Department of Chemistry , Technical University of Denmark , DK-2800 Kongens Lyngby , Denmark.
J Chem Inf Model. 2019 Feb 25;59(2):858-870. doi: 10.1021/acs.jcim.8b00896. Epub 2019 Feb 11.
Alzheimer's disease (AD) is one of the major global health challenges of the 21st century. More than 200 distinct mutations in presenilin 1 (PSEN1) cause severe early-onset familial AD (FAD) and are thus of central interest to the etiology of AD. PSEN1 is the catalytic subunit of γ-secretase that produces β-amyloid peptide (Aβ), and the mutations tend to increase the produced Aβ/Aβ ratio. The molecular reasons for the pathogenesis of these mutations are unknown. We studied a close-to-complete data set of PSEN1 mutations using 21 different computational methods hypothesized to reproduce pathogenesis, using both sequence- and structure-based methods with the full γ-secretase complex as input. First, we tested whether pathogenicity can be estimated accurately using all possible mutations in PSEN1 as a direct control. Several methods predict the pathogenicity of the mutations (pathogenic vs all other possible mutations) well, with accuracies approaching 90%. We then designed a stricter test for predicting the severity of the mutations estimated by the average clinical age of symptom onset for mutation carriers. Surprisingly, we can predict the clinical age of symptom onset at 95% confidence or higher with several methods. Accordingly, our results show that simple biochemical properties of the amino acid changes rationalize an important part of the pathogenicity of FAD-causing PSEN1 mutations. Although pathogenic mutations generally destabilize γ-secretase, all of the tested protein stability methods failed to predict pathogenicity. Thus, either the static cryogenic-electron-microscopy-derived molecular-dynamics-equilibrated structures used as input fail to capture the stability effect of mutated side chains or protein stability is simply not a key factor in the pathogenicity. Our findings suggest that the chemical causes of FAD may be modeled and lend promise to the development of a semiquantitative model predicting the age of onset of mutation carriers that could eventually become of care-strategic value.
阿尔茨海默病（AD）是 21 世纪全球主要健康挑战之一。早发性家族性 AD（FAD）中超过 200 种不同的早老素 1（PSEN1）突变与该病的发病机制密切相关。PSEN1 是 γ-分泌酶的催化亚基，可产生 β-淀粉样肽（Aβ），这些突变往往会增加产生的 Aβ/Aβ 比值。这些突变导致发病的分子原因尚不清楚。我们使用 21 种不同的计算方法研究了 PSEN1 突变的近乎完整数据集，这些方法假设可以复制发病机制，使用基于序列和结构的方法，输入的是完整的 γ-分泌酶复合物。首先，我们测试了是否可以使用 PSEN1 中的所有可能突变作为直接对照来准确估计致病性。几种方法可以很好地预测突变的致病性（致病性与所有其他可能的突变相比），准确率接近 90%。然后，我们设计了一个更严格的测试来预测突变携带者的症状发作平均临床年龄估计的突变严重程度。令人惊讶的是，我们可以使用几种方法以 95%的置信度或更高的置信度预测症状发作的临床年龄。因此，我们的结果表明，氨基酸变化的简单生化特性可以合理地解释 FAD 引起的 PSEN1 突变致病性的重要部分。尽管致病性突变通常会使 γ-分泌酶失稳，但所有测试的蛋白质稳定性方法都无法预测致病性。因此，要么用作输入的低温电子显微镜衍生的分子动力学平衡结构无法捕获突变侧链的稳定性效应，要么蛋白质稳定性根本不是致病性的关键因素。我们的研究结果表明，FAD 的化学原因可能会被建模，并为开发一种半定量模型预测突变携带者的发病年龄带来希望，这种模型最终可能具有护理策略价值。
