Dixon Tom, Uyar Arzu, Ferguson-Miller Shelagh, Dickson Alex
Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, Michigan; Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, Michigan.
Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, Michigan.
Biophys J. 2021 Jan 5;120(1):158-167. doi: 10.1016/j.bpj.2020.11.015. Epub 2020 Nov 20.
The translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is of longstanding medical interest as both a biomarker for neuroinjury and a potential drug target for neuroinflammation and other disorders. Recently, it was shown that ligand residence time is a key factor determining steroidogenic efficacy of TSPO-binding compounds. This spurs interest in simulations of (un)binding pathways of TSPO ligands, which could reveal the molecular interactions governing ligand residence time. In this study, we use a weighted ensemble algorithm to determine the unbinding pathway for different poses of PK-11195, a TSPO ligand used in neuroimaging. In contrast with previous studies, our results show that PK-11195 does not dissociate directly into the solvent but instead dissociates via the lipid membrane by going between the transmembrane helices. We analyze this path ensemble in detail, constructing descriptors that can facilitate a general understanding of membrane-mediated ligand binding. We construct a set of Markov state models augmented with additional straightforward simulations to determine pose-specific ligand residence times. Together, we combine over 40 μs of trajectory data to form a coherent picture of the ligand binding landscape. We find that multiple starting poses yield residence times that roughly agree with the experimental quantity. The ligand binding transition states predicted by these Markov state models occur when PK-11195 is already in the membrane and involves only minimal ligand-protein interactions. This has implications for the design of new long-residence-time TSPO ligands.
转位蛋白(TSPO),以前称为外周苯二氮䓬受体,作为神经损伤的生物标志物以及神经炎症和其他疾病的潜在药物靶点,长期以来一直是医学研究的热点。最近,研究表明配体停留时间是决定TSPO结合化合物类固醇生成功效的关键因素。这激发了人们对TSPO配体(非)结合途径模拟的兴趣,该模拟可以揭示控制配体停留时间的分子相互作用。在本研究中,我们使用加权系综算法来确定用于神经成像的TSPO配体PK-11195不同构象的解离途径。与先前的研究不同,我们的结果表明PK-11195不是直接解离到溶剂中,而是通过跨膜螺旋之间的脂质膜解离。我们详细分析了这条途径系综,构建了有助于全面理解膜介导配体结合的描述符。我们构建了一组马尔可夫状态模型,并辅以额外的简单模拟,以确定特定构象的配体停留时间。我们总共结合了超过40微秒的轨迹数据,以形成配体结合态势的连贯图景。我们发现多个起始构象产生的停留时间与实验值大致相符。这些马尔可夫状态模型预测的配体结合过渡态发生在PK-11195已经在膜中时,并且只涉及最少的配体-蛋白质相互作用。这对新型长停留时间TSPO配体的设计具有启示意义。