Structure-water solubility modeling of aliphatic alcohols using the weighted path numbers

Area of Science:

• Quantitative Structure-Activity Relationships (QSAR)
• Computational Chemistry
• Medicinal Chemistry

Background:

• Accurate prediction of water solubility for aliphatic alcohols is crucial in various chemical and pharmaceutical applications.
• Traditional methods often rely on empirical correlations or complex experimental measurements.
• Developing robust quantitative structure-property relationship (QSPR) models is essential for efficient compound design.

Purpose of the Study:

• To develop and evaluate quantitative structure-property relationship (QSPR) models for predicting the water solubility of aliphatic alcohols.
• To compare the efficacy of weighted path numbers against other established molecular descriptors.
• To identify the optimal number of weighted path numbers for achieving high predictive accuracy.

Main Methods:

• Aliphatic alcohols were represented using weighted trees, with specific weights assigned to C-O and C-C bonds.
• Four quantitative structure-property relationship (QSPR) models utilizing weighted path numbers (1-4 descriptors) were developed.
• These models were rigorously compared against models based on surface areas, connectivity indices, and line graphs.
• Model performance was assessed using statistical characteristics and predictive accuracy on a training/test set partition.

Main Results:

• Models incorporating two, three, or four weighted path numbers exhibited the best statistical performance among all evaluated models.
• The predictive performance of these weighted path number models was validated on a test set of 19 compounds, yielding very good and stable predictions.
• Optimal values for the weighting factor 'x' (for C-O bonds) were consistently found within the range of 3.0-4.0 for this dataset.

Conclusions:

• Weighted path numbers represent a powerful and effective tool for developing high-quality quantitative structure-property relationship (QSPR) models.
• The findings support the utility of weighted path numbers for accurately predicting the water solubility of aliphatic alcohols.
• The study highlights the potential of this approach for broader applications in cheminformatics and drug discovery.