文献类型： 外文期刊
作者： Lu, Tian 1 ; Li, Tong 1 ; Wu, Meng-Ke 1 ; Zheng, Chi-Chong 1 ; He, Xue-Mei 2 ; Zhu, Hai-Liang 3 ; Li, Li 2 ; Man, Ruo-Jun 1 ;
作者机构： 1.Guangxi Univ Nationalities, Guangxi Key Lab Polysaccharide Mat & Modificat, Nanning, Peoples R China
2.Guangxi Acad Agr Sci, Agrofood Sci & Technol Res Inst, Nanning, Peoples R China
3.Nanjing Univ, Sch Life Sci, Nanjing, Peoples R China
4.Guangxi Univ Nationalities, Guangxi Key Lab Polysaccharide Mat & Modificat, Nanning 530006, Guangxi, Peoples R China
关键词： Molecular simulation; Target inhibitors; Cancer invasion; Medicinal Chemistry
期刊名称：EXPERT OPINION ON DRUG DISCOVERY （ 影响因子：6.3； 五年影响因子：6.2 ）
ISSN： 1746-0441
年卷期： 2023 年 18 卷 12 期
页码：
收录情况： SCI
摘要： IntroductionComputer-aided drug design (CADD) is a computational approach used to discover, develop, and analyze drugs and active molecules with similar biochemical properties. Molecular simulation technology has significantly accelerated drug research and reduced manufacturing costs. It is an optimized drug discovery method that greatly improves the efficiency of novel drug development processes.AreascoveredThis review discusses the development of molecular simulations of effective cancer inhibitors and traces the main outcomes of in silico studies by introducing representative categories of six important anticancer targets. The authors provide views on this topic from the perspective of both medicinal chemistry and artificial intelligence, indicating the major challenges and predicting trends.Expert opinionThe goal of introducing CADD into cancer treatment is to realize a highly efficient, accurate, and desired approach with a high success rate for identifying potent drug candidates. However, the major challenge is the lack of a sophisticated data-filtering mechanism to verify bottom data from mixed-quality references. Consequently, despite the continuous development of algorithms, computer power, and interface optimization, specific data filtering mechanisms will become an urgent and crucial issue in the future.
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