Combined strategies in structure-based virtual screening

被引:79
|
作者
Wang, Zhe [1 ]
Sun, Huiyong [1 ]
Shen, Chao [1 ]
Hu, Xueping [1 ]
Gao, Junbo [1 ]
Li, Dan [1 ]
Cao, Dongsheng [2 ]
Hou, Tingjun [1 ]
机构
[1] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou Inst Innovat Med, Hangzhou 310058, Zhejiang, Peoples R China
[2] Cent South Univ, Xiangya Sch Pharmaceut Sci, Changsha 410004, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
BOLTZMANN SURFACE-AREA; PROTEIN-LIGAND DOCKING; INDUCED FIT DOCKING; MOLECULAR DOCKING; SCORING FUNCTIONS; DRUG DISCOVERY; CONFORMATIONAL SELECTION; HIGH-THROUGHPUT; BINDING-ENERGIES; ENSEMBLE DOCKING;
D O I
10.1039/c9cp06303j
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines. As a powerful computational approach for the identification of hits with novel structural scaffolds, structure-based virtual screening (SBVS) has exhibited a remarkably increasing influence in the early stages of drug discovery. During the past decade, a variety of techniques and algorithms have been proposed and tested with different purposes in the scope of SBVS. Although SBVS has been a common and proven technology, it still shows some challenges and problems that are needed to be addressed, where the negative influence regardless of protein flexibility and the inaccurate prediction of binding affinity are the two major challenges. Here, focusing on these difficulties, we summarize a series of combined strategies or workflows developed by our group and others. Furthermore, several representative successful applications from recent publications are also discussed to demonstrate the effectiveness of the combined SBVS strategies in drug discovery campaigns.
引用
收藏
页码:3149 / 3159
页数:11
相关论文
共 50 条
  • [31] Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches
    Vazquez, Javier
    Lopez, Manel
    Gibert, Enric
    Herrero, Enric
    Luque, F. Javier
    MOLECULES, 2020, 25 (20):
  • [32] Improved method of structure-based virtual screening based on ensemble learning
    Li, Jin
    Liu, WeiChao
    Song, Yongping
    Xia, JiYi
    RSC ADVANCES, 2020, 10 (13) : 7609 - 7618
  • [33] SpaceHASTEN: A Structure-Based Virtual Screening Tool for Nonenumerated Virtual Chemical Libraries
    Kalliokoski, Tuomo
    Turku, Ainoleena
    Kasnanen, Heikki
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2024, 65 (01) : 125 - 132
  • [34] A comparison of structure-based and shape-based tools for virtual screening
    Hawkins, Paul C. D.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2006, 231
  • [35] Ligand bias of scoring functions in structure-based virtual screening
    Jacobsson, M
    Karlén, A
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2006, 46 (03) : 1334 - 1343
  • [36] Towards Effective Consensus Scoring in Structure-Based Virtual Screening
    Phuong, Do Nhat
    Flower, Darren R. R.
    Chattopadhyay, Subhagata
    Chattopadhyay, Amit K. K.
    INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES, 2023, 15 (01) : 131 - 145
  • [37] Towards improving compound selection in structure-based virtual screening
    Waszkowycz, Bohdan
    DRUG DISCOVERY TODAY, 2008, 13 (5-6) : 219 - 226
  • [38] Utility of the Morgan Fingerprint in Structure-Based Virtual Ligand Screening
    Zhou, Hongyi
    Skolnick, Jeffrey
    JOURNAL OF PHYSICAL CHEMISTRY B, 2024, 128 (22): : 5363 - 5370
  • [39] Ligand docking and virtual screening in structure-based drug discovery
    Cavasotto, Claudio N.
    FROM PHYSICS TO BIOLOGY: THE INTERFACE BETWEEN EXPERIMENT AND COMPUTATION, 2006, 851 : 34 - 49
  • [40] Structure-based virtual screening for TAR RNA ligands.
    Filikov, AV
    Abagyan, RA
    James, TL
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1997, 214 : 235 - COMP