虚拟筛选
数量结构-活动关系
药物发现
生物信息学
对接(动物)
计算机科学
计算生物学
药物设计
药品
生化工程
化学
生物信息学
机器学习
工程类
药理学
生物
医学
计算化学
基因
护理部
生物化学
作者
Mithun Rudrapal,Dipak Chetia
出处
期刊:Journal of Drug Delivery and Therapeutics
[Society of Pharmaceutical Tecnocrats]
日期:2020-07-15
卷期号:10 (4): 225-233
被引量:8
标识
DOI:10.22270/jddt.v10i4.4218
摘要
Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two basic approaches of computer-aided drug design (CADD) used in modern drug discovery and development programme. Virtual screening (or in silico screening) has been used in drug discovery program as a complementary tool to high throughput screening (HTS) to identify bioactive compounds. It is a preliminary tool of CADD that has gained considerable interest in the pharmaceutical research as a productive and cost-effective technology in search for novel molecules of medicinal interest. Docking is also used for virtual screening of new ligands on the basis of biological structures for identification of hits and generation of leads or optimization (potency/ property) of leads in drug discovery program. Hence, docking is approach of SBDD which plays an important role in rational designing of new drug molecules. Quantitative structure-activity relationship (QSAR) is an important chemometric tool in computational drug design. It is a common practice of LBDD. The study of QSAR gives information related to structural features and/or physicochemical properties of structurally similar molecules to their biological activity. In this paper, a comprehensive review on several computational tools of SBDD and LBDD such as virtual screening, molecular docking and QSAR methods of and their applications in the drug discovery and development programme have been summarized.
Keywords: Virtual screening, Molecular docking, QSAR, Drug discovery, Lead molecule
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