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![[Figure 3]](qt5002fig3mag.jpg)
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Figure 3
The FoldAffinity pipeline can be divided into four steps. In the first step, the data are loaded and preprocessed. The preprocessing includes selecting the temperature range, smoothening the data and adding information about the ligand concentration of each capillary/well. The signal versus temperature plot will be colour-coded using a base-10 log scale and the viridis palette. Secondly, each melting curve is fitted to a two-state unfolding model that implicitly takes ligand binding into account. In this step, the user can see the fitted curves to the raw fluorescence data and identify temperature regions that deviate from the model. Thirdly, the unfolded fraction obtained from the previous fitting (Ku,obs) is used in combination with the protein concentration to estimate the binding affinity (Kd) and the unfolding constant (Ku) at a fixed chosen temperature (64°C in the example shown). Finally, individual CSV files with the model-derived information can be exported. |
![[Figure 3]](qt5002fig3.jpg)
 | STRUCTURAL BIOLOGY |
ISSN: 2059-7983
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