serval:BIB_55E64F2C6DDD
MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets.
10.1093/nar/gkr1294
000302312400008
22210894
Kim
T.
author
Tyndel
M.S.
author
Huang
H.
author
Sidhu
S.S.
author
Bader
G.D.
author
Gfeller
D.
author
Kim
P.M.
author
article
2012
Nucleic Acids Research
1362-4962
0305-1048
journal
40
6
e47
Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factors.
Animals
Binding Sites
High-Throughput Nucleotide Sequencing
Humans
Ligands
Mice
Peptide Library
Peptides/chemistry
Position-Specific Scoring Matrices
Protein Interaction Domains and Motifs
Sequence Analysis, Protein
Software
Transcription Factors/metabolism
src Homology Domains
eng
60_published
true
peer-reviewed
University of Lausanne
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