利用虚拟筛选方法鉴定具有纳摩尔效力的新型酪氨酸酶抑制剂

IF 2.9 4区 医学 Q3 CHEMISTRY, MEDICINAL Current topics in medicinal chemistry Pub Date : 2024-10-02 DOI:10.2174/0115680266333084240918051716
Guohong Liu, Shihao Liu, Xiaofang Li, Tegexibaiyin Wang
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引用次数: 0

摘要

简介色素沉着症是由于色素黑色素在酪氨酸酶的催化下生成过多所致。治疗这些疾病需要新型酪氨酸酶抑制剂:为了发现新的抑制剂,我们对包含 14 亿个化合物的 ZINC20 库进行了虚拟筛选。通过对药物相似性、ADMET 特性和合成可得性的初步筛选,我们将库中的化合物减少到 10,217 个。对这个子集进行的定量结构-活性关系(QSAR)建模预测了几种化学支架的纳摩尔抑制效力。分子对接比较研究和严格的结合能计算根据预测的与酪氨酸酶的强结合亲和力和模式,进一步确定了四个含半胱氨酸二肽化合物的优先次序:结果:长达微秒的分子动力学模拟为了解抑制剂与酶结合相互作用的稳定性提供了更多的原子观点。这一综合计算工作流程有效采样了一个极大的化学空间,发现了四种半最大抑制浓度值低于 10 nM 的新型酪氨酸酶抑制剂:总之,这展示了虚拟筛选和多方面计算技术的威力,通过有效采样化学空间,加快了从海量化合物库中发现强效生物活性配体的速度。
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Identification of Novel Tyrosinase Inhibitors with Nanomolar Potency Using Virtual Screening Approaches.

Introduction: Hyperpigmentation disorders are caused by excess production of the pigment melanin, catalyzed by the enzyme tyrosinase. Novel tyrosinase inhibitors are needed as therapeutic agents to treat these conditions.

Method: To discover new inhibitors, we performed a virtual screening of the ZINC20 library containing 1.4 billion compounds. An initial filter for drug-likeness, ADMET properties, and synthetic accessibility reduced the library to 10,217 hits. Quantitative structure-activity relationship (QSAR) modeling of this subset predicted nanomolar inhibitory potency for several chemical scaffolds. Comparative molecular docking studies and rigorous binding energy calculations further prioritized four cysteine-containing dipeptide compounds based on predicted strong binding affinity and mode to tyrosinase.

Results: Microsecond-long molecular dynamics simulations provided additional atomistic insights into the stability of inhibitor-enzyme binding interactions. This integrated computational workflow effectively sampled an extremely large chemical space to discover four novel tyrosinase inhibitors with half-maximal inhibitory concentration values below 10 nM.

Conclusion: Overall, this demonstrates the power of virtual screening and multi-faceted computational techniques to accelerate the discovery of potent bioactive ligands from massive compound libraries by efficiently sampling chemical space.

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来源期刊
CiteScore
6.40
自引率
2.90%
发文量
186
审稿时长
3-8 weeks
期刊介绍: Current Topics in Medicinal Chemistry is a forum for the review of areas of keen and topical interest to medicinal chemists and others in the allied disciplines. Each issue is solely devoted to a specific topic, containing six to nine reviews, which provide the reader a comprehensive survey of that area. A Guest Editor who is an expert in the topic under review, will assemble each issue. The scope of Current Topics in Medicinal Chemistry will cover all areas of medicinal chemistry, including current developments in rational drug design, synthetic chemistry, bioorganic chemistry, high-throughput screening, combinatorial chemistry, compound diversity measurements, drug absorption, drug distribution, metabolism, new and emerging drug targets, natural products, pharmacogenomics, and structure-activity relationships. Medicinal chemistry is a rapidly maturing discipline. The study of how structure and function are related is absolutely essential to understanding the molecular basis of life. Current Topics in Medicinal Chemistry aims to contribute to the growth of scientific knowledge and insight, and facilitate the discovery and development of new therapeutic agents to treat debilitating human disorders. The journal is essential for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important advances.
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