Site of Reactivity Models Predict Molecular Reactivity of Diverse Chemicals with Glutathione

Drug toxicity is often caused by electrophilic reactive metabolites that covalently bind to proteins. Consequently, the quantitative strength of a molecule’s reactivity with glutathione (GSH) is a frequently used indicator of its toxicity. Through cysteine, GSH (and proteins) scavenges reactive molecules to form conjugates in the body. GSH conjugates to specific atoms in reactive molecules: their sites of reactivity. The value of knowing a molecule’s sites of reactivity is unexplored in the literature. This study tests the value of site of reactivity data that identifies the atoms within 1213 reactive molecules that conjugate to GSH and builds models to predict molecular reactivity with glutathione. An algorithm originally written to model sites of cytochrome P450 metabolism (called XenoSite) finds clear patterns in molecular structure that identify sites of reactivity within reactive molecules with 90.8% accuracy and separate reactive and unreactive molecules with 80.6% accuracy. Furthermore, the model output strongly correlates with quantitative GSH reactivity data in chemically diverse, external data sets. Site of reactivity data is nearly unstudied in the literature prior to our efforts, yet it contains a strong signal for reactivity that can be utilized to more accurately predict molecule reactivity and, eventually, toxicity.药物毒性通常由可与蛋白质发生共价结合的亲电活性代谢物所引发。因此，分子与谷胱甘肽（glutathione, GSH）的反应活性定量强度，常被用作评估其毒性的常用指标。谷胱甘肽（及蛋白质）可通过半胱氨酸残基清除体内活性分子，与之结合形成结合物。谷胱甘肽可结合至活性分子中的特定原子，即该分子的反应位点。目前学界尚未对探明分子反应位点的研究价值展开充分探索。 本研究针对反应位点数据的应用价值展开验证：该数据可识别1213种可与谷胱甘肽结合的活性分子内的结合原子，并构建模型以预测分子与谷胱甘肽的反应活性。一款原本用于建模细胞色素P450代谢位点的算法（命名为XenoSite），可从分子结构中挖掘出明确的结构规律，以90.8%的准确率识别活性分子内的反应位点，并以80.6%的准确率区分活性与非活性分子。此外，在化学多样性的外部数据集上，该模型的输出结果与定量谷胱甘肽反应活性数据呈现显著相关性。尽管在本研究开展前，学界几乎未对反应位点数据展开研究，但该数据蕴含了关于反应活性的强信号，可用于更精准地预测分子反应活性，最终助力药物毒性的精准评估。