Computational studies of tyrosinase inhibitors.

Q3 Biochemistry, Genetics and Molecular Biology Enzymes Pub Date : 2024-01-01 Epub Date: 2024-09-07 DOI:10.1016/bs.enz.2024.06.008
Alessandro Bonardi, Paola Gratteri
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引用次数: 0

Abstract

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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酪氨酸酶抑制剂的计算研究。
计算研究极大地促进了对酪氨酸酶(TYR)功能、机理和抑制作用的了解,加快了更有效、更具选择性的抑制剂的开发。本章概述了有关 TYR 抑制剂的硅学研究,强调了关键的抑制化学类型以及配体与靶标相互作用所涉及的主要残基。本章讨论了在 TYR 抑制剂开发中应用的工具,如基于结构的虚拟筛选、分子对接、人工智能和机器学习算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Enzymes
Enzymes Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
4.30
自引率
0.00%
发文量
10
期刊最新文献
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