Mesh : Molecular Dynamics Simulation Humans Mutation Protein Conformation Serpins / genetics chemistry metabolism Protein Folding Antithrombin III / genetics chemistry metabolism

来  源:   DOI:10.1371/journal.pone.0304451   PDF(Pubmed)

Abstract:
Serine protease inhibitors (serpins) include thousands of structurally conserved proteins playing key roles in many organisms. Mutations affecting serpins may disturb their conformation, leading to inactive forms. Unfortunately, conformational consequences of serpin mutations are difficult to predict. In this study, we integrate experimental data of patients with mutations affecting one serpin with the predictions obtained by AlphaFold and molecular dynamics. Five SERPINC1 mutations causing antithrombin deficiency, the strongest congenital thrombophilia were selected from a cohort of 350 unrelated patients based on functional, biochemical, and crystallographic evidence supporting a folding defect. AlphaFold gave an accurate prediction for the wild-type structure. However, it also produced native structures for all variants, regardless of complexity or conformational consequences in vivo. Similarly, molecular dynamics of up to 1000 ns at temperatures causing conformational transitions did not show significant changes in the native structure of wild-type and variants. In conclusion, AlphaFold and molecular dynamics force predictions into the native conformation at conditions with experimental evidence supporting a conformational change to other structures. It is necessary to improve predictive strategies for serpins that consider the conformational sensitivity of these molecules.
摘要:
丝氨酸蛋白酶抑制剂(serpin)包括数千种结构保守的蛋白质,在许多生物体中起关键作用。影响serpin的突变可能会扰乱它们的构象,导致不活跃的形式。不幸的是,serpin突变的构象后果很难预测。在这项研究中,我们将影响一个血清酶蛋白突变的患者的实验数据与通过AlphaFold和分子动力学获得的预测进行整合。5个SERPINC1突变导致抗凝血酶缺乏,最强的先天性血栓形成倾向是根据功能,从350名无关患者中选择的,生物化学,和支持折叠缺陷的晶体学证据。AlphaFold给出了野生型结构的准确预测。然而,它还产生了所有变体的天然结构,无论体内的复杂性或构象后果。同样,在导致构象转变的温度下高达1000ns的分子动力学并未显示出野生型和变体的天然结构的显着变化。总之,在实验证据支持其他结构的构象变化的条件下,AlphaFold和分子动力学将预测转化为天然构象。有必要改进考虑这些分子构象敏感性的丝氨酸蛋白酶抑制剂的预测策略。
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