00216224:14310/22:00126370

Organization

Přírodovědecká fakulta – Repository – Repository

DOI

https://doi.org/10.1093/nar/gkac378

UT WoS

000796682400001

EID Scopus

2-s2.0-85134376457

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.
Displayed: 2/5/2026 18:30