Using LeDock as a docking tool for computational drug design

被引:48
|
作者
Liu, Ni [1 ]
Xu, Zhibin [1 ]
机构
[1] Beijing Inst Technol, Sch Chem & Chem Engn, Beijing 100081, Peoples R China
关键词
DOPAMINE D3 RECEPTOR;
D O I
10.1088/1755-1315/218/1/012143
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Computer-aided drug design (CADD) is an emerging tool for research and drug development process as it reduces the time taken for the process of drug development and expense. Molecular docking technology, as one of the main method, has been widely used in many fields of drug development. Based on the dopamine D-3 receptor target, this paper describes the method of molecular docking using LeDock software (Windows version) in combination with the docking process of eticlopride ligand and D-3 receptor. This method can predict the binding mode of ligands to proteins, including binding energy, binding sites and attractive interactions types. Four representative D-3 receptor ligands, including BP897, NGB2904, FAUC365 and SB277011A, were respectively docked with D-3 receptor by this method. By analyzing the docking results, we can conclude that the molecular docking method using LeDock software plays an important role in the drug design process.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Molecular Docking of Enzyme Inhibitors A COMPUTATIONAL TOOL FOR STRUCTURE-BASED DRUG DESIGN
    Rudnitskaya, Aleksandra
    Torok, Bela
    Torok, Marianna
    BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION, 2010, 38 (04) : 261 - 265
  • [2] Computational Docking as a Tool in Guiding the Drug Design of Rutaecarpine Derivatives as Potential SARS-CoV-2 Inhibitors
    Lin, Shengying
    Wang, Xiaoyang
    Tang, Roy Wai-Lun
    Duan, Ran
    Leung, Ka Wing
    Dong, Tina Ting-Xia
    Webb, Sarah E.
    Miller, Andrew L.
    Tsim, Karl Wah-Keung
    MOLECULES, 2024, 29 (11):
  • [3] Molecular modeling: A powerful tool for drug design and molecular docking
    Rama Rao Nadendla
    Resonance, 2004, 9 (5) : 51 - 60
  • [4] Carborane Clusters in Computational Drug Design: A Comparative Docking Evaluation Using AutoDock, FlexX, Glide, and Surflex
    Tiwari, Rohit
    Mahasenan, Kiran
    Pavlovicz, Ryan
    Li, Chenglong
    Tjarks, Werner
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2009, 49 (06) : 1581 - 1589
  • [5] Advancing the field of computational drug design using multicanonical molecular dynamics-based dynamic docking
    Gert-Jan Bekker
    Narutoshi Kamiya
    Biophysical Reviews, 2022, 14 : 1349 - 1358
  • [6] Advancing the field of computational drug design using multicanonical molecular dynamics-based dynamic docking
    Bekker, Gert-Jan
    Kamiya, Narutoshi
    BIOPHYSICAL REVIEWS, 2022, 14 (06) : 1349 - 1358
  • [7] Antiviral drug design using computational chemistry
    Clifton, Heather A.
    Ribblett, Jason W.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2009, 237
  • [8] Using PyMOL as a platform for computational drug design
    Yuan, Shuguang
    Chan, H. C. Stephen
    Hu, Zhenquan
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 2017, 7 (02)
  • [9] Standard reference simulations for docking and scoring: Enabling robust computational screening for drug design
    Oliver-Kapur, A. Jayne
    Chaka, Anne M.
    Gilson, Michael K.
    Schwarz, Frederick P.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2005, 230 : U1344 - U1345
  • [10] Molecular docking and drug design
    Irwin, J. J.
    Lorber, D. M.
    McGovern, S. L.
    Wei, B.
    Shoichet, B. K.
    ICCN 2002: INTERNATIONAL CONFERENCE ON COMPUTATIONAL NANOSCIENCE AND NANOTECHNOLOGY, 2002, : 50 - 51