A widely applicable set of descriptors.

Area of Science:

• Computational chemistry
• Medicinal chemistry
• Drug discovery

Background:

• Quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models are crucial for predicting molecular behavior.
• Developing novel, broadly applicable molecular descriptors is essential for advancing these predictive models.

Purpose of the Study:

• To define and validate three new sets of molecular descriptors based on atomic contributions.
• To assess the utility of these descriptors in building QSAR/QSPR models for diverse properties.

Main Methods:

• Molecular descriptors were computed from connection table information, focusing on atomic contributions to van der Waals surface area, log P, molar refractivity, and partial charge.
• These descriptors were applied to construct QSAR/QSPR models for physical properties (boiling point, vapor pressure, solvation free energy, solubility), biological activities (thrombin/trypsin/factor Xa inhibition), and blood-brain barrier permeability.
• Compound classification models were also developed.

Main Results:

• The defined molecular descriptors demonstrated wide applicability across various QSAR/QSPR modeling tasks.
• Successful models were constructed for predicting boiling point, vapor pressure, solvation free energy, water solubility, enzyme inhibition, and blood-brain barrier permeability.
• The descriptors proved effective for compound classification.

Conclusions:

• The developed molecular descriptors are versatile and effective for a wide range of QSAR/QSPR applications.
• These descriptors can significantly aid in drug discovery, combinatorial library design, and molecular diversity studies.
• The atomic contribution-based approach provides a robust foundation for future molecular descriptor development.