title: Are the Sublimation Thermodynamics of Organic Molecules Predictable?
abstract: We compare a range of computational methods for the prediction of sublimation thermodynamics (enthalpy, entropy, and free energy of sublimation). These include a model from theoretical chemistry that utilizes crystal lattice energy minimization (with the DMACRYS program) and quantitative structure property relationship (QSPR) models generated by both machine learning (random forest and support vector machines) and regression (partial least squares) methods. Using these methods we investigate the predictability of the enthalpy, entropy and free energy of sublimation, with consideration of whether such a method may be able to improve solubility prediction schemes. Previous work has suggested that the major source of error in solubility prediction schemes involving a thermodynamic cycle via the solid state is in the modeling of the free energy change away from the solid state. Yet contrary to this conclusion other work has found that the inclusion of terms such as the enthalpy of sublimation in QSPR methods does not improve the predictions of solubility. We suggest the use of theoretical chemistry terms, detailed explicitly in the Methods section, as descriptors for the prediction of the enthalpy and free energy of sublimation. A data set of 158 molecules with experimental sublimation thermodynamics values and some CSD refcodes has been collected from the literature and is provided with their original source references.
authors.affiliation: Manchester Institute of Biotechnology, The University of Manchester , 131 Princess Street, Manchester, M1 7DN, U.K.|School of Chemistry, University of St Andrews , North Haugh, St Andrews, Fife, Scotland, United Kingdom , KY16 9ST.
authors.forename: James L
authors.initials: JL
authors.lastname: McDonagh
authors.affiliation: Department of Pure and Applied Chemistry, University of Strathclyde , Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland, United Kingdom , G1 1XL.
authors.forename: David S
authors.initials: DS
authors.lastname: Palmer
authors.affiliation: School of Chemistry, University of St Andrews , North Haugh, St Andrews, Fife, Scotland, United Kingdom , KY16 9ST.
authors.forename: Tanja van
authors.initials: TV
authors.lastname: Mourik
authors.affiliation: School of Chemistry, University of St Andrews , North Haugh, St Andrews, Fife, Scotland, United Kingdom , KY16 9ST.
authors.forename: John B O
authors.initials: JB
authors.lastname: Mitchell
mesh_terms: D019277:Entropy; D048088:Informatics / Q000379:methods*; D008958:Models, Molecular; D008968:Molecular Conformation; D009930:Organic Chemicals / Q000737:chemistry*; D044367:Phase Transition; D021281:Quantitative Structure-Activity Relationship
chemical_list: D009930:Organic Chemicals