Docking Screens for Dual Inhibitors of Disparate Drug Targets for Parkinson’s Disease

Modulation
of multiple biological targets with a single drug can
lead to synergistic therapeutic effects and has been demonstrated
to be essential for efficient treatment of CNS disorders. However,
rational design of compounds that interact with several targets is
very challenging. Here, we demonstrate that structure-based virtual
screening can guide the discovery of multi-target ligands of unrelated
proteins relevant for Parkinson’s disease. A library with 5.4
million molecules was docked to crystal structures of the A2A adenosine receptor (A2AAR) and monoamine oxidase B (MAO-B).
Twenty-four compounds that were among the highest ranked for both
binding sites were evaluated experimentally, resulting in the discovery
of four dual-target ligands. The most potent compound was an A2AAR antagonist with nanomolar affinity (Ki = 19 nM) and inhibited MAO-B with an IC50 of 100 nM. Optimization guided by the predicted binding modes led
to the identification of a second potent dual-target scaffold. The
two discovered scaffolds were shown to counteract 6-hydroxy­dopamine-induced
neurotoxicity in dopaminergic neuronal-like SH-SY5Y cells. Structure-based
screening can hence be used to identify ligands with specific polypharmacological
profiles, providing new avenues for drug development against complex
diseases.

单一药物调控多种生物靶点可产生协同治疗效应，且已被证实对中枢神经系统（Central Nervous System, CNS）疾病的高效治疗至关重要。然而，理性设计可与多个靶点结合的化合物极具挑战性。本研究证实，基于结构的虚拟筛选可助力发现与帕金森病相关的非同源蛋白的多靶点配体。我们将包含540万个分子的化合物库，针对A2A腺苷受体（A2A adenosine receptor, A2AAR）与单胺氧化酶B（monoamine oxidase B, MAO-B）的晶体结构开展分子对接。我们对两个结合位点均排名靠前的24种化合物进行实验评估，最终发现4种双靶点配体。效力最强的化合物为A2A腺苷受体拮抗剂，具备纳摩尔级亲和力（Ki=19 nM），且对单胺氧化酶B的半抑制浓度（IC50）为100 nM。基于预测结合模式指导的结构优化，我们又发现了第二种强效双靶点骨架。实验证实，所发现的两种骨架均可对抗6-羟基多巴胺诱导的多巴胺能神经元样SH-SY5Y细胞神经毒性。由此可见，基于结构的虚拟筛选可用于鉴定具有特定多药理学特性的配体，为针对复杂疾病的药物研发提供全新途径。