MOTIPS: automated motif analysis for predicting targets of modular protein domains.
BACKGROUND
Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.


RESULTS
We developed an efficient search algorithm to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder. The integration is performed using naïve Bayes and a training set of validated experiments.


CONCLUSIONS
By integrating a variety of biologically relevant features to predict domain targets, we demonstrated a notably improved prediction of modular protein domain targets. Combined with emerging high-resolution data of domain specificities, we believe that our approach can assist in the reconstruction of many signaling pathways.
Lam
Hugo Y K
HY
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
Kim
Philip M
PM
Mok
Janine
J
Tonikian
Raffi
R
Sidhu
Sachdev S
SS
Turk
Benjamin E
BE
Snyder
Michael
M
Gerstein
Mark B
MB
D000465:Algorithms; D020816:Amino Acid Motifs; D001665:Binding Sites; D008958:Models, Molecular; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D020543:Proteome / Q000737:chemistry / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D012984:Software
D011506:Proteins; D020543:Proteome
Proc Natl Acad Sci U S A. 1992 Nov 15;89(22):10915-9
1438297
J Mol Biol. 2001 Dec 14;314(5):1041-52
11743721
Sci Signal. 2010 Feb 16;3(109):ra12
20159853
Nat Methods. 2004 Oct;1(1):27-9
15782149
Nature. 2003 Dec 11;426(6967):676-80
14668868
Bioinformatics. 2004 Sep 1;20(13):2138-9
15044227
Nature. 1995 Feb 16;373(6515):573-80
7531822
Nat Protoc. 2007;2(6):1368-86
17545975
Bioinformatics. 2001 Aug;17(8):700-12
11524371
Nucleic Acids Res. 2003 Jul 1;31(13):3625-30
12824381
PLoS Comput Biol. 2005 Aug;1(3):e26
16110343
Science. 2003 Apr 18;300(5618):445-52
12702867
Science. 1988 Jul 1;241(4861):42-52
3291115
J Cell Biol. 1999 Jan 11;144(1):71-82
9885245
Sci STKE. 2003 Apr 22;2003(179):RE8
12709533
Proteins. 2003;53 Suppl 6:573-8
14579348
Nat Biotechnol. 2004 Aug;22(8):1035-6
15286655
Science. 2002 Jan 11;295(5553):321-4
11743162
Nat Biotechnol. 2001 Apr;19(4):348-53
11283593
Bioinformatics. 2004 Oct 12;20(15):2479-81
15073010
Proteins. 2004 Sep 1;56(4):753-67
15281128
J Mol Biol. 1972 Mar 14;64(2):417-37
5023183
PLoS Biol. 2004 Jan;2(1):E14
14737190
Nucleic Acids Res. 2003 Jul 1;31(13):3635-41
12824383
Comput Appl Biosci. 1996 Apr;12(2):135-43
8744776
PLoS Biol. 2009 Oct;7(10):e1000218
19841731
Science. 2003 Oct 17;302(5644):449-53
14564010
Nucleic Acids Res. 2004 Mar 19;32(5):1792-7
15034147