I used the motif-specific PPI targeting algorithm (moPPIt) for peptide sequence generation and moPPIt output scores for ranking the sequences. A complete report is available at https://github.com/agitter/adaptyv-rbx1/blob/main/gitter-moppit-rbx1.pdf with code and output files in that repository https://github.com/agitter/adaptyv-rbx1.
id: quiet-kiwi-cypress
RBX1
0.60
80.30
--
3.2 kDa
25
id: quiet-seal-vine
RBX1
0.50
72.32
--
3.1 kDa
25
id: quiet-ibis-fern
RBX1
0.32
63.37
--
2.6 kDa
20
id: swift-bat-orchid
RBX1
0.07
68.84
--
2.5 kDa
20
id: scarlet-deer-fern
RBX1
0.59
74.07
--
3.1 kDa
25
id: gentle-jaguar-wave
RBX1
0.26
70.32
--
3.3 kDa
25
id: golden-boar-wave
RBX1
0.46
59.15
--
3.1 kDa
25
id: rapid-falcon-topaz
RBX1
0.50
78.22
--
3.0 kDa
25
id: frozen-gecko-sand
RBX1
0.54
67.43
--
2.6 kDa
20
id: hollow-eagle-crystal
RBX1
0.49
68.36
--
3.1 kDa
25
id: silent-zebra-bronze
RBX1
0.17
84.23
--
2.9 kDa
25
id: radiant-hawk-reed
RBX1
0.48
75.88
--
2.9 kDa
25
id: soft-lynx-ivy
RBX1
0.34
64.02
--
2.6 kDa
20
id: jade-jaguar-cedar
RBX1
0.14
53.71
--
3.1 kDa
25
id: solid-gecko-topaz
RBX1
0.16
79.88
--
3.2 kDa
25
id: pale-lynx-ash
RBX1
0.20
75.31
--
2.9 kDa
25
id: quick-jaguar-topaz
RBX1
0.14
66.87
--
2.5 kDa
20
id: solid-falcon-topaz
RBX1
0.01
61.42
--
3.1 kDa
25
id: azure-bison-sand
RBX1
0.58
82.98
--
3.1 kDa
25
id: misty-tiger-cloud
RBX1
0.52
71.95
--
3.2 kDa
25
id: quiet-mole-frost
RBX1
0.82
80.42
--
3.3 kDa
25