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用于在σ受体上发现配体的虚拟筛选

Virtual Screening for Ligand Discovery at the σ Receptor.

作者信息

Greenfield Daniel A, Schmidt Hayden R, Skiba Meredith A, Mandler Michael D, Anderson Jacob R, Sliz Piotr, Kruse Andrew C

机构信息

Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, Boston, Massachusetts 02115, United States.

Harvard University, Department of Chemistry and Chemical Biology, Cambridge, Massachusetts 02138, United States.

出版信息

ACS Med Chem Lett. 2020 Jul 27;11(8):1555-1561. doi: 10.1021/acsmedchemlett.9b00314. eCollection 2020 Aug 13.

Abstract

The σ receptor is a transmembrane protein implicated in several pathophysiological conditions, including neurodegenerative disease (J. Pharmacol. Sci.2015127 (1), 1729), drug addiction (Behav. Pharmacol.201627 (2-3 Spec Issue), 10015), cancer (Handb. Exp. Pharmacol.2017244237308), and pain (Neural Regener. Res.201813 (5), 775778). However, there are no high-throughput functional assays for σ receptor drug discovery. Here, we assessed high-throughput structure-based computational docking for discovery of novel ligands of the σ receptor. We screened a library of over 6 million compounds using the Schrödinger Glide package, followed by experimental characterization of top-scoring candidates. 77% of tested candidates bound σ with high affinity (K < 1 μM). These include compounds with high selectivity for the σ receptor compared to the genetically unrelated but pharmacologically similar σ receptor, as well as compounds with substantial crossreactivity between the two receptors. These results establish structure-based virtual screening as a highly effective platform for σ receptor ligand discovery and provide compounds to prioritize in studies of σ biology.

摘要

σ受体是一种跨膜蛋白,与多种病理生理状况有关,包括神经退行性疾病(《药理学杂志》2015年,127(1),17 - 29)、药物成瘾(《行为药理学》2016年,27(2 - 3特刊),100 - 15)、癌症(《实验药理学手册》2017年,244,237 - 308)和疼痛(《神经再生研究》2018年,13(5),775 - 778)。然而,目前尚无用于σ受体药物发现的高通量功能检测方法。在此,我们评估了基于结构的高通量计算对接技术,以发现σ受体的新型配体。我们使用薛定谔公司的Glide软件包筛选了一个包含超过600万种化合物的文库,随后对得分最高的候选化合物进行了实验表征。77%的受试候选化合物与σ受体具有高亲和力(K < 1 μM)。这些化合物包括与遗传上无关但药理学上相似的σ受体相比,对σ受体具有高选择性的化合物,以及在两种受体之间具有显著交叉反应性的化合物。这些结果确立了基于结构的虚拟筛选作为σ受体配体发现的高效平台,并为σ生物学研究中优先研究的化合物提供了依据。

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