RESUMO
Differential scanning fluorimetry (DSF) is a technique that reports protein thermal stability via the selective recognition of unfolded states by fluorogenic dyes. However, DSF applications remain limited by protein incompatibilities with existing DSF dyes. Here we overcome this obstacle with the development of a protein-adaptive DSF platform (paDSF) that combines a dye library 'Aurora' with a streamlined procedure to identify protein-dye pairs on demand. paDSF was successfully applied to 94% (66 of 70) of proteins, tripling the previous compatibility and delivering assays for 66 functionally and biochemically diverse proteins, including 10 from severe acute respiratory syndrome coronavirus 2. We find that paDSF can be used to monitor biological processes that were previously inaccessible, demonstrated for the interdomain allostery of O-GlcNAc transferase. The chemical diversity and varied selectivities of Aurora dyes suggest that paDSF functionality may be readily extended. paDSF is a generalizable tool to interrogate protein stability, dynamics and ligand binding.
RESUMO
Differential scanning fluorimetry (DSF) is a method to determine the apparent melting temperature (Tma) of a purified protein. In DSF, the raw unfolding curves from which Tma is calculated vary widely in shape and complexity. However, the tools available for calculating Tma are only compatible with the simplest of DSF curves, hindering many otherwise straightforward applications of the technology. To overcome this limitation, we designed new mathematical models for Tma calculation that accommodate common forms of variation in DSF curves, including the number of transitions, the presence of high initial signal, and temperature-dependent signal decay. When tested these models against DSFbase, an open-source database of 6235 raw, real-life DSF curves, these models outperformed the existing standard approaches of sigmoid fitting and maximum of the first derivative. To make these models accessible, we created an open-source software and website, DSFworld (https://gestwickilab.shinyapps.io/dsfworld/). In addition to these improved fitting capabilities, DSFworld also includes features that overcome the practical limitations of many analysis workflows, including automatic reformatting of raw data exported from common qPCR instruments, labeling of data based on experimental variables, and flexible interactive plotting. We hope that DSFworld will enable more streamlined and accurate calculation of Tma values for DSF experiments.