Center for Theoretical Biological Physics and Department of Physics, Rice University, Houston, Texas 77005, USA.
J Phys Chem B. 2012 Jun 14;116(23):6880-8. doi: 10.1021/jp212623d. Epub 2012 Apr 26.
Evolution has selected a protein's sequence to be consistent with the native state geometry, as this configuration must be both thermodynamically stable and kinetically accessible to prevent misfolding and loss of function. In simple protein geometries, such as coiled-coil helical bundles, symmetry produces a competing, globally different, near mirror image with identical secondary structure and similar native contact interactions. Experimental techniques such as circular dichroism, which rely on probing secondary structure content, cannot readily distinguish these folds. Here, we want to clarify whether the native fold and mirror image are energetically competitive by investigating the free energy landscape of three-helix bundles. To prevent a bias from a specific computational approach, the present study employs the structure prediction forcefield PFF01/02, explicit solvent replica exchange molecular dynamics (REMD) with the Amber94 forcefield, and structure-based simulations based on energy landscape theory. We observe that the native fold and its mirror image have a similar enthalpic stability and are thermodynamically competitive. There is evidence that the mirror fold has faster folding kinetics and could function as a kinetic trap. All together, our simulations suggest that mirror images might not just be a computational annoyance but are competing folds that might switch depending on environmental conditions or functional considerations.
进化选择了蛋白质序列使其与天然状态的几何形状一致,因为这种构象必须在热力学上稳定并且在动力学上可及,以防止错误折叠和功能丧失。在简单的蛋白质几何形状中,如螺旋卷曲的螺旋束,对称会产生一种竞争的、全局不同的、近镜像,具有相同的二级结构和类似的天然接触相互作用。依赖于探测二级结构含量的实验技术,如圆二色性,不能轻易区分这些折叠。在这里,我们希望通过研究三螺旋束的自由能景观来澄清天然折叠和镜像折叠是否在能量上具有竞争力。为了防止特定计算方法的偏差,本研究采用了结构预测力场 PFF01/02、基于能量景观理论的 Amber94 力场的显式溶剂复制交换分子动力学 (REMD) 和基于结构的模拟。我们观察到天然折叠及其镜像具有相似的焓稳定性,并且在热力学上具有竞争力。有证据表明,镜像折叠具有更快的折叠动力学,并且可以作为动力学陷阱。总的来说,我们的模拟表明镜像可能不仅仅是一个计算上的麻烦,而是具有竞争力的折叠,可能会根据环境条件或功能考虑而发生变化。