Sulimov Alexey V, Zheltkov Dmitry A, Oferkin Igor V, Kutov Danil C, Katkova Ekaterina V, Tyrtyshnikov Eugene E, Sulimov Vladimir B
Dimonta, Ltd, Nagornaya Street 15, Bldg. 8, Moscow 117186, Russia; Research Computer Center, Moscow State University, Leninskie Gory 1, Bldg. 4, Moscow 119992, Russia.
Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University, Leninskie Gory 1, Bldg. 52, Moscow 119992, Russia.
Comput Struct Biotechnol J. 2017 Mar 3;15:275-285. doi: 10.1016/j.csbj.2017.02.004. eCollection 2017.
We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.
我们提出了一种基于张量列车分解和TT-Cross全局优化的新型对接算法。该算法应用于具有柔性配体和可移动蛋白质原子的对接问题。在真空中的MMFF94力场框架内计算蛋白质-配体复合物的能量。未使用预先计算的探针配体原子在目标蛋白质原子场中的能量势网格。对于任何给定构型的蛋白质-配体复合物的能量,直接使用MMFF94力场进行计算,无需任何拟合参数。系统坐标的构象空间由配体整体的平移和旋转、配体扭转以及所选目标蛋白质原子的笛卡尔坐标形成。在对接过程中同时且同等地考虑蛋白质和配体原子的流动性。该算法在新型并行对接SOL-P程序中实现,并给出了其对一组30个蛋白质-配体复合物的性能结果。研究了对接定位精度作为对接算法参数和蛋白质可移动原子数量的函数的依赖性。结果表明,蛋白质原子的流动性提高了对接定位精度。SOL-P程序能够将柔性配体对接至具有数十个蛋白质可移动原子的目标蛋白质的活性位点:在罗蒙诺索夫超级计算机上使用4700 CPU∗h,在157维的搜索空间中正确地将天然结晶配体构象作为全局能量最小值找到。