• 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

利用开放笔记本科学挑战赛的数据预测正辛醇溶解度。

Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge.

作者信息

Buonaiuto Michael A, Lang Andrew S I D

机构信息

Department of Computing and Mathematics, Oral Roberts University, 7777 S. Lewis Avenue, Tulsa, OK 74171 USA.

出版信息

Chem Cent J. 2015 Sep 24;9(1):50. doi: 10.1186/s13065-015-0131-2. eCollection 2015 Dec.

DOI:10.1186/s13065-015-0131-2
PMID:26435734
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4585410/
Abstract

BACKGROUND

1-Octanol solubility is important in a variety of applications involving pharmacology and environmental chemistry. Current models are linear in nature and often require foreknowledge of either melting point or aqueous solubility. Here we extend the range of applicability of 1-octanol solubility models by creating a random forest model that can predict 1-octanol solubilities directly from structure.

RESULTS

We created a random forest model using CDK descriptors that has an out-of-bag (OOB) R value of 0.66 and an OOB mean squared error of 0.34. The model has been deployed for general use as a Shiny application.

CONCLUSION

The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure. The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.

摘要

背景

1-辛醇溶解度在涉及药理学和环境化学的各种应用中很重要。当前的模型本质上是线性的，并且通常需要熔点或水溶性的先验知识。在这里，我们通过创建一个可以直接从结构预测1-辛醇溶解度的随机森林模型，扩展了1-辛醇溶解度模型的适用范围。

结果

我们使用CDK描述符创建了一个随机森林模型，其袋外（OOB）R值为0.66，OOB均方误差为0.34。该模型已作为一个Shiny应用程序部署以供通用。

结论

1-辛醇溶解度模型可以直接从结构合理准确地预测有机溶质的1-辛醇溶解度。该模型是在开放笔记本科学条件下开发的，这使其具有开放性、可重复性且尽可能有用。图形摘要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/2dc05dcd83e7/13065_2015_131_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/ab3e60dae06b/13065_2015_131_Figa_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/8610b5a53352/13065_2015_131_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/d74e9e52630c/13065_2015_131_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/12a61b3033b0/13065_2015_131_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/c8b69466bfc4/13065_2015_131_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/e3a6e0538e23/13065_2015_131_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/665752a83eba/13065_2015_131_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/2dc05dcd83e7/13065_2015_131_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/ab3e60dae06b/13065_2015_131_Figa_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/8610b5a53352/13065_2015_131_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/d74e9e52630c/13065_2015_131_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/12a61b3033b0/13065_2015_131_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/c8b69466bfc4/13065_2015_131_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/e3a6e0538e23/13065_2015_131_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/665752a83eba/13065_2015_131_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/4606915/2dc05dcd83e7/13065_2015_131_Fig7_HTML.jpg

相似文献

1
Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge.利用开放笔记本科学挑战赛的数据预测正辛醇溶解度。
Chem Cent J. 2015 Sep 24;9(1):50. doi: 10.1186/s13065-015-0131-2. eCollection 2015 Dec.
2
Predicting Abraham model solvent coefficients.预测亚伯拉罕模型溶剂系数。
Chem Cent J. 2015 Mar 22;9:12. doi: 10.1186/s13065-015-0085-4. eCollection 2015.
3
Solubility of organic compounds in octanol: Improved predictions based on the geometrical fragment approach.有机物在辛醇中的溶解度：基于几何片段方法的改进预测。
Chemosphere. 2017 Sep;182:399-405. doi: 10.1016/j.chemosphere.2017.05.045. Epub 2017 May 10.
4
Predicting the octanol solubility of organic compounds.预测有机化合物的辛醇溶解度。
J Pharm Sci. 2013 Jul;102(7):2112-9. doi: 10.1002/jps.23561. Epub 2013 Apr 22.
5
Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 2. Aqueous solubility, octanol solubility and octanol-water partition coefficient.使用UPPER估算多卤代芳香族和脂肪族化合物的物理化学性质：第2部分。水溶性、辛醇溶解度和辛醇-水分配系数。
Chemosphere. 2015 Jan;119:1441-1446. doi: 10.1016/j.chemosphere.2014.10.031. Epub 2014 Oct 29.
6
Calculating the Solubilities of Drugs and Drug-Like Compounds in Octanol.计算药物及类药物化合物在辛醇中的溶解度。
J Pharm Sci. 2016 Sep;105(9):2770-2773. doi: 10.1016/j.xphs.2016.02.002. Epub 2016 Mar 21.
7
Solubility and partitioning IV: Aqueous solubility and octanol-water partition coefficients of liquid nonelectrolytes.溶解度与分配系数IV：液态非电解质的水溶性和正辛醇-水分配系数
J Pharm Sci. 1981 May;70(5):502-7. doi: 10.1002/jps.2600700510.
8
Determination of Abraham model solute descriptors for the monomeric and dimeric forms of trans-cinnamic acid using measured solubilities from the Open Notebook Science Challenge.利用开放笔记本科学挑战赛中测得的溶解度，测定反式肉桂酸单体和二聚体形式的亚伯拉罕模型溶质描述符。
Chem Cent J. 2015 Mar 22;9:11. doi: 10.1186/s13065-015-0080-9. eCollection 2015.
9
Scores of extended connectivity fingerprint as descriptors in QSPR study of melting point and aqueous solubility.在熔点和水溶性的定量构效关系（QSPR）研究中，将扩展连接性指纹图谱分数用作描述符。
J Chem Inf Model. 2008 May;48(5):981-7. doi: 10.1021/ci800024c. Epub 2008 May 9.
10
Intrinsic molecular volume as a measure of the cavity term in linear solvation energy relationships: octanol-water partition coefficients and aqueous solubilities.作为线性溶剂化能关系中空腔项度量的本征分子体积：正辛醇-水分配系数和水溶性。
J Pharm Sci. 1986 Jul;75(7):629-36. doi: 10.1002/jps.2600750702.

引用本文的文献

1
Solubility Prediction from Molecular Properties and Analytical Data Using an In-phase Deep Neural Network (Ip-DNN).利用同相深度神经网络（Ip-DNN）从分子性质和分析数据预测溶解度
ACS Omega. 2021 May 17;6(22):14278-14287. doi: 10.1021/acsomega.1c01035. eCollection 2021 Jun 8.

本文引用的文献

1
Solubility prediction in octanol: A technical note.辛醇中的溶解度预测：技术说明。
AAPS PharmSciTech. 2006 Mar;7(1):E184-E191. doi: 10.1208/pt070126. Epub 2017 Mar 8.
2
Predicting Abraham model solvent coefficients.预测亚伯拉罕模型溶剂系数。
Chem Cent J. 2015 Mar 22;9:12. doi: 10.1186/s13065-015-0085-4. eCollection 2015.
3
Determination of Abraham model solute descriptors for the monomeric and dimeric forms of trans-cinnamic acid using measured solubilities from the Open Notebook Science Challenge.利用开放笔记本科学挑战赛中测得的溶解度，测定反式肉桂酸单体和二聚体形式的亚伯拉罕模型溶质描述符。
Chem Cent J. 2015 Mar 22;9:11. doi: 10.1186/s13065-015-0080-9. eCollection 2015.
4
The solubility of liquid and solid compounds in dry octan-1-ol.液体和固体化合物在干燥辛-1-醇中的溶解度。
Chemosphere. 2014 May;103:26-34. doi: 10.1016/j.chemosphere.2013.10.095. Epub 2013 Nov 28.
5
Predicting the octanol solubility of organic compounds.预测有机化合物的辛醇溶解度。
J Pharm Sci. 2013 Jul;102(7):2112-9. doi: 10.1002/jps.23561. Epub 2013 Apr 22.
6
Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 2. Solubility in 1-octanol.决定化学物质在水-溶剂-气体体系中溶解度和分配的物理化学性质/描述符。第2部分。在1-辛醇中的溶解度。
SAR QSAR Environ Res. 2007 Jul-Sep;18(5-6):543-78. doi: 10.1080/10629360701430124.
7
Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics.化学开发工具包（CDK）的最新进展——一个用于化学和生物信息学的开源Java库。
Curr Pharm Des. 2006;12(17):2111-20. doi: 10.2174/138161206777585274.
8
The Chemistry Development Kit (CDK): an open-source Java library for Chemo- and Bioinformatics.化学开发工具包（CDK）：一个用于化学信息学和生物信息学的开源Java库。
J Chem Inf Comput Sci. 2003 Mar-Apr;43(2):493-500. doi: 10.1021/ci025584y.