Uyar Arzu, Kantarci-Carsibasi Nigar, Haliloglu Turkan, Doruker Pemra
Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey.
Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey.
Biophys J. 2014 Jun 17;106(12):2656-66. doi: 10.1016/j.bpj.2014.05.017.
We performed a detailed analysis of conformational transition pathways for a set of 10 proteins, which undergo large hinge-bending-type motions with 4-12 Å RMSD (root mean-square distance) between open and closed crystal structures. Anisotropic network model-Monte Carlo (ANM-MC) algorithm generates a targeted pathway between two conformations, where the collective modes from the ANM are used for deformation at each iteration and the conformational energy of the deformed structure is minimized via an MC algorithm. The target structure was approached successfully with an RMSD of 0.9-4.1 Å when a relatively low cutoff radius of 10 Å was used in ANM. Even though one predominant mode (first or second) directed the open-to-closed conformational transition, changes in the dominant mode character were observed for most cases along the transition. By imposing radius of gyration constraint during mode selection, it was possible to predict the closed structure for eight out of 10 proteins (with initial 4.1-7.1 Å and final 1.7-2.9 Å RMSD to target). Deforming along a single mode leads to most successful predictions. Based on the previously reported free energy surface of adenylate kinase, deformations along the first mode produced an energetically favorable path, which was interestingly facilitated by a change in mode shape (resembling second and third modes) at key points. Pathway intermediates are provided in our database of conformational transitions (http://safir.prc.boun.edu.tr/anmmc/method/1).
我们对一组10种蛋白质的构象转变途径进行了详细分析,这些蛋白质经历了大的铰链弯曲型运动,开放和闭合晶体结构之间的均方根偏差(RMSD)为4 - 12埃。各向异性网络模型 - 蒙特卡罗(ANM - MC)算法生成两个构象之间的目标途径,其中ANM的集体模式用于每次迭代的变形,并且通过MC算法使变形结构的构象能量最小化。当在ANM中使用相对较低的截止半径10埃时,成功逼近目标结构,RMSD为0.9 - 4.1埃。尽管一种主要模式(第一或第二种)主导了从开放到闭合的构象转变,但在大多数情况下,沿着转变过程观察到主导模式特征的变化。通过在模式选择期间施加回转半径约束,可以预测10种蛋白质中的8种的闭合结构(与目标结构的初始RMSD为4.1 - 7.1埃,最终RMSD为1.7 - 2.9埃)。沿着单一模式变形导致最成功的预测。基于先前报道的腺苷酸激酶的自由能表面,沿着第一模式的变形产生了能量上有利的途径,有趣的是,在关键点处模式形状的变化(类似于第二和第三模式)促进了这一途径。我们的构象转变数据库(http://safir.prc.boun.edu.tr/anmmc/method/1)中提供了途径中间体。