A random forest model for predicting the crystallisability of organic molecules

被引：21
|
作者：
Bhardwaj, Rajni M. [1 ]
Johnston, Andrea [1 ]
Johnston, Blair F. [1 ]
Florence, Alastair J. [1 ]
机构：
[1] Univ Strathclyde, Strathclyde Inst Pharm & Biomed Sci, Glasgow G4 0RE, Lanark, Scotland
来源：
CRYSTENGCOMM | 2015年 / 17卷 / 23期
基金：
英国工程与自然科学研究理事会;
关键词：
PROTEIN CRYSTALLIZATION PROPENSITY; CLASSIFICATION; QSAR; PURIFICATION; SCALE;
D O I：
10.1039/c4ce02403f
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
A random forest model has for the first time enabled the prediction of the crystallisability (crystals vs. no crystals) of organic molecules with similar to 70% accuracy. The predictive model is based on calculated molecular descriptors and published experimental crystallisation propensities of a library of substituted acylanilides.
引用
收藏
页码：4272 / 4275
页数：4
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