A Benchmark Dataset Comprising Partition and Distribution Coefficients of Linear Peptides. (16th May 2013)

• Record Type: Journal Article
• Authors: Davies, Matthew N.; Flower, Darren R.
• Other Names: McGuffin Liam Academic Editor.; Ponce Soto Luis Alberto Academic Editor.
• Is Part Of: Dataset papers in science. Volume 2013(2013)
• Publication Date: 2013-05-16
• Subjects: Science -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Biology; Medicine; Science; Electronic journals; Electronic journals; Periodicals; 500
• DOI: 10.7167/2013/976758
• Languages: English
• ISSNs: 2314-8497

Abstract

Abstract : Peptides have a dominant role in biology; yet the study of their physical properties is at best sporadic. Peptide quantitative structure-activity relationship (QSAR) lags far behind the QSAR analysis of drug-like organic small molecules. Traditionally, QSAR has focussed on experimentally determined partition coefficients as the main descriptor of hydrophobicity. A partition coefficient (log P ) is the ratio between the concentrations of an uncharged chemical substance in two immiscible phases: most typically water and an organic solvent, usually 1-octanol. A distribution coefficient (log D ) is the equivalent ratio for charged molecules. We report here a compilation of partition and distribution coefficients for linear peptides compiled from literature reports, suitable for the development and benchmarking of peptidelog P andlog D prediction algorithms.