相关实验视频

Updated: Jan 12, 2026

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Screening Traditional Chinese Medicine Compounds for Inhibiting UCHL3 Activity Based on Molecular Docking and Deubiquitinating Enzyme Probe Technology

Published on: November 22, 2024

通过整合性定量结构-活性关系建模,对接和分子动力学,以结构为导向的发现泛素特异性蛋白酶7抑制剂

Muhammad Shahab¹, Muhammad Waqas¹, Aamir Fahira¹

¹Dongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, 523710, China; Guangdong Medical University Key Laboratory of Big Data Mining and Precision Drug Design, Guangdong Provincial Key Laboratory for Research and Development of Natural Drugs, School of Pharmacy, Guangdong Medical University, Dongguan, 523808, China.

Computers in biology and medicine

|November 5, 2025

概括

我们使用QSAR和虚拟查确定了强大的Ubiquitin特定蛋白酶7 (USP7) 抑制剂. 像NPC472846这样的顶级化合物显示出癌症治疗开发的前景.

科学领域:

药用化学医学化学
计算机化药物发现技术
生物化学生物化学

背景情况:

乌比奎丁特异性蛋白酶7 (USP7) 是瘤原蛋白的关键调节剂,也是癌症中重要的治疗点.
针对USP7为开发新型抗癌疗法提供了一个有前途的战略.

研究的目的:

开发和验证用于预测USP7抑制剂的定量结构-活性关系 (QSAR) 模型.
通过虚拟查和分子模拟来识别新型,高亲和度的USP7抑制剂.

主要方法:

开发了使用837个抑制剂和随机森林算法的QSAR模型,实现了高预测精度 (R2=0.96,Q2=0.92).
对NPASS,TCM和ZINC数据库进行虚拟选.
经过验证的对接协议和使用分子对接,分子动力学模拟和MM-GBSA自由能量计算评估的顶级热点.

主要成果:

确定了几种强大的USP7抑制剂,包括NPC472846,TCM11676,TCM36723,ZINC18193314,和ZINC65536649.这些都是我们发现的.
NPC472846,ZINC65536649和TCM11676表现出强烈的结合亲缘关系,表现优于参考配体GNE6640.
分子动力学模拟证实了排名第一的化合物的稳定性和动态行为.

结论:

已识别的化合物,特别是NPC472846和ZINC65536649,是具有治疗潜力的强效USP7抑制剂.
这些发现为进一步的实验验证和开发针对USP7.7的新型癌症治疗方法提供了坚实的基础.

关键词:

癌症癌症癌症癌症人类的USP7 模拟MD的模拟方法机器学习机器学习分子对接是分子对接.在QSAR中使用QSAR.

更多相关视频

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

相关概念视频

Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

Covalently Linked Protein Regulators

Covalently Linked Protein Regulators

Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....

Structure-Activity Relationships and Drug Design

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...