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考察 COSMO-SAC 模型在药物化合物溶解度和共晶形成中的应用。

Investigation of COSMO-SAC model for solubility and cocrystal formation of pharmaceutical compounds.

机构信息

Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

出版信息

Sci Rep. 2020 Nov 16;10(1):19879. doi: 10.1038/s41598-020-76986-3.

DOI:10.1038/s41598-020-76986-3
PMID:33199834
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7670437/
Abstract

In this study, a predictive model named COSMO-SAC was investigated in solid/liquid equilibria for pharmaceutical compounds. The examined properties were the solubility of drug in the pure and mixed solvents, octanol/water partition coefficient, and cocrystal formation. The results of the original COSMO-SAC model (COSMO-SAC (2002)) was compared with a semi-predictive model named Flory-Huggins model and a revised version of the COSMO-SAC (COSMO-SAC (2010)). The results indicated the acceptable accuracy of the COSMO-SAC (2002) in the considered scope. The results emphasized on the suitability of the COSMO-SAC model for simple molecules containing C, H, and O by covalent and hydrogen bonding interactions. Applicability of the COSMO-SAC for more complicated molecules made of various functional groups such as COO and COOH doubly requires more modification in the COSMO-SAC.

摘要

在这项研究中,考察了一个名为 COSMO-SAC 的预测模型在药物化合物固/液平衡中的应用。考察的性质包括药物在纯溶剂和混合溶剂中的溶解度、辛醇/水分配系数和共晶形成。将原始 COSMO-SAC 模型(COSMO-SAC(2002))的结果与一个半预测模型(Flory-Huggins 模型)和 COSMO-SAC 的修订版本(COSMO-SAC(2010))进行了比较。结果表明,在考虑的范围内,COSMO-SAC(2002)具有可接受的准确性。结果强调了 COSMO-SAC 模型对于含有 C、H 和 O 的简单分子通过共价和氢键相互作用的适用性。COSMO-SAC 对于由各种官能团(如 COO 和 COOH)组成的更复杂分子的适用性需要对 COSMO-SAC 进行更多的修改。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/1583e0c2b86b/41598_2020_76986_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/256eb1033564/41598_2020_76986_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/b6dd350d08fb/41598_2020_76986_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/50f305dde28e/41598_2020_76986_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/824aaa494640/41598_2020_76986_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/9e1b9621ae26/41598_2020_76986_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/28566b492566/41598_2020_76986_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/1583e0c2b86b/41598_2020_76986_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/256eb1033564/41598_2020_76986_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/b6dd350d08fb/41598_2020_76986_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/50f305dde28e/41598_2020_76986_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/824aaa494640/41598_2020_76986_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/9e1b9621ae26/41598_2020_76986_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/28566b492566/41598_2020_76986_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d03c/7670437/1583e0c2b86b/41598_2020_76986_Fig7_HTML.jpg

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本文引用的文献

1
A Benchmark Open-Source Implementation of COSMO-SAC.COSMO-SAC 的基准开源实现。
J Chem Theory Comput. 2020 Apr 14;16(4):2635-2646. doi: 10.1021/acs.jctc.9b01016. Epub 2020 Mar 6.
2
Modeling and prediction of cocrystal phase diagrams.共晶相图的建模与预测。
Int J Pharm. 2009 Jun 5;374(1-2):82-9. doi: 10.1016/j.ijpharm.2009.03.016. Epub 2009 Mar 24.
3
Prediction of pharmaceutical solubility Via NRTL-SAC and COSMO-SAC.通过非随机双液体-统计缔合流体理论(NRTL-SAC)和导体屏蔽模型(COSMO-SAC)预测药物溶解度
基于 COSMO 的用于药物化合物的预测 PC-SAFT EOS。
Sci Rep. 2021 Mar 19;11(1):6405. doi: 10.1038/s41598-021-85942-8.
J Pharm Sci. 2008 May;97(5):1813-20. doi: 10.1002/jps.21032.