Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), Butenandtstr. 7, 81377, Munich, Germany.
Dept. Chemistry, Section Biochemistry, Johannes Gutenberg-Universität Mainz, 55128, Mainz, Germany.
Angew Chem Int Ed Engl. 2020 Jul 27;59(31):12669-12673. doi: 10.1002/anie.202000539. Epub 2020 May 25.
The absence of fluorine from most biomolecules renders it an excellent probe for NMR spectroscopy to monitor inhibitor-protein interactions. However, predicting the binding mode of a fluorinated ligand from a chemical shift (or vice versa) has been challenging due to the high electron density of the fluorine atom. Nonetheless, reliable F chemical-shift predictions to deduce ligand-binding modes hold great potential for in silico drug design. Herein, we present a systematic QM/MM study to predict the F NMR chemical shifts of a covalently bound fluorinated inhibitor to the essential oxidoreductase tryparedoxin (Tpx) from African trypanosomes, the causative agent of African sleeping sickness. We include many protein-inhibitor conformations as well as monomeric and dimeric inhibitor-protein complexes, thus rendering it the largest computational study on chemical shifts of F nuclei in a biological context to date. Our predicted shifts agree well with those obtained experimentally and pave the way for future work in this area.
氟在大多数生物分子中都不存在,这使其成为监测抑制剂-蛋白质相互作用的 NMR 光谱学的理想探针。然而,由于氟原子的高电子密度,从化学位移(或反之亦然)预测氟化配体的结合模式一直具有挑战性。尽管如此,可靠的 F 化学位移预测对于推断配体结合模式在计算机药物设计中具有巨大的潜力。在此,我们进行了一项系统的 QM/MM 研究,以预测共价结合的氟化抑制剂与来自非洲锥虫(引起非洲昏睡病的病原体)的必需氧化还原酶 tryparedoxin(Tpx)的 F NMR 化学位移。我们包括了许多蛋白质-抑制剂构象以及单体和二聚体抑制剂-蛋白质复合物,因此这是迄今为止在生物环境中对 F 核化学位移进行的最大计算研究。我们预测的位移与实验获得的结果吻合良好,为该领域的未来工作铺平了道路。