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

@article{Buonaiuto2015PredictionO1,
  title={Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge},
  author={Michael A. Buonaiuto and Andrew S. I. D. Lang},
  journal={Chemistry Central Journal},
  year={2015},
  volume={9}
}
Background1-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.ResultsWe created a random forest model using CDK descriptors that has an out-of-bag… 
Solubility Prediction from Molecular Properties and Analytical Data Using an In-phase Deep Neural Network (Ip-DNN)
TLDR
This study succeeded at establishing a solubility prediction tool using a unique machine learning method called the in-phase deep neural network (ip-DNN), which starts exclusively from the analytical input data to predictsolubility by predicting intermediate elements, such as molecular components and molecular descriptors, in the multiple-step method.

References

SHOWING 1-10 OF 28 REFERENCES
Estimation of solubility of organic compounds in 1-octanol
Five methods were evaluated for their ability to estimate the solubility of organic compounds in 1-octanol. OCTASOL is a modified group contribution method developed in this study. Another proposed
Predicting the octanol solubility of organic compounds.
TLDR
Criteria is developed to determine if the real or hypothetical liquid form of a given compound will be miscible with octanol based on its molar volume and solubility parameter, and shows that more than 95% of the octanol solubilities studied are predicted with an error of less than 1 logarithmic unit.
The solubility of liquid and solid compounds in dry octan-1-ol.
Predicting Abraham model solvent coefficients
TLDR
Open random forest models for the solvent coefficients e, s, a, b, and v are created that predict that propylene glycol may be used as a general sustainable solvent replacement for methanol.
Solubility prediction in octanol: A technical note
TLDR
An equation for the rapid estimation of octanol solubilities of organic compounds was derived with an average absolute error of 0.39 logarithmic units using melting point alone.
Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 2. Solubility in 1-octanol
TLDR
It was shown that the exclusive consideration of melting points did not provide satisfactory results in the quantitative prediction of octanol solubility, and it was proposed that the main reason for such behaviour was the different crystal lattice interaction of different classes of chemicals.
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
TLDR
Abraham descriptors were calculated for both the monomeric and dimeric forms of trans-cinnamic acid, the first time that descriptors for a carboxylic acid dimer have been obtained.
Open Notebook Science Challenge Solubilities of Organic Compounds in
This book contains the results of the Open Notebook Science Solubility Challenge. All experimental measurements are provided with a link to either the laboratory notebook page where the experiment
Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics.
TLDR
The Chemistry Development Kit's new QSAR capabilities and the recently introduced interface to statistical software are introduced.
The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics
TLDR
The Chemistry Development Kit provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc.
...
...