Sources of and solutions to problems in the refinement of protein NMR structures against torsion angle potentials of mean force
Sources of and solutions to problems in the refinement of protein NMR structures against torsion angle potentials of mean force
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DOI：
10.1006/jmre.2000.2142
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发表时间：
2000-10-01
影响因子：
2.2
通讯作者：
Clore, GM
中科院分区：
文献类型：
--
作者：
Kuszewski, J;Clore, GM
通常情况下，通过NMR确定的蛋白质和核酸结构中的大量扭转角（主链和侧链）在物理上不太可能和能量上不利的构象中被发现。我们先前已经提出了一个数据库衍生的潜在的平均力，包括一维，二维，三维和四维的潜在表面，其描述了各种扭转角组合的可能性，以偏置构象采样在模拟退火细化过程中向那些区域填充在非常高的分辨率（小于或等于1.75埃）的晶体结构。现在我们注意到这种方法最初实现的一个缺点：即它施加在原子上的力非常粗糙。当实验约束的密度较低时，这种粗糙度既会阻碍收敛到扭转角空间中常见的区域，又会减少整体构象采样。在本文中，我们描述了一种修改，通过用多维高斯函数的和替换原始的势面，完全消除了这些问题。用新的高斯实现改进的结构现在同时享有出色的全局采样和出色的扭转角局部选择。
It is often the case that a substantial number of torsion angles (both backbone and sidechain) in structures of proteins and nucleic acids determined by NMR are found in physically unlikely and energetically unfavorable conformations. We have previously proposed a database-derived potential of mean force comprising one-, two-, three-, and four-dimensional potential surfaces which describe the likelihood of various torsion angle combinations to bias conformational sampling during simulated annealing refinement toward those regions that are populated in very high resolution (less than or equal to 1.75 Angstrom) crystal structures. We now note a shortcoming of our original implementation of this approach: namely, the forces it places on atoms are very rough. When the density of experimental restraints is low, this roughness can both hinder convergence to commonly populated regions of torsion angle space and reduce overall conformational sampling, In this paper we describe a modification that completely eliminates these problems by replacing the original potential surfaces by a sum of multidimensional Gaussian functions. Structures refined with the new Gaussian implementation now simultaneously enjoy excellent global sampling and excellent local choices of torsion angles.