语境
髓样细胞 (TREM) 上表达的特殊触发受体家族在引起神经退行性疾病和激活小胶质细胞抗炎反应中发挥着关键作用。纳苏-哈科拉病 (NHD) 是一种罕见的常染色体隐性遗传疾病,与 TREM2 突变有关,而 TREM2 突变也会增加患阿尔茨海默病 (AD) 的风险。在此,我们努力使用突变诱导的折叠稳定性变化 (ΔΔ G ) 来区分与 NHD 和 AD 相关的 TREM2 胞外域 (ECD) 中已确认的致病性变异,并通过 12 种不同的基于结构的方法进行计算饱和诱变。相对溶剂可及性 (RSA) 和 ΔΔ G之间的相关性分析表达了 AD ( R 2 = 0.061) 和 NHD ( R 2 = 0.601)中与 TREM2 相关的突变体的离散分布行为 。我们的研究结果强调 W50 和 V126 作为维持 TREM2 中 V 样结构域的主要参与者。有趣的是,我们发现它们都与共同的残基 Y108 相互作用,该残基在突变时溶解。该 Y108 可能对 TREM2 具有结构或功能作用,是进一步研究的理想候选者。此外,残余相互作用网络凸显了 R47 和 R62 在维持对配体结合至关重要的 CDR 环方面的重要性。未来使用 TREM2-ECD 中配体相互作用的生物物理表征的研究将有助于开发 AD 和 NHD 的新型疗法。
方法
使用ConSurf算法和ENDscript确定TREM2野生型ECD中每个残基的位置和保守性。使用 12 种最先进的基于结构的蛋白质稳定性工具估计了与 NHD 和 AD 相关的已确认致病突变体的突变诱导的倍数稳定性变化 (ΔΔ G )。此外,我们还使用计算饱和诱变计算了随机突变对这些位点的影响。通过 GraphPad 软件使用突变体 ΔΔ G和 RSA进行线性回归分析。此外,使用RING3.0枚举了野生型及其TREM2-ECD突变体的综合非键残基相互作用网络(RIN)。
"点击查看英文标题和摘要"
Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer’s and Nasu-Hakola disease
Context
The specialised family of triggering receptors expressed on myeloid cells (TREMs) plays a pivotal role in causing neurodegenerative disorders and activating microglial anti-inflammatory responses. Nasu-Hakola disease (NHD), a rare autosomal recessive disorder, has been associated with mutations in TREM2, which is also responsible for raising the risk of Alzheimer’s disease (AD). Herein, we have made an endeavour to differentiate the confirmed pathogenic variants in TREM2 extra-cellular domain (ECD) linked with NHD and AD using mutation-induced fold stability change (∆∆G), with the computation of 12distinct structure-based methods through saturation mutagenesis. Correlation analysis between relative solvent accessibility (RSA) and ∆∆G expresses the discrete distributive behaviour of mutants associated with TREM2 in AD (R2 = 0.061) and NHD (R2 = 0.601). Our findings put an emphasis on W50 and V126 as major players in maintaining V-like domain in TREM2. Interestingly, we discern that both of them interact with a common residue Y108, which is dissolved upon mutation. This Y108 could have structural or functional role for TREM2 which can be an ideal candidate for further study. Furthermore, the residual interaction network highlights the importance of R47 and R62 in maintaining the CDR loops that are crucial for ligand binding. Future studies using biophysical characterisation of ligand interactions in TREM2-ECD would be helpful for the development of novel therapeutics for AD and NHD.
Methods
ConSurf algorithm and ENDscript were used to determine the position and conservation of each residue in the wild-type ECD of TREM2. The mutation-induced fold stability change (∆∆G) of confirmed pathogenic mutants associated with NHD and AD was estimated using 12 state-of-the-art structure-based protein stability tools. Furthermore, we also computed the effect of random mutation on these sites using computational saturation mutagenesis. Linear regression analysis was performed using mutants ∆∆G and RSA through GraphPad software. In addition, a comprehensive non-bonded residual interaction network (RIN) of wild type and its mutants of TREM2-ECD was enumerated using RING3.0.