Institute of Molecular and Cellular Biosciences, University of Tokyo, Bunkyo, Tokyo 113-0032, Japan.
Division of Chemical Engineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531, Japan.
J Chem Phys. 2018 Mar 14;148(10):105101. doi: 10.1063/1.5019864.
To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.
为了辅助评估蛋白质对接预测(诱饵)生成的蛋白质-蛋白质复合物模型结构,我们之前开发了一种计算复合物结合自由能的方法。该方法结合了短(2ns)全原子分子动力学模拟与显式溶剂和能量表示(ER)中的溶液理论。我们表明,该方法成功选择了与天然复合物结构相似的结构(近天然诱饵)作为具有最低结合自由能的结构。在我们目前的工作中,我们将该方法(evERdock)应用于四个蛋白质-蛋白质复合物的 100 或 300 个模型结构。晶体结构和近天然诱饵显示出所有检查结构中最低的结合自由能,表明 evERdock 可以成功评估诱饵。还确定了一些诱饵,其界面均方根距离较低,但结合自由能相对较高。对蛋白质-蛋白质界面处的天然接触、氢键和盐桥分数的分析表明,这些诱饵在界面处的优化程度不足。通过包括界面水分子来优化界面周围的相互作用后,这些诱饵的结合自由能得到了提高。我们还研究了溶剂熵对结合自由能的影响,发现考虑熵项不一定会改善使用正常模型分析计算熵时对诱饵的评估。