Empirical prediction of peptide octanol-water partition coefficients

Channa K. Hattotuwagama, Darren R. Flower

Research output: Contribution to journalArticlepeer-review


Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient P (commonly expressed in logarithm form: logP), is useful for screening out unsuitable molecules and also for the development of predictive Quantitative Structure-Activity Relationships (QSARs). In this paper we develop a new approach to the prediction of LogP values for peptides based on an empirical relationship between global molecular properties and measured physical properties. Our method was successful in terms of peptide prediction (total r2 = 0.641). The final model consisted of 5 physicochemical descriptors (molecular weight, number of single bonds, 2D-VDW volume, 2D-VSA hydrophobic and 2D-VSA polar). The approach is peptide specific and its predictive accuracy was high. Overall, 67% of the peptides were able to be predicted within +/-0.5 log units from the experimental values. Our method thus represents a novel prediction method with proven predictive ability.

Original languageEnglish
Pages (from-to)257-259
Number of pages3
Issue number7
Early online date24 Nov 2006
Publication statusPublished - 2006

Bibliographical note

This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.


  • peptide
  • log P
  • partition coefficient
  • octanol-water
  • regression
  • physicochemical descriptor
  • hydrophobicity


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