Name
Title | ||
|---|---|---|
Novel enhanced applications of QSPR models: Temperature dependence of aqueous solubility. |
Abstract | ||
|---|---|---|
A model developed to predict aqueous solubility at different temperatures has been proposed based on quantitative structure-property relationships (QSPR) methodology. The prediction consists of two steps. The first one predicts the value of k parameter in the linear equation lgSw=kT+c, where S-w is the value of solubility and T is the value of temperature. The second step uses Random Forest technique to create high-efficiency QSPR model. The performance of the model is assessed using cross-validation and external test set prediction. Predictive capacity of developed model is compared with COSMO-RS approximation, which has quantum chemical and thermodynamic foundations. The comparison shows slightly better prediction ability for the QSPR model presented in this publication. (c) 2016 Wiley Periodicals, Inc. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1002/jcc.24424 | JOURNAL OF COMPUTATIONAL CHEMISTRY |
Keywords | Field | DocType |
QSPR,feature net,temperature-dependent,aqueous solubility | Quantitative structure–activity relationship,Linear equation,Quantum,Thermodynamics,Chemistry,Solubility,Random forest,Test set,Aqueous solution | Journal |
Volume | Issue | ISSN |
37.0 | 22 | 0192-8651 |
Citations | PageRank | References |
1 | 0.37 | 6 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kyrylo Klimenko | 1 | 1 | 0.37 |
| Victor Kuzmin | 2 | 26 | 2.89 |
| Liudmila Ognichenko | 3 | 1 | 0.71 |
| Leonid Gorb | 4 | 13 | 6.08 |
| Manoj Shukla | 5 | 1 | 0.37 |
| Natalia Vinas | 6 | 1 | 0.37 |
| Edward J. Perkins | 7 | 225 | 20.46 |
| Pavel G. Polishchuk | 8 | 64 | 4.86 |
| Anatoly G. Artemenko | 9 | 40 | 2.94 |
| Jerzy Leszczynski | 10 | 38 | 28.99 |