计算机辅助
药物发现
药品
抗癌药
过程(计算)
癌症治疗
计算机科学
医学
风险分析(工程)
药理学
癌症
生物信息学
生物
操作系统
内科学
程序设计语言
作者
Maira Rubí Segura Campos,Nidia del Carmen Quintal Bojórquez
出处
期刊:Current Cancer Drug Targets
[Bentham Science]
日期:2022-07-06
卷期号:23 (5): 333-345
被引量:18
标识
DOI:10.2174/1568009622666220705104249
摘要
In the last decade, cancer has been a leading cause of death worldwide. Despite the impressive progress in cancer therapy, firsthand treatments are not selective to cancer cells and cause serious toxicity. Thus, the design and development of selective and innovative small molecule drugs is of great interest, particularly through in silico tools.The aim of this review is to analyze different subsections of computer-aided drug design (CADD) in the process of discovering anticancer drugs.Articles from the 2008-2021 timeframe were analyzed and based on the relevance of the information and the JCR of its journal of precedence, were selected to be included in this review.The information collected in this study highlights the main traditional and novel CADD approaches used in anticancer drug discovery, its sub-segments, and some applied examples. Throughout this review, the potential use of CADD in drug research and discovery, particularly in the field of oncology, is evident due to the many advantages it presents.CADD approaches play a significant role in the drug development process since they allow a better administration of resources with successful results and a promising future market and clinical wise.
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