Department of Biochemistry, School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
J Mol Biol. 2011 Jan 28;405(4):1079-100. doi: 10.1016/j.jmb.2010.08.058. Epub 2010 Oct 7.
Because the space of folded protein structures is highly degenerate, with recurring secondary and tertiary motifs, methods for representing protein structure in terms of collective physically relevant coordinates are of great interest. By collapsing structural diversity to a handful of parameters, such methods can be used to delineate the space of designable structures (i.e., conformations that can be stabilized with a large number of sequences)-a crucial task for de novo protein design. We first demonstrate this on natural α-helical coiled coils using the Crick parameterization. We show that over 95% of known coiled-coil structures are within 1-Å C(α) root mean square deviation of a Crick-ideal backbone. Derived parameters show that natural geometric space of coiled coils is highly restricted and can be represented by "allowed" conformations amidst a potential continuum of conformers. Allowed structures have (1) restricted axial offsets between helices, which differ starkly between parallel and anti-parallel structures; (2) preferred superhelical radii, which depend linearly on the oligomerization state; (3) pronounced radius-dependent a- and d-position amino acid propensities; and (4) discrete angles of rotation of helices about their axes, which are surprisingly independent of oligomerization state or orientation. In all, we estimate the space of designable coiled-coil structures to be reduced at least 160-fold relative to the space of geometrically feasible structures. To extend the benefits of structural parameterization to other systems, we developed a general mathematical framework for parameterizing arbitrary helical structures, which reduces to the Crick parameterization as a special case. The method is successfully validated on a set of non-coiled-coil helical bundles, frequent in channels and transporter proteins, which show significant helix bending but not supercoiling. Programs for coiled-coil parameter fitting and structure generation are provided via a web interface at http://www.gevorggrigoryan.com/cccp/, and code for generalized helical parameterization is available upon request.
由于折叠蛋白质结构的空间高度简并,具有反复出现的二级和三级结构模体,因此用集体物理相关坐标来表示蛋白质结构的方法非常有趣。通过将结构多样性折叠到少数几个参数中,可以使用这些方法来描绘可设计结构的空间(即可以用大量序列稳定的构象)-这是从头设计蛋白质的关键任务。我们首先使用克里克参数化在天然α-螺旋卷曲螺旋上演示了这一点。我们表明,超过 95%的已知卷曲螺旋结构在 1-Å C(α)均方根偏差内与克里克理想骨架一致。衍生参数表明,天然卷曲螺旋的几何空间受到高度限制,可以通过潜在连续构象中的“允许”构象来表示。允许的结构具有(1)螺旋之间的轴向偏移受限,平行和反平行结构之间的差异很大;(2)优选的超螺旋半径,其线性依赖于寡聚化状态;(3)明显依赖于半径的α-和 d-位置氨基酸倾向;(4)螺旋围绕其轴的旋转角度离散,这令人惊讶地独立于寡聚化状态或取向。总之,我们估计可设计的卷曲螺旋结构的空间至少减少了 160 倍,相对于几何上可行的结构空间。为了将结构参数化的好处扩展到其他系统,我们开发了一种用于参数化任意螺旋结构的通用数学框架,该框架简化为克里克参数化作为特例。该方法在一组非卷曲螺旋束上成功得到验证,这些螺旋束在通道和转运蛋白中经常出现,它们显示出明显的螺旋弯曲而不是超螺旋。卷曲螺旋参数拟合和结构生成程序可通过 web 界面在 http://www.gevorggrigoryan.com/cccp/ 获得,并且可根据要求提供通用螺旋参数化的代码。