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Using a second‐order differential model to fit data without baselines in protein isothermal chemical denaturation
Author(s) -
Tang Chuanning,
Lew Scott,
He Dacheng
Publication year - 2016
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.2878
Subject(s) - denaturation (fissile materials) , isothermal process , protein folding , stability (learning theory) , folding (dsp implementation) , protein stability , chemistry , gibbs free energy , experimental data , biological system , thermodynamics , differential (mechanical device) , computer science , mathematics , physics , statistics , biochemistry , biology , machine learning , electrical engineering , nuclear chemistry , engineering
In vitro protein stability studies are commonly conducted via thermal or chemical denaturation/renaturation of protein. Conventional data analyses on the protein unfolding/(re)folding require well‐defined pre‐ and post‐transition baselines to evaluate Gibbs free‐energy change associated with the protein unfolding/(re)folding. This evaluation becomes problematic when there is insufficient data for determining the pre‐ or post‐transition baselines. In this study, fitting on such partial data obtained in protein chemical denaturation is established by introducing second‐order differential (SOD) analysis to overcome the limitations that the conventional fitting method has. By reducing numbers of the baseline‐related fitting parameters, the SOD analysis can successfully fit incomplete chemical denaturation data sets with high agreement to the conventional evaluation on the equivalent completed data, where the conventional fitting fails in analyzing them. This SOD fitting for the abbreviated isothermal chemical denaturation further fulfills data analysis methods on the insufficient data sets conducted in the two prevalent protein stability studies.