What question did this study set out to answer?

To extend the COSMO-RS quantum chemical framework to solid compounds for the a priori prediction of aqueous solubilities across neutral drugs and pesticides.

November 27, 2001Journal of Computational ChemistryOpen Access

Prediction of aqueous solubility of drugs and pesticides with COSMO‐RS

View Full Paper

Ask AI

Bookmark

Authors

AKAndreas Klamt FEFrank Eckert MHMartin Hornig

Discussion

Member takes

Overview

Computational modeling demonstrates accurate prediction of aqueous solubility in solid drugs and pesticides, indicating broad applicability across diverse chemical structures.

Key Points

To extend the COSMO-RS quantum chemical framework to solid compounds for the a priori prediction of aqueous solubilities across neutral drugs and pesticides.
Incorporated a heuristic expression for the Gibbs free energy of fusion containing three parameters calibrated on 150 drug-like compounds.
Evaluated model performance without parameter adjustments on an external test set of 107 structurally diverse pesticides validated by experimental databases and HQSAR modeling.
Achieved a root mean square (RMS) deviation of 0.66 log-units on the training set of 150 drug-like compounds.
Attained an RMS deviation of 0.61 log-units across the independent test set of 107 diverse pesticides.

Cite This Study

Klamt et al. (2001) studied this question.

synapsesocial.com/papers/6a162d30f508cb2fcbc1ec48 https://doi.org/10.1002/jcc.1168

View Full Paper

Ask AI

Bookmark

November 27, 2001Journal of Computational ChemistryOpen Access

Prediction of aqueous solubility of drugs and pesticides with COSMO‐RS

View Full Paper

Ask AI

Bookmark

Authors

AKAndreas Klamt FEFrank Eckert MHMartin Hornig

Discussion

Member takes

Overview

Computational modeling demonstrates accurate prediction of aqueous solubility in solid drugs and pesticides, indicating broad applicability across diverse chemical structures.

Key Points

To extend the COSMO-RS quantum chemical framework to solid compounds for the a priori prediction of aqueous solubilities across neutral drugs and pesticides.
Incorporated a heuristic expression for the Gibbs free energy of fusion containing three parameters calibrated on 150 drug-like compounds.
Evaluated model performance without parameter adjustments on an external test set of 107 structurally diverse pesticides validated by experimental databases and HQSAR modeling.
Achieved a root mean square (RMS) deviation of 0.66 log-units on the training set of 150 drug-like compounds.
Attained an RMS deviation of 0.61 log-units across the independent test set of 107 diverse pesticides.

Cite This Study

Klamt et al. (2001) studied this question.

synapsesocial.com/papers/6a162d30f508cb2fcbc1ec48 https://doi.org/10.1002/jcc.1168

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

View Full Paper

Ask AI

Bookmark