PFRMAT DP
TARGET T0359
REMARK number of domains: 1
METHOD domain prediction based on fold recognition of FOLDpro
METHOD FOLDpro: Cheng and Baldi.Bioinformatics,2006:22:1456-1463.
METHOD -------------
MODEL 1
1 S 1 0.6
2 M 1 0.6
3 S 1 0.6
4 E 1 0.6
5 T 1 0.6
6 F 1 0.6
7 D 1 0.6
8 V 1 0.6
9 E 1 0.6
10 L 1 0.6
11 T 1 0.6
12 K 1 0.6
13 N 1 0.6
14 V 1 0.6
15 Q 1 0.6
16 G 1 0.6
17 L 1 0.6
18 G 1 0.6
19 I 1 0.6
20 T 1 0.6
21 I 1 0.6
22 A 1 0.6
23 G 1 0.6
24 Y 1 0.6
25 I 1 0.6
26 G 1 0.6
27 D 1 0.6
28 K 1 0.6
29 K 1 0.6
30 L 1 0.6
31 E 1 0.6
32 P 1 0.6
33 S 1 0.6
34 G 1 0.6
35 I 1 0.6
36 F 1 0.6
37 V 1 0.6
38 K 1 0.6
39 S 1 0.6
40 I 1 0.6
41 T 1 0.6
42 K 1 0.6
43 S 1 0.6
44 S 1 0.6
45 A 1 0.6
46 V 1 0.6
47 E 1 0.6
48 H 1 0.6
49 D 1 0.6
50 G 1 0.6
51 R 1 0.6
52 I 1 0.6
53 Q 1 0.6
54 I 1 0.6
55 G 1 0.6
56 D 1 0.6
57 Q 1 0.6
58 I 1 0.6
59 I 1 0.6
60 A 1 0.6
61 V 1 0.6
62 D 1 0.6
63 G 1 0.6
64 T 1 0.6
65 N 1 0.6
66 L 1 0.6
67 Q 1 0.6
68 G 1 0.6
69 F 1 0.6
70 T 1 0.6
71 N 1 0.6
72 Q 1 0.6
73 Q 1 0.6
74 A 1 0.6
75 V 1 0.6
76 E 1 0.6
77 V 1 0.6
78 L 1 0.6
79 R 1 0.6
80 H 1 0.6
81 T 1 0.6
82 G 1 0.6
83 Q 1 0.6
84 T 1 0.6
85 V 1 0.6
86 L 1 0.6
87 L 1 0.6
88 T 1 0.6
89 L 1 0.6
90 M 1 0.6
91 R 1 0.6
92 R 1 0.6
93 G 1 0.6
94 E 1 0.6
95 T 1 0.6
96 S 1 0.6
97 V 1 0.6
END