Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine in St. Louis, St. Louis, United States.
Center for the Science and Engineering of Living Systems, Washington University in St. Louis, St. Louis, United States.
Elife. 2020 May 29;9:e55132. doi: 10.7554/eLife.55132.
Myosin motor domains perform an extraordinary diversity of biological functions despite sharing a common mechanochemical cycle. Motors are adapted to their function, in part, by tuning the thermodynamics and kinetics of steps in this cycle. However, it remains unclear how sequence encodes these differences, since biochemically distinct motors often have nearly indistinguishable crystal structures. We hypothesized that sequences produce distinct biochemical phenotypes by modulating the relative probabilities of an ensemble of conformations primed for different functional roles. To test this hypothesis, we modeled the distribution of conformations for 12 myosin motor domains by building Markov state models (MSMs) from an unprecedented two milliseconds of all-atom, explicit-solvent molecular dynamics simulations. Comparing motors reveals shifts in the balance between nucleotide-favorable and nucleotide-unfavorable P-loop conformations that predict experimentally measured duty ratios and ADP release rates better than sequence or individual structures. This result demonstrates the power of an ensemble perspective for interrogating sequence-function relationships.
肌球蛋白马达结构域尽管共享一个共同的机械化学循环，但却执行着极其多样的生物学功能。马达通过调整这个循环步骤的热力学和动力学来适应其功能。然而，序列如何编码这些差异仍然不清楚，因为生化上不同的马达通常具有几乎无法区分的晶体结构。我们假设，序列通过调节不同功能角色的构象组合的相对概率来产生不同的生化表型。为了验证这一假设，我们通过从超过两毫秒的全原子、显式溶剂分子动力学模拟中构建马氏状态模型（MSM），对 12 个肌球蛋白马达结构域的构象分布进行了建模。对马达的比较揭示了核苷酸有利和核苷酸不利的 P 环构象之间平衡的转变，这种转变比序列或单个结构更能预测实验测量的占空比和 ADP 释放速率。这一结果证明了从整体角度研究序列-功能关系的强大。
