THE APPLICATION OF SMILES NOTATION MOLECULAR DESCRIPTORS IN QSPR MODELING OF MICELLE–WATER PARTITION COEFFICIENT

17th International Conference on Fundamental and Applied Aspects of Physical Chemistry (Proceedings, Volume II) (2024) [S-03-P, pp. 723-726]   

AUTHOR(S) / АУТОР(И): Jelena V. Živković  and Aleksandar M. Veselinović

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DOI: 10.46793/Phys.Chem24II.723Z

ABSTRACT / САЖЕТАК:

This study explores the development of robust QSPR (Quantitative Structure-Property Relationship) models for predicting micelle-water partition coefficients of organic compounds. The Monte Carlo (MC) optimization method was employed to construct conformation-independent models, utilizing SMILES notation descriptors and local molecular graph invariants. Three independent splits of a dataset containing 81 compounds with experimentally determined coefficients in sodium dodecyl sulfate (SDS) solutions were used for model development and validation. Rigorous statistical evaluation confirmed excellent predictive ability and robustness of the developed QSPR models. Additionally, key molecular fragments within SMILES descriptors influencing the micelle-water partition coefficient were identified. This work demonstrates the efficacy of the MC method for constructing conformation-independent QSPR models with strong predictive power for this crucial property.

KEYWORDS / КЉУЧНЕ РЕЧИ:

ACKNOWLEDGEMENT / ПРОЈЕКАТ:

This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (grant no 451-03-65/2024-03/200113).

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