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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.
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计算机辅助金属酶靶向药物发现的研究进展
余俊霖, 李国菠
四川大学华西药学院, 成都 610041
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
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