机器学习本质无序蛋白质磷酸化导致的微妙构象变化,The Journal of Physical Chemistry B

当前位置： X-MOL 学术 › J. Phys. Chem. B › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

机器学习本质无序蛋白质磷酸化导致的微妙构象变化
The Journal of Physical Chemistry B ( IF 2.8 ) Pub Date : 2023-10-31 , DOI: 10.1021/acs.jpcb.3c05136
Subinoy Adhikari ₁ , Jagannath Mondal ₁

Affiliation

本质无序蛋白质/区域 (IDP/IDR) 的磷酸化对细胞信号传导、蛋白质折叠或解折叠以及长程变构效应等生物功能具有深远影响。然而，这里我们重点关注两个 IDP，即酿酒酵母中发现的 83 残基 IDR 转录因子 Ash1 和 CDK 抑制剂 Sic1 蛋白的 92 残基长 N 端区域，其平均构象特性的实验测量，即半径旋转和结构因子表明磷酸化后的变化可以忽略不计。在这里，我们表明，通过结合无监督机器学习和广泛的分子动力学（MD）轨迹对构象整体进行明智的剖析可以突出磷酸化和野生型IDP之间的关键差异和相似之处。特别是，我们使用自动编码器的潜在空间维度开发马尔可夫状态模型（MSM），并使用多微秒长的 MD 模拟轨迹进行训练。对磷酸化之前和之后状态之间的结构变化进行检查，捕获了它们的主链接触图、二级结构和扭转角的一些相似之处和差异。氢键分析表明，磷酸化不仅增加了氢键的数量，而且还改变了主链和侧链原子与磷酸化残基之间的氢键模式。我们还观察到，虽然磷酸化引入了盐桥，但阳离子-π相互作用消失了。磷酸化还提高了长距离疏水接触的可能性，还增强了与水分子的相互作用，并改善了水的局部结构，从几何顺序参数可以明显看出。对这些机器学习状态的观察提供了重要的见解，因为如果我们要了解 IDP 磷酸化在其生物学功能中的作用，就很难通过实验确定哪个是重要的。

"点击查看英文标题和摘要"

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation–π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.

更新日期：2023-10-31

点击分享查看原文

点击收藏

阅读更多本刊新发论文