ChemRxiv
These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
1/1
3 files

Challenges of the Use of Atomistic Simulations to Predict Solubilities of Drug-like Molecules

preprint
submitted on 09.05.2018 and posted on 10.05.2018 by Guilherme Duarte Ramos Matos, David Mobley
Background.
Solubility is a physical property of extreme importance to the Pharmaceutical industry whose prediction for potential drugs has so far been a hard task.
We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule.

Methods.
Chemical potentials were estimated from all-atom molecular dynamics simulations.
We used the Einstein Molecule Method to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid phase systems.

Results.
Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the Einstein Molecule Method required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally.
Despite the computational cost, however, the computed value did not agree well with experiment, potentially due to limitations with the underlying energy model.
Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation.

Conclusions.
Solubility prediction of drug-like solids still is a challenge on the computational side, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.

Funding

NSF Grant CHE-0840513

History

Email Address of Submitting Author

dmobley@mobleylab.org

Email Address(es) for Other Author(s)

gduarter@uci.edu

Institution

University of California, Irvine

Country

United States

ORCID For Submitting Author

0000-0002-1083-5533

Declaration of Conflict of Interest

DLM is a member of the Scientific Advisory Board for OpenEye Scientific Software. As far as we know no conflict of interest exist as this work is independent of this entity and free and open source.

Licence

Exports