Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France ; INSERM, U973, Paris, France.
PLoS One. 2013 Sep 6;8(9):e73587. doi: 10.1371/journal.pone.0073587. eCollection 2013.
Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug-drug interactions. We focus on sulfotransferases (SULTs), a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD) simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands' binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes.
药物代谢酶在异源生物、药物和内源性分子的代谢、消除和解毒中起着关键作用。虽然它们的主要作用是通过修饰化合物（如污染物或药物）来使生物体解毒，从而快速排泄，但在某些情况下，它们会使底物变得更具毒性，从而导致严重的副作用和药物不良反应，或者它们的抑制作用会导致药物相互作用。我们专注于磺基转移酶（SULTs），这是一类 II 相代谢酶，作用于大量药物和激素，表现出重要的结构灵活性。在这里，我们报告了一种新的基于结构的计算方法来探测配体与 SULTs 的结合。我们通过分子动力学（MD）模拟探索了 SULTs 的灵活性，以确定最适合配体结合预测的多个受体构象。然后，我们采用基于结构的对接评分方法来预测配体结合，最后我们通过 QSAR 方法组合预测的相互作用能。结果表明，我们的方案成功地为研究的 SULT1 同工酶优先排列了强效结合物，并为不同配体结合的特定分子机制提供了新的见解，这些机制与它们结合部位的可塑性有关。我们最好的 QSAR 模型，通过对接引入预测的蛋白质-配体相互作用能，对同工酶 SULT1A1、SULT1A3 和 SULT1E1 的准确性分别为 67.28%、78.00%和 75.46%。据我们所知，我们的方案是第一个基于结构的计算方法，它包括在原子水平上进行蛋白质-配体相互作用分析，同时考虑配体和酶的灵活性，以及 QSAR 方法，以识别可以与 II 相药物代谢酶相互作用的小分子。
