引用本文: | 余俊霖,李国菠.计算机辅助金属酶靶向药物发现的研究进展[J].中国现代应用药学,2022,39(21):2828-2833. |
| YU Junlin,LI Guobo.Advances in Computer-aided Metalloenzyme-targeted Drug Discovery[J].Chin J Mod Appl Pharm(中国现代应用药学),2022,39(21):2828-2833. |
|
摘要: |
金属酶是指含功能必需和(或)结构必需金属离子的酶的统称,广泛参与关键生理和病理过程,是非常重要的药物作用靶标群。金属结合位点的电子和几何结构具有复杂性、多变性和动态性等特点,使得计算机辅助药物设计存在挑战性。本文综述金属结合药效团,基于结构的药物设计,人工智能等策略应用于金属酶靶向药物发现的研究进展、优势和面临挑战,期望能为金属酶靶向创新药物研发提供借鉴和思考。 |
关键词: 金属酶 药效团 人工智能 药物发现 分子动力学 |
DOI:10.13748/j.cnki.issn1007-7693.2022.21.019 |
分类号:R914.2 |
基金项目:国家自然科学基金项目(82122065,82073698,81874291);四川省科技厅国际合作项目(2022YFH0027) |
|
Advances in Computer-aided Metalloenzyme-targeted Drug Discovery |
YU Junlin, LI Guobo
|
West China School of Pharmacy, Sichuan University, Chengdu 610041, China
|
Abstract: |
Metalloenzyme is a generic term normally used for the enzymes containing functionally and/or structurally essential metal ions, which are widely involved in key physiological and pathological processes, and are a colony of important drug targets. Electronic and geometric structures of metal-binding sites usually have complicated, flexible, dynamic features, which make computer-aided drug design more challenging. This paper summarizes the research progress, strengths and challenges for metal-binding pharmacophores, structure-based drug design, and artificial intelligence used in metalloenzyme-targeted drug discovery, with the hope to provide reference and reflection for high-efficient innovative drug discovery targeting metalloenzymes. |
Key words: metalloenzyme pharmacophore artificial intelligence drug discovery molecular dynamics |