Differential scanning fluorimetry (DSF) can be an effective high-throughput screening assay in drug discovery for detecting protein-compound interactions that stabilize or destabilize macromolecules. Due to the magnitude and quality of the data produced by this biophysical assay, analyzing and prioritizing compounds from large-scale DSF data sets has proven challenging to the research community. Here, we present ShiftScan-a powerful, stand-alone tool designed for the rapid analysis of DSF data and compound prioritization based on thermal transition patterns. ShiftScan accurately and quickly predicts melting temperatures (Tm values) from both canonical and non-canonical transition patterns, efficiently filtering out spurious data to minimize false positives. We report on the use of this tool for data analysis of screens involving both pure compound and natural product fraction libraries and provide the software to the screening community to aid in the discovery of molecularly-targeted compounds. Instructions for installation and usage of ShiftScan can be found at our GitHub repository: https://github.com/samche42/ShiftScan.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848206 | PMC |
| http://dx.doi.org/10.1002/pro.70055 | DOI Listing |
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