The physical basis of model-free analysis of NMR relaxation data from proteins and complex fluids

The physical basis of model-free analysis of NMR relaxation data from proteins and complex fluids
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DOI:
10.1063/1.3269991
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发表时间:
2009-12-14
影响因子:
4.4
通讯作者:
Halle, Bertil
Halle, Bertil
中科院分区:
化学2区
文献类型:
--
作者:
Halle, Bertil

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核磁共振弛豫实验提供了大量关于大分子和有序流体中分子运动的信息。尽管有严格的自旋弛豫理论,但所研究系统的复杂性往往使有限数据集的解释具有挑战性和模糊性。为了使物理上有意义的信息被提取的数据,而不承诺详细的动力学模型,几个版本的无模型(MF)的数据分析方法已经开发出来。在过去的20年里,MF方法已被用于绝大多数的NMR弛豫研究的内部运动的蛋白质和其他大分子,它也发挥了重要作用,在胶体系统的研究。虽然MF方法几乎被普遍采用,但对其物理基础和有效性范围仍存在重大分歧。我们在此的目的是澄清这些问题。为此,我们首先提出了严格的推导三个著名的MF公式的时间相关函数的各向同性解决方案。这些推导比原来的推导更一般,从而大大扩展了MF方法的有效性范围。我们指出几个常见的误解,并解释所涉及的近似的物理意义。特别是,我们讨论了对称性的要求和动态解耦近似MF方法中起着关键作用。我们还推导出一个新的MF公式,适用于各向异性流体和固体,包括微晶蛋白质样品。所谓的缓慢松弛局部结构(SRLS)模型已被先进的MF方法,不需要动态解耦的内部和全球的运动作为一种替代。为了解决SRLS模型和MF方法的相对优点的现有争议,我们制定和解决一个平面版本的SRLS模型。该模型的解析解揭示了对称两体Smoluchowski方程应用于蛋白质动力学的非物理后果,从而驳斥了普遍认为SRLS模型比MF方法更准确的观点。因此,用这两种方法分析数据得到的不同结果并不表明内部运动和全球运动之间动力学耦合的重要性。最后,我们探讨了蛋白质动力学耦合的两个主要机制:扭矩介导的和摩擦介导的耦合。我们认为,通过具体的解析可解模型,扭矩介导的耦合(SRLS模型试图捕捉)是不重要的,因为可能耦合到全局运动的相对缓慢的内部运动往往是间歇性的在性格上,而摩擦介导耦合(SRLS模型和MF方法都没有结合)对于具有非结构化部分或柔性连接结构域的蛋白质可能是重要的。
NMR relaxation experiments have provided a wealth of information about molecular motions in macromolecules and ordered fluids. Even though a rigorous theory of spin relaxation is available, the complexity of the investigated systems often makes the interpretation of limited datasets challenging and ambiguous. To allow physically meaningful information to be extracted from the data without commitment to detailed dynamical models, several versions of a model-free (MF) approach to data analysis have been developed. During the past 2 decades, the MF approach has been used in the vast majority of all NMR relaxation studies of internal motions in proteins and other macromolecules, and it has also played an important role in studies of colloidal systems. Although the MF approach has been almost universally adopted, substantial disagreement remains about its physical foundations and range of validity. It is our aim here to clarify these issues. To this end, we first present rigorous derivations of the three well-known MF formulas for the time correlation function relevant for isotropic solutions. These derivations are more general than the original ones, thereby substantially extending the range of validity of the MF approach. We point out several common misconceptions and explain the physical significance of the approximations involved. In particular, we discuss symmetry requirements and the dynamical decoupling approximation that plays a key role in the MF approach. We also derive a new MF formula, applicable to anisotropic fluids and solids, including microcrystalline protein samples. The so-called slowly relaxing local structure (SRLS) model has been advanced as an alternative to the MF approach that does not require dynamical decoupling of internal and global motions. To resolve the existing controversy about the relative merits of the SRLS model and the MF approach, we formulate and solve a planar version of the SRLS model. The analytical solution of this model reveals the unphysical consequences of the symmetrical two-body Smoluchowski equation as applied to protein dynamics, thus refuting the widely held belief that the SRLS model is more accurate than the MF approach. The different results obtained by analyzing data with these two approaches therefore do not indicate the importance of dynamical coupling between internal and global motions. Finally, we explore the two principal mechanisms of dynamical coupling in proteins: torque-mediated and friction-mediated coupling. We argue by way of specific analytically solvable models that torque-mediated coupling (which the SRLS model attempts to capture) is unimportant because the relatively slow internal motions that might couple to the global motion tend to be intermittent (jumplike) in character, whereas friction-mediated coupling (which neither the SRLS model nor the MF approach incorporates) may be important for proteins with unstructured parts or flexibly connected domains.