A random forest model for predicting the crystallisability of organic molecules

被引：25

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

页码：4272 / 4275

页数：4

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