Samantha C Waterworth, Shilpa R Shenoy, Nirmala D Sharma, Chris Wolcott, Duncan E Donohue, Barry R O'Keefe, John A Beutler
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引用次数: 0
Abstract
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.
期刊介绍:
Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution.
Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics.
The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication.
Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).