Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry. / Augustijn, Dillen; Mahapatra, Sujata; Streicher, Werner; Svilenov, Hristo; Kulakova, Alina; Pohl, Christin; Rinnan, Åsmund.

In: European Journal of Pharmaceutics and Biopharmaceutics, Vol. 142, 2019, p. 506-517.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Augustijn, D, Mahapatra, S, Streicher, W, Svilenov, H, Kulakova, A, Pohl, C & Rinnan, Å 2019, 'Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry', European Journal of Pharmaceutics and Biopharmaceutics, vol. 142, pp. 506-517. https://doi.org/10.1016/j.ejpb.2019.06.001

APA

Augustijn, D., Mahapatra, S., Streicher, W., Svilenov, H., Kulakova, A., Pohl, C., & Rinnan, Å. (2019). Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry. European Journal of Pharmaceutics and Biopharmaceutics, 142, 506-517. https://doi.org/10.1016/j.ejpb.2019.06.001

Vancouver

Augustijn D, Mahapatra S, Streicher W, Svilenov H, Kulakova A, Pohl C et al. Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry. European Journal of Pharmaceutics and Biopharmaceutics. 2019;142:506-517. https://doi.org/10.1016/j.ejpb.2019.06.001

Author

Augustijn, Dillen ; Mahapatra, Sujata ; Streicher, Werner ; Svilenov, Hristo ; Kulakova, Alina ; Pohl, Christin ; Rinnan, Åsmund. / Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry. In: European Journal of Pharmaceutics and Biopharmaceutics. 2019 ; Vol. 142. pp. 506-517.

Bibtex

@article{60971cf84f9f48acb36badb3001143b2,

title = "Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry",

abstract = "In biotherapeutic protein research, an estimation of the studied protein's thermal stability is one of the important steps that determine developability as a function of solvent conditions. Differential Scanning Fluorimetry (DSF) can be applied to measure thermal stability. Label-free DSF measures amino acid fluorescence as a function of temperature, where conformational changes induce observable peak deformation, yielding apparent melting temperatures. The estimation of the stability parameters can be hindered in the case of multidomain, multimeric or aggregating proteins when multiple transitions partially coincide. These overlapping protein unfolding transitions are hard to evaluate by the conventional methodology, as peak maxima are shifted by convolution. We show how non-linear curve fitting of intrinsic fluorescence DSF can deconvolute highly overlapping transitions in formulation screening in a semi-automated process. The proposed methodology relies on synchronous, constrained fits of the fluorescence intensity, ratio and their derivatives, by combining linear baselines with generalized logistic transition functions. The proposed algorithm is applied to data from three proteins; a single transition, a double separated transition and a double overlapping transition. Extracted thermal stability parameters; apparent melting temperatures Tm,1, Tm,2 and melting onset temperature Tonset are obtained and compared with reference software analysis. The fits show R2 = 0.94 for single and R2 = 0.88 for separated transitions. Obtaining values and trends for Tonset in a well-described and automated way, will aid protein scientist to better evaluate the thermal stability of proteins.",

keywords = "Biotherapeutics, Differential scanning fluorimetry, Intrinsic fluorescence DSF, Multivariate data analysis, Non-linear curve fitting, Protein screening, Thermal stability screening",

author = "Dillen Augustijn and Sujata Mahapatra and Werner Streicher and Hristo Svilenov and Alina Kulakova and Christin Pohl and {\AA}smund Rinnan",

year = "2019",

doi = "10.1016/j.ejpb.2019.06.001",

language = "English",

volume = "142",

pages = "506--517",

journal = "European Journal of Pharmaceutics and Biopharmaceutics",

issn = "0939-6411",

publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry

AU - Augustijn, Dillen

AU - Mahapatra, Sujata

AU - Streicher, Werner

AU - Svilenov, Hristo

AU - Kulakova, Alina

AU - Pohl, Christin

AU - Rinnan, Åsmund

PY - 2019

Y1 - 2019

N2 - In biotherapeutic protein research, an estimation of the studied protein's thermal stability is one of the important steps that determine developability as a function of solvent conditions. Differential Scanning Fluorimetry (DSF) can be applied to measure thermal stability. Label-free DSF measures amino acid fluorescence as a function of temperature, where conformational changes induce observable peak deformation, yielding apparent melting temperatures. The estimation of the stability parameters can be hindered in the case of multidomain, multimeric or aggregating proteins when multiple transitions partially coincide. These overlapping protein unfolding transitions are hard to evaluate by the conventional methodology, as peak maxima are shifted by convolution. We show how non-linear curve fitting of intrinsic fluorescence DSF can deconvolute highly overlapping transitions in formulation screening in a semi-automated process. The proposed methodology relies on synchronous, constrained fits of the fluorescence intensity, ratio and their derivatives, by combining linear baselines with generalized logistic transition functions. The proposed algorithm is applied to data from three proteins; a single transition, a double separated transition and a double overlapping transition. Extracted thermal stability parameters; apparent melting temperatures Tm,1, Tm,2 and melting onset temperature Tonset are obtained and compared with reference software analysis. The fits show R2 = 0.94 for single and R2 = 0.88 for separated transitions. Obtaining values and trends for Tonset in a well-described and automated way, will aid protein scientist to better evaluate the thermal stability of proteins.

AB - In biotherapeutic protein research, an estimation of the studied protein's thermal stability is one of the important steps that determine developability as a function of solvent conditions. Differential Scanning Fluorimetry (DSF) can be applied to measure thermal stability. Label-free DSF measures amino acid fluorescence as a function of temperature, where conformational changes induce observable peak deformation, yielding apparent melting temperatures. The estimation of the stability parameters can be hindered in the case of multidomain, multimeric or aggregating proteins when multiple transitions partially coincide. These overlapping protein unfolding transitions are hard to evaluate by the conventional methodology, as peak maxima are shifted by convolution. We show how non-linear curve fitting of intrinsic fluorescence DSF can deconvolute highly overlapping transitions in formulation screening in a semi-automated process. The proposed methodology relies on synchronous, constrained fits of the fluorescence intensity, ratio and their derivatives, by combining linear baselines with generalized logistic transition functions. The proposed algorithm is applied to data from three proteins; a single transition, a double separated transition and a double overlapping transition. Extracted thermal stability parameters; apparent melting temperatures Tm,1, Tm,2 and melting onset temperature Tonset are obtained and compared with reference software analysis. The fits show R2 = 0.94 for single and R2 = 0.88 for separated transitions. Obtaining values and trends for Tonset in a well-described and automated way, will aid protein scientist to better evaluate the thermal stability of proteins.

KW - Biotherapeutics

KW - Differential scanning fluorimetry

KW - Intrinsic fluorescence DSF

KW - Multivariate data analysis

KW - Non-linear curve fitting

KW - Protein screening

KW - Thermal stability screening

U2 - 10.1016/j.ejpb.2019.06.001

DO - 10.1016/j.ejpb.2019.06.001

M3 - Journal article

C2 - 31175923

AN - SCOPUS:85069878158

VL - 142

SP - 506

EP - 517

JO - European Journal of Pharmaceutics and Biopharmaceutics

JF - European Journal of Pharmaceutics and Biopharmaceutics

SN - 0939-6411

ER -

ID: 228365797