虚拟筛选
生物信息学
酪氨酸酶
计算生物学
对接(动物)
背景(考古学)
化学
计算机科学
机制(生物学)
化学信息学
人工智能
药效团
生物化学
生物
酶
计算化学
基因
医学
物理
古生物学
护理部
量子力学
作者
Alessandro Bonardi,Paola Gratteri
出处
期刊:The Enzymes
日期:2024-01-01
卷期号:: 191-229
标识
DOI:10.1016/bs.enz.2024.06.008
摘要
Computational studies have significantly advanced the understanding of tyrosinase (TYR) function, mechanism, and inhibition, accelerating the development of more effective and selective inhibitors. This chapter provides an overview of in silico studies on TYR inhibitors, emphasizing key inhibitory chemotypes and the main residues involved in ligand-target interactions. The chapter discusses tools applied in the context of TYR inhibitor development, e.g., structure-based virtual screening, molecular docking, artificial intelligence, and machine learning algorithms.
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