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Beyond Bioinformatics |
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Title |
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Empirical prediction of peptide octanol-water partition coefficients
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Authors |
Channa K. Hattotuwagama & Darren R. Flower * |
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Affiliation |
*The Jenner Institute, University of Oxford, Compton, Newbury, Berkshire, RG20 7NN, UK
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darren.flower@jenner.ac.uk; * Corresponding author
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Phone |
+44 1635 577954
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Fax |
+44 1635 577908
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Article Type |
Prediction Model
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Date |
received November 11,2006; accepted November 22, 2006; published online November 24, 2006
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Abstract |
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.
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Keywords
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Peptide; log P; partition coefficient; octanol-water; regression; physicochemical descriptor; hydrophobicity
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Citation |
Hattotuwagama & Flower, Bioinformation 1(7): 257-259 (2006)
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Edited by |
P. Kangueane
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ISSN |
0973-2063
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Publisher |
Biomedical Informatics Publishing Group
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Copyright |
Publisher
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Copyright Transfer Statement |
The authors of published articles in Bioinformation automatically transfer the copyright to the publisher upon formal acceptance. However, the authors reserve right to use the information contained in the article for non commercial purposes
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License |
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.
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