Standardizing and Simplifying
Analysis of Peptide
Library Data
- Publication date
- Publisher
Abstract
Peptide libraries allow researchers to quickly find hundreds
of
peptide sequences with a desired property. Currently, the large amount
of data generated from peptide libraries is analyzed by hand, where
researchers search for repeating patterns in the peptide sequences.
Such patterns are called motifs. In this work, we describe a set of
algorithms which allow quick, efficient, and standard analysis of
peptide libraries. Four main techniques are described: (1) choice
of the number of motifs present in a peptide library; (2) separation
of the peptides into groups of similar sequences; (3) fitting of a
model to the peptides to extract motifs; (4) analysis of the library
using quantitative structure–property relationships if no clear
motifs are present. The application of five previously published data
sets shows these techniques can automatically repeat the work of experts
quickly and allow much more flexibility in analysis. A new way of
visually presenting peptide libraries is also described, which allows
visual inspection of the grouping and spread of sequences. The algorithms
have been implemented in an open-source plug-in called “peplib”
and an online web application