Gong Haipeng, Fleming Patrick J, Rose George D
T. C. Jenkins Department of Biophysics, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA.
Proc Natl Acad Sci U S A. 2005 Nov 8;102(45):16227-32. doi: 10.1073/pnas.0508415102. Epub 2005 Oct 26.
Reconstructing a protein in three dimensions from its backbone torsion angles is an ongoing challenge because minor inaccuracies in these angles produce major errors in the structure. As a familiar example, a small change in an elbow angle causes a large displacement at the end of your arm, the longer the arm, the larger the displacement. Even accurate knowledge of the backbone torsions and Psi is insufficient, owing to the small, but cumulative, deviations from ideality in backbone planarity, which, if ignored, also lead to major errors in the structure. Against this background, we conducted a computational experiment to assess whether protein conformation can be determined from highly approximate backbone torsion angles, the kind of information that is now obtained readily from NMR. Specifically, backbone torsion angles were taken from proteins of known structure and mapped into 60 degrees x 60 degrees grid squares, called mesostates. Side-chain atoms beyond the beta -carbon were discarded. A mesostate representation of the protein backbone was then used to extract likely candidates from a fragment library of mesostate pentamers, followed by Monte Carlo-based fragment-assembly simulations to identify stable conformations compatible with the given mesostate sequence. Only three simple energy terms were used to gauge stability: molecular compaction, soft-sphere repulsion, and hydrogen bonding. For the six representative proteins described here, stable conformers can be partitioned into a remarkably small number of topologically distinct clusters. Among these, the native topology is found with high frequency and can be identified as the cluster with the most favorable energy.
根据蛋白质主链扭转角重建其三维结构一直是一项具有挑战性的任务,因为这些角度的微小不准确会在结构上产生重大误差。举个常见的例子,肘部角度的微小变化会导致手臂末端的大幅位移,手臂越长,位移越大。即使准确知道主链扭转角和Ψ角也不够,因为主链平面性与理想状态存在微小但累积的偏差,如果忽略这些偏差,也会导致结构上的重大误差。在此背景下,我们进行了一项计算实验,以评估能否从高度近似的主链扭转角确定蛋白质构象,这种信息现在可以很容易地从核磁共振(NMR)中获得。具体来说,主链扭转角取自已知结构的蛋白质,并映射到60度×60度的网格方块中,称为中间状态。β碳以外的侧链原子被舍弃。然后,利用蛋白质主链的中间状态表示从中间状态五聚体的片段库中提取可能的候选物,接着进行基于蒙特卡洛的片段组装模拟,以识别与给定中间状态序列兼容的稳定构象。仅使用三个简单的能量项来衡量稳定性:分子紧密性、软球排斥和氢键。对于此处描述的六种代表性蛋白质,稳定构象可以被划分为数量非常少的拓扑上不同的簇。其中,天然拓扑结构出现的频率很高,可以被识别为能量最有利的簇。