Ligand and Structure-Based Drug Design (LBDD and SBDD): Promising Approaches to Discover New Drugs

虚拟筛选 计算机科学 药物发现 药品 过程(计算) 鉴定(生物学) 药物设计 数据科学 生化工程 工程类 风险分析(工程) 管理科学 医学 药理学 生物信息学 生物 操作系统 植物
作者
Igor José dos Santos Nascimento,Ricardo Olímpio de Moura
出处
期刊:BENTHAM SCIENCE PUBLISHERS eBooks [BENTHAM SCIENCE PUBLISHERS]
卷期号:: 1-32
标识
DOI:10.2174/9789815179934123010003
摘要

The drug discovery and development process are challenging and have undergone many changes over the last few years. Academic researchers and pharmaceutical companies invest thousands of dollars a year to search for drugs capable of improving and increasing people's life quality. This is an expensive, time-consuming, and multifaceted process requiring the integration of several fields of knowledge. For many years, the search for new drugs was focused on Target-Based Drug Design methods, identifying natural compounds or through empirical synthesis. However, with the improvement of molecular modeling techniques and the growth of computer science, Computer-Aided Drug Design (CADD) emerges as a promising alternative. Since the 1970s, its main approaches, Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD), have been responsible for discovering and designing several revolutionary drugs and promising lead and hit compounds. Based on this information, it is clear that these methods are essential in drug design campaigns. Finally, this chapter will explore approaches used in drug design, from the past to the present, from classical methods such as bioisosterism, molecular simplification, and hybridization, to computational methods such as docking, molecular dynamics (MD) simulations, and virtual screenings, and how these methods have been vital to the identification and design of promising drugs or compounds. Finally, we hope that this chapter guides researchers worldwide in rational drug design methods in which readers will learn about approaches and choose the one that best fits their research.

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