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基于 COSMO 的用于药物化合物的预测 PC-SAFT EOS。

A predictive PC-SAFT EOS based on COSMO for pharmaceutical compounds.

机构信息

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

出版信息

Sci Rep. 2021 Mar 19;11(1):6405. doi: 10.1038/s41598-021-85942-8.

DOI:10.1038/s41598-021-85942-8
PMID:33742065
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7979706/
Abstract

The present study was conducted to develop a predictive type of PC-SAFT EOS by incorporating the COSMO computations. With the proposed model, the physical adjustable inputs to PC-SAFT EOS were determined from the suggested correlations with dependency to COSMO computation results. Afterwards, we tested the reliability of the proposed predictive PC-SAFT EOS by modeling the solubility data of certain pharmaceutical compounds in pure and mixed solvents and their octanol/water partition coefficients. The obtained RMSE based on logarithmic scale for the predictive PC-SAFT EOS was 1.435 for all of the solubility calculations. The reported values (1.435) had a lower value than RMSE for COSMO-SAC model (4.385), which is the same as that for RMSE for COSMO-RS model (1.412). The standard RMSE for octanol/water partition coefficient of the investigated pharmaceutical compounds was estimated to be 1.515.

摘要

本研究旨在通过结合 COSMO 计算开发一种预测型 PC-SAFT EOS。在所提出的模型中,PC-SAFT EOS 的物理可调输入通过与 COSMO 计算结果相关的建议相关性来确定。之后,我们通过对某些药物化合物在纯溶剂和混合溶剂中的溶解度数据以及它们的辛醇/水分配系数进行建模,测试了所提出的预测性 PC-SAFT EOS 的可靠性。基于对数标度的预测性 PC-SAFT EOS 的 RMSE 为所有溶解度计算的 1.435。所报道的值(1.435)低于 COSMO-SAC 模型(4.385)的 RMSE,与 COSMO-RS 模型(1.412)的 RMSE 相同。所研究的药物化合物的辛醇/水分配系数的标准 RMSE 估计为 1.515。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/083d6e798f23/41598_2021_85942_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/e6c942e581e1/41598_2021_85942_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/63e286796fd1/41598_2021_85942_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/72f8db1ef351/41598_2021_85942_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/09d71968bd5b/41598_2021_85942_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/6340178d83e7/41598_2021_85942_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/582b56407da4/41598_2021_85942_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/455fb76a9ebd/41598_2021_85942_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/e39bf9555cc3/41598_2021_85942_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1b8/7979706/083d6e798f23/41598_2021_85942_Fig10_HTML.jpg

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A Benchmark Open-Source Implementation of COSMO-SAC.COSMO-SAC 的基准开源实现。
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