Atom/fragment contribution method for estimating octanol-water partition coefficients

Area of Science:

• Computational Chemistry
• Quantitative Structure-Property Relationships (QSPR)

Background:

• The log octanol-water partition coefficient (log P) is a crucial parameter in drug discovery and environmental science.
• Accurate estimation of log P is essential for predicting compound behavior and properties.
• Existing methods for log P estimation face challenges such as 'missing fragments'.

Purpose of the Study:

• To develop and validate a novel atom/fragment contribution (AFC) method for estimating log P.
• To provide a statistically superior and more comprehensive alternative to existing log P estimation techniques.

Main Methods:

• Determined atom/fragment contribution values for 130 chemical substructures using multiple linear regression on 1120 compounds with measured log P values.
• Identified 235 correction factors for substructure orientations using an additional 1231 compounds.
• Estimated log P by summing atom/fragment contributions and correction factors for each compound structure.

Main Results:

• The AFC method achieved a high correlation coefficient (r2=0.98) and low error (ME=0.16) on a training set of 2351 compounds.
• Validation on a separate set of 6055 compounds yielded strong results (r2=0.943, SD=0.408, ME=0.31).
• The method predicts log P within +/- 0.8 log units for over 96% of 8406 compounds and avoids 'missing fragments'.

Conclusions:

• The AFC method provides a robust, accurate, and comprehensive approach for estimating log P.
• This statistically superior method overcomes limitations of previous log P estimation techniques.
• The AFC method is highly effective for predicting physicochemical properties of organic compounds.