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View Structure Prediction Details

Protein: GALP_MOUSE
Organism: Mus musculus
Length: 117 amino acids
Reference: Drew K, et al. (2011) The proteome folding project: Proteome-scale prediction of structure and function. Genome Res. 2011 Sep 16



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Top Sequence Alignment Hits

Listed below are up to the top 10 sequence alignment matches, by species, for the PSI-BLAST search against the protein sequence for GALP_MOUSE.

Description E-value Query
Range
Subject
Range
GALP_RAT - Galanin-like peptide OS=Rattus norvegicus GN=Galp PE=3 SV=1
220.0 [0..1] [114..1]
HGNC:24840|MIM:6... - peptide
GALP - galanin-like peptide
gi|151555123, gi... - gi|151555123|gb|AAI48723.1| Galanin-like peptide [synthetic construct], gi|146327238|gb|AAI41469.1| ...
191.0 [0..18] [115..19]
gi|109126180 - gi|109126180|ref|XP_001090902.1| PREDICTED: similar to galanin-like peptide precursor [Macaca mulatt...
GALP_MACNE - Galanin-like peptide OS=Macaca nemestrina GN=GALP PE=2 SV=1
190.0 [0..18] [115..18]
gi|114679247 - gi|114679247|ref|XP_524495.2| PREDICTED: similar to galanin-like peptide precursor [Pan troglodytes]
188.0 [0..18] [115..19]
GALP_PIG - Galanin-like peptide OS=Sus scrofa GN=GALP PE=1 SV=1
172.0 [0..1] [97..1]
gi|73947395 - gi|73947395|ref|XP_853936.1| PREDICTED: similar to zinc finger protein 444 [Canis familiaris]
135.0 [0..19] [105..383]
gi|16945957 - gi|16945957|gb|AAL32205.1|AF426450_1 galanin-like peptide [Mus musculus]
105.0 [0..11] [65..1]

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Predicted Domain #1
Region A:
Residues: [1-117]
      1          11         21         31         41         51         
      |          |          |          |          |          |          
    1 MACSVHLVLF LTILLSLAET PESAPAHRGR GGWTLNSAGY LLGPVLPVSS KADQGRKRDS  60
   61 ALEILDLWKI IDGLPYSHSP RMTKRTMGET FVKANTGDMH ILDKNVPKEE ATLDSES

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Detection Method: deduced

Shown below is our most confident de novo (Rosetta) prediction for this domain.
Click here to view all matches.

Found no confident structure predictions for this domain.


YRC Informatics Platform - Version 3.0
Created and Maintained by: Michael Riffle