Virtual Screening in Drug Design and Development

被引:0
|
作者
Sousa, Sergio F. [1 ]
Cerqueira, Nuno M. F. S. A. [1 ]
Fernandes, Pedro A. [1 ]
Ramos, Maria Joao [1 ]
机构
[1] Univ Porto, REQUIMTE, Dept Quim, Fac Ciencias, P-4169007 Oporto, Portugal
关键词
Drug design; docking; scoring; filters; compound libraries; druggability; protein flexibility; computational chemistry; PROTEIN-COUPLED RECEPTORS; MOLECULAR DOCKING; CHEMICAL DATABASES; LEAD OPTIMIZATION; LIGAND DOCKING; DISCOVERY; FLEXIBILITY; STRATEGIES; INHIBITORS; BETA;
D O I
暂无
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Virtual screening (VS) is presently a key component in the process of drug design and development. VS is normally regarded as the selection of likely drug candidates from large libraries of chemical structures by using computational methodologies. However, the generic definition of VS is significantly wider and may encompass many different methods. This review tries to present a comprehensive overview of the virtual screening process and of its importance in the present drug discovery and development paradigm. Following a focused contextualization on the subject, an introduction to the general types of virtual screening methodologies is presented. The main stages of a virtual screening campaign, including its strengths and limitations, are the subject of particular attention in this review. This analysis is complemented with a careful selection of VS success stories. Finally, a reflection on the future challenges of this promising methodology is drawn.
引用
下载
收藏
页码:442 / 453
页数:12
相关论文
共 50 条
  • [41] Virtual screening of chemical libraries for drug discovery
    Green, Darren V. S.
    EXPERT OPINION ON DRUG DISCOVERY, 2008, 3 (09) : 1011 - 1026
  • [42] STRATEGIES IN ANTIEPILEPTIC DRUG DEVELOPMENT - IS RATIONAL DRUG DESIGN SUPERIOR TO RANDOM SCREENING AND STRUCTURAL VARIATION
    LOSCHER, W
    SCHMIDT, D
    EPILEPSY RESEARCH, 1994, 17 (02) : 95 - 134
  • [43] High-throughput screening, virtual screening and rational drug design identify potent inhibitors for Pseudomonas aeruginosa RmlA
    Sarkar, Aurijit
    Gardiner, Mary
    Alphey, Magnus S.
    Gray, David
    Naismith, James
    Brenk, Ruth
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2012, 243
  • [44] A STATISTICAL DESIGN FOR DRUG SCREENING
    KING, EP
    BIOMETRICS, 1963, 19 (03) : 429 - &
  • [45] Molecular modeling of drug-DNA interactions: Virtual screening to structure-based design
    Ma, Dik-Lung
    Chan, Daniel Shiu-Hin
    Lee, Paul
    Kwan, Maria Hiu-Tung
    Leung, Chung-Hang
    BIOCHIMIE, 2011, 93 (08) : 1252 - 1266
  • [46] Computer especially AI-assisted drug virtual screening and design in traditional Chinese medicine
    Lin, Yumeng
    Zhang, You
    Wang, Dongyang
    Yang, Bowen
    Shen, Ying-Qiang
    PHYTOMEDICINE, 2022, 107
  • [47] Using machine learning method for drug design to develop a high-performance virtual screening
    Okada, Masato
    Kanamori, Katsutoshi
    Aoki, Shin
    Ohwada, Hayato
    Transactions of the Japanese Society for Artificial Intelligence, 2014, 29 (01) : 194 - 200
  • [48] Machine learning for hit discovery: Recent work in virtual screening and de novo drug design
    Amaro, Rommie
    Parks, Conor
    Gaieb, Zied
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 258
  • [49] Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening
    Yusuf Tanrikulu
    Gisbert Schneider
    Nature Reviews Drug Discovery, 2008, 7 : 667 - 677
  • [50] Combining ligand-based and structure-based drug design in the virtual screening arena
    Moro, Stefano
    Bacilieri, Magdalena
    Deflorian, Francesca
    EXPERT OPINION ON DRUG DISCOVERY, 2007, 2 (01) : 37 - 49