Fedorov Ivan I, Ivanov Mark V, Gorshkov Mikhail V
V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia.
Anal Chem. 2025 Jan 14;97(1):22-26. doi: 10.1021/acs.analchem.4c04313. Epub 2024 Dec 25.
In this Letter, a two-term formalism for constructing protein solubility curves in thermal proteome profiling (TPP) is considered, which takes into account the efficiency of the drug-protein binding reaction. When the reaction is incomplete, this results in distortion of the otherwise sigmoidal shape of the curve after drug treatment, which is often observed in experiments. This distortion may be significant enough to disqualify the corresponding protein from the list of drug target candidates, thus negatively affecting the results of TPP data analysis. To further assist this analysis, we also developed the solubility curve simulation software to visualize the discussed effect. Several experimental data sets from recent TPP studies have been reprocessed, and we demonstrate in a few examples that the proposed two-term equation fits correctly the observed protein solubility curves with distorted shapes, also highlighting the previously unrecognized targets.
在本信函中，我们考虑了一种用于构建热蛋白质组分析（TPP）中蛋白质溶解度曲线的双项形式，该形式考虑了药物 - 蛋白质结合反应的效率。当反应不完全时，这会导致药物处理后曲线原本的S形发生扭曲，这种情况在实验中经常观察到。这种扭曲可能足够显著，以至于将相应蛋白质从药物靶标候选列表中排除，从而对TPP数据分析结果产生负面影响。为了进一步辅助这种分析，我们还开发了溶解度曲线模拟软件来可视化所讨论的效应。对近期TPP研究中的几个实验数据集进行了重新处理，并且我们在一些示例中证明，所提出的双项方程能够正确拟合观察到的具有扭曲形状的蛋白质溶解度曲线，同时还突出了先前未被识别的靶标。
