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Screening of peptides with a high affinity to bile acids using peptide arrays and a computational analysis

Paper ID Volume ID Publish Year Pages File Format Full-Text
21194 43210 2011 6 PDF Available
Title
Screening of peptides with a high affinity to bile acids using peptide arrays and a computational analysis
Abstract

Bile acid binding peptides have attracted attention for the improvement and prevention of hypercholesterolemia. In this study, screening of bile acid high affinity peptides was investigated using computationally-assisted peptide array analysis. Starting with the screening data obtained from a limited, random 6-mer library (2212 sequences), the peptides with a high affinity to bile acid were characterized by comparison of high- and low-affinity peptides using fuzzy neural network (FNN) analysis. The physical properties of amino acids at specific positions that contribute to bile acid binding activity were extracted as the structural rule; optimization was carried out using three repeated screening cycles of the rule extraction. The extracted structural rule indicates that Trp, Tyr, Phe, Leu, Ile and Val are enriched in bile acid binding peptides. The yields of bile acid binding peptides with an affinity of above the VAWWMY peptide (soystatin, control sequence) were significantly higher in the optimized structural rule (32.5%) compared to that of the random library (3.1%), and 6 peptides were obtained with above 2.0-fold increased binding activity.

Keywords
Bile acids; Functional peptides; Spot-synthesized peptide array; Computational analysis; Peptide screening
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Screening of peptides with a high affinity to bile acids using peptide arrays and a computational analysis
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Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Bioscience and Bioengineering - Volume 112, Issue 1, July 2011, Pages 92–97
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us