ClusPro LigTBM: Automated Template-based Small Molecule Docking.
ClusPro LigTBM: Automated Template-based Small Molecule Docking.
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DOI：
10.1016/j.jmb.2019.12.011
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发表时间：
2020-05-15
影响因子：
5.6
通讯作者：
Kozakov D
中科院分区：
文献类型：
--
作者：
Alekseenko A;Kotelnikov S;Ignatov M;Egbert M;Kholodov Y;Vajda S;Kozakov D
在最近几轮盲蛋白-蛋白对接竞争CAPRI（预测相互作用的关键评估）中，基于模板的方法对于获得高质量模型至关重要。然而，这种自动化的方法很少用于蛋白质与小分子的对接。本文提出了一种基于模板的小分子对接算法。它搜索已知的具有部分覆盖目标配体的配体的配合物，进行构象采样和模板引导的能量精化以产生各种可能的姿态，然后对精化的姿态进行评分。该算法可作为自动化的ClusPro lightbm服务器使用。它允许用户将目标蛋白指定为PDB文件，并将配体指定为SMILES字符串。然后，服务器搜索模板并使用它们进行对接，向用户展示得分最高的姿势和他们的自信得分。该方法在Astex多样化基准测试以及D3R（药物设计数据资源）大挑战最后一轮的目标上进行了测试。该服务器作为ClusPro对接服务器套件的一部分公开提供，网址为https://ligtbm.cluspro.org/。
The template-based approach has been essential for achieving high-quality models in the recent rounds of blind protein-protein docking competition CAPRI (Critical Assessment of Predicted Interactions). However, few such automated methods exist for protein-small molecule docking. In this paper, we present an algorithm for template-based docking of small molecules. It searches for known complexes with ligands that have partial coverage of the target ligand, performs conformational sampling and template-guided energy refinement to produce a variety of possible poses, and then scores the refined poses. The algorithm is available as the automated ClusPro LigTBM server. It allows the user to specify the target protein as a PDB file and the ligand as a SMILES string. The server then searches for templates and uses them for docking, presenting the user with top-scoring poses and their confidence scores. The method is tested on the Astex Diverse benchmark, as well as on the targets from the last round of the D3R (Drug Design Data Resource) Grand Challenge. The server is publicly available as part of the ClusPro docking server suite at https://ligtbm.cluspro.org/.
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影响因子：
2.9
作者：
Kundrotas PJ;Anishchenko I;Badal VD;Das M;Dauzhenka T;Vakser IA
通讯作者：
Vakser IA
影响因子：
2.9
作者：
Lensink, Marc F.;Velankar, Sameer;Kryshtafovych, Andriy;Huang, Shen-You;Schneidman-Duhovny, Dina;Sali, Andrej;Segura, Joan;Fernandez-Fuentes, Narcis;Viswanath, Shruthi;Elber, Ron;Grudinin, Sergei;Popov, Petr;Neveu, Emilie;Lee, Hasup;Baek, Minkyung;Park, Sangwoo;Heo, Lim;Lee, Gyu Rie;Seok, Chaok;Qin, Sanbo;Zhou, Huan-Xiang;Ritchie, David W.;Maigret, Bernard;Devignes, Marie-Dominique;Ghoorah, Anisah;Torchala, Mieczyslaw;Chaleil, Raphael A. G.;Bates, Paul A.;Ben-Zeev, Efrat;Eisenstein, Miriam;Negi, Surendra S.;Weng, Zhiping;Vreven, Thom;Pierce, Brian G.;Borrman, Tyler M.;Yu, Jinchao;Ochsenbein, Francoise;Guerois, Raphael;Vangone, Anna;Rodrigues, Joao P. G. L. M.;van Zundert, Gydo;Nellen, Mehdi;Xue, Li;Karaca, Ezgi;Melquiond, Adrien S. J.;Visscher, Koen;Kastritis, Panagiotis L.;Bonvin, Alexandre M. J. J.;Xu, Xianjin;Qiu, Liming;Yan, Chengfei;Li, Jilong;Ma, Zhiwei;Cheng, Jianlin;Zou, Xiaoqin;Shen, Yang;Peterson, Lenna X.;Kim, Hyung-Rae;Roy, Amit;Han, Xusi;Esquivel-Rodriguez, Juan;Kihara, Daisuke;Yu, Xiaofeng;Bruce, Neil J.;Fuller, Jonathan C.;Wade, Rebecca C.;Anishchenko, Ivan;Kundrotas, Petras J.;Vakser, Ilya A.;Imai, Kenichiro;Yamada, Kazunori;Oda, Toshiyuki;Nakamura, Tsukasa;Tomii, Kentaro;Pallara, Chiara;Romero-Durana, Miguel;Jimenez-Garcia, Brian;Moal, Iain H.;Fernandez-Recio, Juan;Joung, Jong Young;Kim, Jong Yun;Joo, Keehyoung;Lee, Jooyoung;Kozakov, Dima;Vajda, Sandor;Mottarella, Scott;Hall, David R.;Beglov, Dmitri;Mamonov, Artem;Xia, Bing;Bohnuud, Tanggis;Del Carpio, Carlos A.;Ichiishi, Eichiro;Marze, Nicholas;Kuroda, Daisuke;Burman, Shourya S. Roy;Gray, Jeffrey J.;Chermak, Edrisse;Cavallo, Luigi;Oliva, Romina;Tovchigrechko, Andrey;Wodak, Shoshana J.
通讯作者：
Wodak, Shoshana J.
影响因子：
5.6
作者：
Moghadasi, Mohammad;Mirzaei, Hanieh;Kozakov, Dima
通讯作者：
Kozakov, Dima
影响因子：
14.8
作者：
Kozakov D;Hall DR;Xia B;Porter KA;Padhorny D;Yueh C;Beglov D;Vajda S
通讯作者：
Vajda S
影响因子：
14.9
作者：
Pons JL;Labesse G
通讯作者：
Labesse G