• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

定量构效关系的开发与应用指南。

Guidelines for developing and using quantitative structure-activity relationships.

作者信息

Walker John D, Jaworska Joanna, Comber Mike H I, Schultz T Wayne, Dearden John C

机构信息

TSCA Interagency Testing Committee, U.S. Environmental Protection Agency (7401M), Washington, DC 20460, USA.

出版信息

Environ Toxicol Chem. 2003 Aug;22(8):1653-65. doi: 10.1897/01-627.

DOI:10.1897/01-627
PMID:12924568
Abstract

Numerous quantitative structure-activity relationships (QSARs) have been developed to predict properties, fate, and effects of mostly discrete organic chemicals. As the demand for different types of regulatory testing increases and the cost of experimental testing escalates, there is a need to evaluate the use of QSARs and provide some guidance to avoid their misuse, especially as QSARs are being considered for regulatory purposes. This paper provides some guidelines that will promote the proper development and use of QSARs. While this paper uses examples of QSARs to predict toxicity, the proposed guidelines are applicable to QSARs used to predict physical or chemical properties, environmental fate, ecological effects and health effects.

摘要

人们已经建立了许多定量构效关系(QSAR)来预测大多数离散有机化学品的性质、归宿和影响。随着对不同类型监管测试的需求增加以及实验测试成本的上升,有必要评估QSAR的使用情况并提供一些指导以避免其被滥用,特别是在考虑将QSAR用于监管目的时。本文提供了一些指导方针,将促进QSAR的正确开发和使用。虽然本文使用QSAR预测毒性的例子,但所提出的指导方针适用于用于预测物理或化学性质、环境归宿、生态影响和健康影响的QSAR。

相似文献

1
Guidelines for developing and using quantitative structure-activity relationships.定量构效关系的开发与应用指南。
Environ Toxicol Chem. 2003 Aug;22(8):1653-65. doi: 10.1897/01-627.
2
QSARs promote more efficient use of chemical testing resources--carpe diem.
Environ Toxicol Chem. 2003 Aug;22(8):1651-2. doi: 10.1897/03-189.
3
Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.用于监管风险评估的预测有机化学品潜在生态危害的定量构效关系。
Environ Toxicol Chem. 2003 Aug;22(8):1822-8. doi: 10.1897/01-261.
4
Global government applications of analogues, SARs and QSARs to predict aquatic toxicity, chemical or physical properties, environmental fate parameters and health effects of organic chemicals.全球各国政府应用类似物、结构活性关系和定量结构活性关系来预测有机化学品的水生毒性、化学或物理性质、环境归宿参数及健康影响。
SAR QSAR Environ Res. 2002 Oct;13(6):607-16. doi: 10.1080/1062936021000020062.
5
Quantitative structure-activity relationships for predicting skin and eye irritation.
Environ Toxicol Chem. 2003 Aug;22(8):1862-9. doi: 10.1897/01-439.
6
Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.在国际决策框架中使用定量构效关系来预测化学物质的生态效应和环境归宿。
Environ Health Perspect. 2003 Aug;111(10):1376-90. doi: 10.1289/ehp.5759.
7
Health-effects related structure-toxicity relationships: a paradigm for the first decade of the new millennium.与健康效应相关的结构-毒性关系:新千年第一个十年的范例。
Sci Total Environ. 2000 Apr 17;249(1-3):73-84. doi: 10.1016/s0048-9697(99)00512-4.
8
Evolution of the international workshops on quantitative structure-activity relationships (QSARs) in environmental toxicology.环境毒理学中定量构效关系(QSARs)国际研讨会的发展历程。
SAR QSAR Environ Res. 2007 Jan-Mar;18(1-2):3-20. doi: 10.1080/10629360601053927.
9
Quantitative structure-activity relationships for human health effects: commonalities with other endpoints.
Environ Toxicol Chem. 2003 Aug;22(8):1829-43. doi: 10.1897/01-274.
10
The current status and future applicability of quantitative structure-activity relationships (QSARs) in predicting toxicity.定量构效关系(QSARs)在预测毒性方面的现状及未来适用性。
Altern Lab Anim. 2002 Dec;30 Suppl 2:81-4. doi: 10.1177/026119290203002S12.

引用本文的文献

1
Quantum Descriptor-Based Machine-Learning Modeling of Thermal Hazard of Cyclic Sulfamidates.基于量子描述符的环氨基磺酸酯热危险性机器学习建模
J Chem Inf Model. 2025 Aug 25;65(16):8624-8636. doi: 10.1021/acs.jcim.5c01048. Epub 2025 Aug 15.
2
Transparency in Modeling through Careful Application of OECD's QSAR/QSPR Principles via a Curated Water Solubility Data Set.通过精心应用经合组织的 QSAR/QSPR 原则并通过精心制作的水溶性数据集实现建模透明度。
Chem Res Toxicol. 2023 Mar 20;36(3):465-478. doi: 10.1021/acs.chemrestox.2c00379. Epub 2023 Mar 6.
3
Computer-Aided Design of Antimicrobial Peptides: Are We Generating Effective Drug Candidates?
抗菌肽的计算机辅助设计:我们正在生成有效的候选药物吗?
Front Microbiol. 2020 Jan 22;10:3097. doi: 10.3389/fmicb.2019.03097. eCollection 2019.
4
Developing Predictive Models for Carrying Ability of Micro-Plastics towards Organic Pollutants.开发预测微塑料对有机污染物承载能力的模型。
Molecules. 2019 May 8;24(9):1784. doi: 10.3390/molecules24091784.
5
Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure-activity relationship studies.以恶二唑作为虚拟分子探针开发克鲁萨因药效团:定量构效关系研究
J Comput Aided Mol Des. 2017 Sep;31(9):801-816. doi: 10.1007/s10822-017-0039-0. Epub 2017 Aug 9.
6
Structure based comprehensive modelling, spatial fingerprints mapping and ADME screening of curcumin analogues as novel ALR2 inhibitors.基于结构的姜黄素类似物作为新型ALR2抑制剂的综合建模、空间指纹图谱绘制及ADME筛选
PLoS One. 2017 Apr 11;12(4):e0175318. doi: 10.1371/journal.pone.0175318. eCollection 2017.
7
Quantitative Structure-Antioxidant Activity Models of Isoflavonoids: A Theoretical Study.异黄酮类化合物的定量结构-抗氧化活性模型:一项理论研究。
Int J Mol Sci. 2015 Jun 8;16(6):12891-906. doi: 10.3390/ijms160612891.
8
Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review.基于分子性质预测环境中有机化合物的归宿:综述
Crit Rev Environ Sci Technol. 2015 Jun 18;45(12):1277-1377. doi: 10.1080/10643389.2014.955627.
9
Extracting Relevant Information from FDA Drug Files to Create a Structurally Diverse Drug Database Using KnowItAll.从美国食品药品监督管理局(FDA)药品档案中提取相关信息,使用“万事通”创建一个结构多样的药物数据库。
Pharm Rev. 2009 May 8;7(3).
10
Structural findings of cinnolines as anti-schizophrenic PDE10A inhibitors through comparative chemometric modeling.通过比较化学计量学建模研究噌啉类化合物作为抗精神分裂症PDE10A抑制剂的结构特征。
Mol Divers. 2014 Aug;18(3):655-71. doi: 10.1007/s11030-014-9523-9. Epub 2014 May 1.