Empirical prediction of peptide octanol-water partition coefficients


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.

Divisions: College of Health & Life Sciences > Aston Pharmacy School
College of Health & Life Sciences
Additional Information: 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.
Uncontrolled Keywords: peptide,log P,partition coefficient,octanol-water,regression,physicochemical descriptor,hydrophobicity
Last Modified: 08 Dec 2023 09:30
Date Deposited: 03 Jul 2014 12:35
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Related URLs: http://www.bioi ... net/001/001.htm (Publisher URL)
PURE Output Type: Article
Published Date: 2006
Published Online Date: 2006-11-24
Authors: Hattotuwagama, Channa K.
Flower, Darren R. (ORCID Profile 0000-0002-8542-7067)



Version: Published Version

License: Creative Commons Attribution

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