The System of Self-Consistent Models: The Case of Henry's Law Constants

Andrey A Toropov; Alla P Toropova; Alessandra Roncaglioni; Emilio Benfenati; Danuta Leszczynska; Jerzy Leszczynski

doi:10.3390/molecules28207231

The System of Self-Consistent Models: The Case of Henry's Law Constants

Molecules. 2023 Oct 23;28(20):7231. doi: 10.3390/molecules28207231.

Authors

Andrey A Toropov¹, Alla P Toropova¹, Alessandra Roncaglioni¹, Emilio Benfenati¹, Danuta Leszczynska², Jerzy Leszczynski³

Affiliations

¹ Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy.
² Interdisciplinary Nanotoxicity Center, Department of Civil and Environmental Engineering, Jackson State University, 1325 Lynch Street, Jackson, MS 39217-0510, USA.
³ Interdisciplinary Nanotoxicity Center, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, 1400 J. R. Lynch Street, Jackson, MS 39217-0510, USA.

Abstract

Data on Henry's law constants make it possible to systematize geochemical conditions affecting atmosphere status and consequently triggering climate changes. The constants of Henry's law are desired for assessing the processes related to atmospheric contaminations caused by pollutants. The most important are those that are capable of long-term movements over long distances. This ability is closely related to the values of Henry's law constants. Chemical changes in gaseous mixtures affect the fate of atmospheric pollutants and ecology, climate, and human health. Since the number of organic compounds present in the atmosphere is extremely large, it is desirable to develop models suitable for predictions for the large pool of organic molecules that may be present in the atmosphere. Here, we report the development of such a model for Henry's law constants predictions of 29,439 compounds using the CORAL software (2023). The statistical quality of the model is characterized by the value of the coefficient of determination for the training and validation sets of about 0.81 (on average).

Keywords: CORAL software; Henry’s law constant; Monte Carlo method; QSPR; SMILES; system of self-consistent models.

Grants and funding

A.A.T., A.P.T., A.R. and E.B. acknowledge EFSA for the financial contribution within the project sOFT-ERA, OC/EFSA/IDATA/2022/02. D.L. and J.L. are thankful to the National Science Foundation for grant No. NSF/CREST HRD-1547754 support.