Identify altered SH2 domain motifs

A potential consequence of altered flanking sequences is that the short linear motifs important for driving PTM-specific domain interactions are disrupted, such as for the phosphotyrosine binding domains SH2 or 14-3-3 proteins (which bind to phosphoserines and threonines). Using PTM-POSE and motif data from [ELM](http://elm.eu.org/searchdb.html), we can identify and visualize the altered 14-3-3 domain motifs due to splicing events.

from ptm_pose import helpers
from ptm_pose.analyze import flank_analysis as afs

#load example altered flanking sequence data
altered_flanks = helpers.load_example_data(altered_flanks = True)

First, we need to identify the linear motifs present for each altered flanking sequence event. We can do this with the compare_inclusion_motifs function, which will identify matching any matching motifs for both the inclusion and exclusion flanking sequences.

altered_flanks = afs.compare_inclusion_motifs(altered_flanks)
altered_flanks[['Gene', 'Residue', 'PTM Position in Isoform', 'Motif only in Inclusion', 'Motif only in Exclusion']].head()

	Gene	Residue	PTM Position in Isoform	Motif only in Inclusion	Motif only in Exclusion
0	ARHGAP17	S	497	DOC_MAPK_gen_1;LIG_PDZ_Class_2;LIG_WD40_WDR5_V...	LIG_SH3_3;LIG_SH3_1
1	ARHGAP17	S	497	DOC_MAPK_gen_1;LIG_PDZ_Class_2;LIG_WD40_WDR5_V...	LIG_SH3_3;LIG_SH3_1
2	KRAS	K	147	TRG_ER_diArg_1
3	KRAS	K	147	TRG_ER_diArg_1
4	KRAS	T	148	TRG_ER_diArg_1

We can then identify the instances in which 14-3-3 motifs are altered:

fourteen33_motifs = afs.identify_change_to_specific_motif(altered_flanks, elm_motif_name = '14-3-3', modification_class = 'Phosphorylation', residues = ['S','T'])
fourteen33_motifs[['Gene', 'Residue', 'PTM Position in Isoform', 'Motif only in Inclusion', 'Motif only in Exclusion']]

77 PTMs removed due to insignificant splice event (p < 0.05, dpsi >= 0.2): (51.33%)
Final number of PTMs to be assessed: 73

	Gene	Residue	PTM Position in Isoform	Motif only in Inclusion	Motif only in Exclusion
23	MLPH	S	336	LIG_14-3-3_CanoR_1	NaN
52	CEACAM1	T	457	LIG_14-3-3_CterR_2	NaN
68	ENAH	S	512	NaN	LIG_14-3-3_CterR_2
84	TSC2	S	946	NaN	LIG_14-3-3_CterR_2

And visualize the differences in sequence

afs.plot_alterations_matrix(fourteen33_motifs)