Tensor Train Global Optimization: Application to Docking in the Configuration Space with a Large Number of Dimensionsстатья

Информация о цитировании статьи получена из Scopus
Дата последнего поиска статьи во внешних источниках: 24 апреля 2018 г.

Работа с статьей


[1] Tensor train global optimization: Application to docking in the configuration space with a large number of dimensions / A. V. Sulimov, D. A. Zheltkov, I. V. Oferkin et al. // Supercomputing. Third Russian Supercomputing Days, RuSCDays 2017, Moscow, Russia, September 25–26, 2017, Revised Selected Papers / Ed. by В. В. Воеводин, С. И. Соболев. — Vol. 793 of Communications in Computer and Information Science (CCIS). — Springer Cham, 2017. — P. 1–532. The novel docking algorithm is presented and it 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 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. 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. 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 dozen of protein moveable atoms – up to 157 degrees of freedom. [ DOI ]

Публикация в формате сохранить в файл сохранить в файл сохранить в файл сохранить в файл сохранить в файл сохранить в файл скрыть