基于3D药效团的精神活性物质预测模型
Construction of 3D-Pharmacophore Model for Psychoactive Substances Prediction
李佳维 1肖伟烈 1张兴杰 1刘昕 2刘美 2张芮菡1
作者信息
- 1. 云南大学药学院/教育部自然资源药物化学重点实验室/化学科学与工程学院,云南 昆明 650500
- 2. 云南警官学院智慧禁毒教育部重点实验室/毒品分析及禁毒技术公安部重点实验室/云南省智慧禁毒重点实验室,云南 昆明 650223
- 折叠
摘要
目的:探索快速甄别新精神活性物质的工具,为新精神活性物质结构预警、禁毒决策提供技术支撑.方法:基于《非法物质折算表》和DEA Controlled Substance两套管制物质数据集,构建了3D药效团模型.结果:本研究构建的5个药效团模型(D1C1-Ph6、D1C2-Ph5、D1C3-Ph1、D2C1-Ph6、D2C2-Ph7)在相应聚类结构的测试集化合物上均表现出良好的预测结果,其中三个外部样本都与D1C2-Ph5 有 0.9 以上的匹配值.结论:药效团模型能够超越骨架结构的限制,体现一系列生物活性分子共有的关键结构特征,从而辅助新精神活性物质的快速识别,防止危害性物质的快速泛滥.
Abstract
Objective:To explore the tools for rapid screening of new psychoactive substances,and to provide technical support for early warning of new psychoactive substances structure and drug control decision-making.Methods:The 3D pharmacophore models were constructed based on two sets of controlled substance datasets(Illegal Drug Conversion Table and DEA Controlled Substance).Results:The five pharmacophore models(D1C1-Ph6,D1C2-Ph5,D1C3-Ph1,D2C1-Ph6,D2C2-Ph7)constructed in this study all showed good prediction results on the test set compounds with corresponding cluster structure,and three of the external samples had matching values above 0.9 to D1C2-Ph5.Conclusion:Pharmacophore model can go beyond the limitation of skeleton structure and reflect the key structural features shared by a series of bioactive molecules,thereby assisting the rapid identification of new psychoactive substances and preventing the rapid emergence of hazardous substances.
关键词
新精神活性物质/药效团/禁毒/早期结构预警Key words
New psychoactive substances/Pharmacophore/Drug control/Early warning of structure引用本文复制引用
基金项目
云南大学大学生创新创业训练项目(202301122)
云南大学教育教学改革研究项目(202220)
云南警官学院校级科研项目(19A009)
云南省智慧禁毒重点实验室内部课题(ZHJDNB202301)
出版年
2024
NETL
NSTL
万方数据