CalFitter: a web server for analysis of protein thermal denaturation data

Abstract

Despite significant advances in the understanding of protein structure-function relationships, revealing protein folding pathways still poses a challenge due to a limited number of relevant experimental tools. Widely-used experimental techniques, such as calorimetry or spectroscopy, critically depend on a proper data analysis. Currently, there are only separate data analysis tools available for each type of experiment with a limited model selection. To address this problem, we have developed the CalFitter web server to be a unified platform for comprehensive data fitting and analysis of protein thermal denaturation data. The server allows simultaneous global data fitting using any combination of input data types and offers 12 protein unfolding pathway models for selection, including irreversible transitions often missing from other tools. The data fitting produces optimal parameter values, their confidence intervals, and statistical information to define unfolding pathways. The server provides an interactive and easy-to-use interface that allows users to directly analyse input datasets and simulate modelled output based on the model parameters. CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.

Adaptation to mutational inactivation of an essential gene converges to an accessible suboptimal fitness peak

“…Thermal denaturation curves were also performed in the presence of 5x concentration of Sypro Orange and 20 μM. Melting temperature and confidence intervals at 95% were determined from the simultaneous analysis of the thermal denaturation curves obtained with both tryptophan and Sypro Orange fluorescence using the online software Calfitter (Mazurenko et al, 2018).…”

Constructing protein polyhedra via orthogonal chemical interactions

“…Data collection was performed using software EPU (FEI). All image processing was performed in the Relion-3.0 pipeline 46 . Motion-correction and dose-weighting was performed using MotionCor2 47 , and defocus values were estimated with Gctf 48 using a pixel size of 0.8 Å /pixel.…”

Predicting protein stability and solubility changes upon mutations: data perspective

“…Therefore, most data on protein stability changes upon mutation come from less demanding techniques, namely differential scanning calorimetry, light scattering, circular dichroism, fluorescence spectroscopy, etc. [39] In those experiments, protein in solution is denatured by physical (temperature, pressure), chemical (pH, osmolytes), or biological (proteases) perturbation, and the output signal is recorded and analyzed. For temperature denaturation, this analysis typically yields the melting temperature T m , loosely defined as the apparent midpoint of the transition in the signal, the difference in Gibbs free energy of the unfolded and folded states~G, typically derived from data fitting, or the activity-related temperature T 50 at which the residual activity is reduced by 50 % after incubation.…”

“…However, such experiments are expensive, low throughput, require sophisticated instrumentation, and are often limited by the protein size. Therefore, most data on protein stability changes upon mutation come from less demanding techniques, namely differential scanning calorimetry, light scattering, circular dichroism, fluorescence spectroscopy, etc [39] . In those experiments, protein in solution is denatured by physical (temperature, pressure), chemical (pH, osmolytes), or biological (proteases) perturbation, and the output signal is recorded and analyzed.…”