Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.
Department of Biological Chemistry, University of Michigan, Ann Arbor, Michigan, United States of America.
PLoS Comput Biol. 2021 Sep 16;17(9):e1009370. doi: 10.1371/journal.pcbi.1009370. eCollection 2021 Sep.
Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.
蛋白质的三维结构可以为个性化治疗的疗效提供重要线索。我们对三种遗传性溶酶体贮积症中的变体进行了结构分析，比较了对药物伴侣治疗有反应和无反应的变体。我们发现，在法布里病和庞贝病的数据集情况下，对于无反应的治疗变体，预测突变的 ΔΔG 平均更高，这与以前的发现一致。使用单个决策树和基于较大法布里数据集的先进机器学习方法，我们正确预测了三种戈谢病变体的反应性，并对未经测试的变体提供了预测。许多变体被预测对治疗有反应，这表明基于药物的治疗可能对戈谢病的许多变体有效。在我们的分析中，我们观察到依赖于拓扑特征报告关于接触排列的情况，这可能与蛋白质残基折叠的顺序有关，并且我们基于稳态细胞动力学为这一观察结果提供了一个潜在的理由。
