1 Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California, San Francisco, San Francisco, CA, USA.
2 Department of Biomedical Engineering, Laboratory of Chemical Biology, and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands.
SLAS Discov. 2018 Feb;23(2):183-192. doi: 10.1177/2472555217732072. Epub 2017 Sep 25.
We report the refinement of a high-throughput, liquid chromatography/mass spectrometry (LC/MS)-based screening method for the identification of covalent small-molecule binders to proteins. Using a custom library of 1600 disulfide-capped fragments targeting surface cysteine residues, we optimize sample preparation, chromatography, and ionization conditions to maximize the reliability and flexibility of the approach. Data collection at a rate of 84 s per sample balances speed with reliability for sustained screening over multiple, diverse projects run over a 24-month period. The method is applicable to protein targets of various classes and a range of molecular masses. Data are processed in a custom pipeline that calculates a percent bound value for each compound and identifies false positives by calculating significance of detected masses (signal significance). An example pipeline is available through Biovia's ScienceCloud Protocol Exchange. Data collection and analysis methods for the screening of covalent adducts of intact proteins are now fast enough to screen the largest covalent compound libraries in 1 to 2 days.
我们报告了一种基于高效液相色谱/质谱（LC/MS）的高通量筛选方法的改进，用于鉴定与蛋白质发生共价结合的小分子配体。该方法使用了一个针对表面半胱氨酸残基的 1600 个巯基封闭片段的定制文库，我们优化了样品制备、色谱和离子化条件，以最大限度地提高该方法的可靠性和灵活性。以 84 秒/样的速度进行数据采集，在多个不同项目的 24 个月运行期间，在速度和可靠性之间取得了平衡。该方法适用于各种类别和分子量的蛋白质靶标。数据通过一个自定义的管道进行处理，该管道为每个化合物计算结合百分比值，并通过计算检测到的质量的显著性（信号显著性）来识别假阳性。通过 Biovia 的 ScienceCloud Protocol Exchange 可以获得示例管道。用于完整蛋白质共价加合物筛选的数据采集和分析方法现在足够快，可以在 1 到 2 天内筛选最大的共价化合物文库。
