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

Buonaiuto MA, Lang AS - Chem Cent J (2015)

Bottom Line: The model has been deployed for general use as a Shiny application.The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure.The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.

View Article: PubMed Central - PubMed

Affiliation: Department of Computing and Mathematics, Oral Roberts University, 7777 S. Lewis Avenue, Tulsa, OK 74171 USA.

ABSTRACT

Background: 1-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.

Results: We created a random forest model using CDK descriptors that has an out-of-bag (OOB) R(2) value of 0.66 and an OOB mean squared error of 0.34. The model has been deployed for general use as a Shiny application.

Conclusion: The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure. The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.

No MeSH data available.


Solubility distribution of the compounds in our study. 76 % of compounds have solubilityvalues between 0.01 and 1.00 M
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Fig2: Solubility distribution of the compounds in our study. 76 % of compounds have solubilityvalues between 0.01 and 1.00 M

Mentions: The collection and curation process left us with 261 data points to model, seeAdditional file 1. The structures in our dataset are notvery diverse and can be characterized, in general, as relatively small organic compounds with1-octanol solubility values between 0.01 and 1.00 M, see Figs. 1, 2, and 3.Fig. 1


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

Buonaiuto MA, Lang AS - Chem Cent J (2015)

Solubility distribution of the compounds in our study. 76 % of compounds have solubilityvalues between 0.01 and 1.00 M
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585410&req=5

Fig2: Solubility distribution of the compounds in our study. 76 % of compounds have solubilityvalues between 0.01 and 1.00 M
Mentions: The collection and curation process left us with 261 data points to model, seeAdditional file 1. The structures in our dataset are notvery diverse and can be characterized, in general, as relatively small organic compounds with1-octanol solubility values between 0.01 and 1.00 M, see Figs. 1, 2, and 3.Fig. 1

Bottom Line: The model has been deployed for general use as a Shiny application.The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure.The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.

View Article: PubMed Central - PubMed

Affiliation: Department of Computing and Mathematics, Oral Roberts University, 7777 S. Lewis Avenue, Tulsa, OK 74171 USA.

ABSTRACT

Background: 1-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.

Results: We created a random forest model using CDK descriptors that has an out-of-bag (OOB) R(2) value of 0.66 and an OOB mean squared error of 0.34. The model has been deployed for general use as a Shiny application.

Conclusion: The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure. The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.

No MeSH data available.