Shehu Amarda, Kavraki Lydia E, Clementi Cecilia
Department of Computer Science, Rice University, Houston, Texas 77005, USA.
Proteins. 2009 Sep;76(4):837-51. doi: 10.1002/prot.22390.
We propose a multiscale exploration method to characterize the conformational space populated by a protein at equilibrium. The method efficiently obtains a large set of equilibrium conformations in two stages: first exploring the entire space at a coarse-grained level of detail, then narrowing a refined exploration to selected low-energy regions. The coarse-grained exploration periodically adds all-atom detail to selected conformations to ensure that the search leads to regions which maintain low energies in all-atom detail. The second stage reconstructs selected low-energy coarse-grained conformations in all-atom detail. A low-dimensional energy landscape associated with all-atom conformations allows focusing the exploration to energy minima and their conformational ensembles. The lowest energy ensembles are enriched with additional all-atom conformations through further multiscale exploration. The lowest energy ensembles obtained from the application of the method to three different proteins correctly capture the known functional states of the considered systems.
我们提出了一种多尺度探索方法,以表征蛋白质在平衡状态下所占据的构象空间。该方法分两个阶段有效地获得大量平衡构象:首先在粗粒度细节水平上探索整个空间,然后将精细探索范围缩小到选定的低能区域。粗粒度探索会定期为选定的构象添加全原子细节,以确保搜索导向在全原子细节上保持低能量的区域。第二阶段以全原子细节重建选定的低能粗粒度构象。与全原子构象相关的低维能量景观允许将探索聚焦于能量最小值及其构象集合。通过进一步的多尺度探索,最低能量集合中富集了额外的全原子构象。将该方法应用于三种不同蛋白质所获得的最低能量集合正确地捕获了所考虑系统的已知功能状态。