

PFRMAT RR
TARGET T0093
AUTHOR 7875-6238-4020
METHOD Prediction Made with CORNET: a Neural Network based method trained using Correlated Mutations, 
METHOD Sequence Conservation, Predicted Secondary structure of Proteins and Evolutionary Information. 
METHOD Authors Fariselli Piero, Olmea Osvaldo, Valencia Alfonso, Rita Casadio. 
METHOD This method is an extension of the two following methods 
METHOD Olmea O. and Valencia A. (1997) Fold. Des. 2: S25-32. 
METHOD Fariselli P and Casadio R. (1999) Prot. Engng 12:15-21 
MODEL  1
MLDIVLYEPE IPQNTGNIIR LCANTGFRLH LIEPLGFTWD DKRLRRSGLD 
YHEFAEIKRH KTFEAFLESE KPKRLFALTT KGCPAHSQVK FKLGDYLMFG 
PETRGIPMSI LNEMPMEQKI RIPMTANSRS MNLSNSVAVT VYEAWRQLGY 
KGAVNLPEVK
6	29	0	8	0.933
6	31	0	8	0.922
29	122	0	8	0.902
29	75	0	8	0.885
29	97	0	8	0.883
5	31	0	8	0.881
6	97	0	8	0.881
32	78	0	8	0.876
31	122	0	8	0.875
30	96	0	8	0.871
97	122	0	8	0.864
5	122	0	8	0.864
6	78	0	8	0.863
75	97	0	8	0.863
32	122	0	8	0.863
30	123	0	8	0.861
5	97	0	8	0.855
5	29	0	8	0.855
6	98	0	8	0.847
22	30	0	8	0.844
31	97	0	8	0.843
4	75	0	8	0.843
29	78	0	8	0.841
6	122	0	8	0.838
29	96	0	8	0.837
32	98	0	8	0.837
5	98	0	8	0.837
32	75	0	8	0.837
5	75	0	8	0.836
6	30	0	8	0.834
6	76	0	8	0.832
98	122	0	8	0.831
6	75	0	8	0.83
4	31	0	8	0.828
6	77	0	8	0.825
78	98	0	8	0.825
5	78	0	8	0.824
5	30	0	8	0.824
4	98	0	8	0.823
7	96	0	8	0.821
7	75	0	8	0.82
18	122	0	8	0.819
5	77	0	8	0.819
30	79	0	8	0.818
32	120	0	8	0.817
99	122	0	8	0.817
31	78	0	8	0.816
4	29	0	8	0.815
98	123	0	8	0.814
5	76	0	8	0.813
76	98	0	8	0.812
30	98	0	8	0.812
5	96	0	8	0.812
30	76	0	8	0.811
75	122	0	8	0.81
7	29	0	8	0.81
7	31	0	8	0.809
76	122	0	8	0.808
77	97	0	8	0.806
6	32	0	8	0.803
31	75	0	8	0.801
29	77	0	8	0.801
4	76	0	8	0.8
32	89	0	8	0.8
6	120	0	8	0.799
7	98	0	8	0.799
7	78	0	8	0.798
30	75	0	8	0.797
7	120	0	8	0.797
97	120	0	8	0.796
19	31	0	8	0.796
99	123	0	8	0.795
4	77	0	8	0.795
4	120	0	8	0.795
96	120	0	8	0.794
6	99	0	8	0.794
18	153	0	8	0.794
31	99	0	8	0.794
23	122	0	8	0.793
7	32	0	8	0.79
78	122	0	8	0.79
4	122	0	8	0.79
29	98	0	8	0.789
78	97	0	8	0.788
78	120	0	8	0.788
6	96	0	8	0.785
30	78	0	8	0.785
96	122	0	8	0.785
2	122	0	8	0.785
29	124	0	8	0.783
5	121	0	8	0.783
76	97	0	8	0.781
5	120	0	8	0.781
31	153	0	8	0.779
31	77	0	8	0.779
29	120	0	8	0.779
76	96	0	8	0.778
3	121	0	8	0.778
6	121	0	8	0.778
75	96	0	8	0.777
32	99	0	8	0.775
30	99	0	8	0.774
22	96	0	8	0.774
7	122	0	8	0.773
4	97	0	8	0.773
31	98	0	8	0.772
29	89	0	8	0.772
32	76	0	8	0.771
2	29	0	8	0.771
75	98	0	8	0.771
2	75	0	8	0.769
2	97	0	8	0.769
30	97	0	8	0.769
22	154	0	8	0.769
31	96	0	8	0.767
2	120	0	8	0.767
67	122	0	8	0.767
6	79	0	8	0.766
22	31	0	8	0.766
77	96	0	8	0.765
19	122	0	8	0.765
18	154	0	8	0.764
99	124	0	8	0.764
30	91	0	8	0.764
32	133	0	8	0.763
7	30	0	8	0.762
32	96	0	8	0.762
30	122	0	8	0.761
4	78	0	8	0.761
57	159	0	8	0.761
77	98	0	8	0.76
32	77	0	8	0.759
30	77	0	8	0.759
30	121	0	8	0.758
19	29	0	8	0.758
22	122	0	8	0.758
29	131	0	8	0.758
79	98	0	8	0.757
7	76	0	8	0.757
32	124	0	8	0.756
31	76	0	8	0.754
6	123	0	8	0.751
32	91	0	8	0.751
97	123	0	8	0.751
29	99	0	8	0.751
30	120	0	8	0.748
31	89	0	8	0.746
78	96	0	8	0.746
96	123	0	8	0.746
2	31	0	8	0.746
76	121	0	8	0.746
22	32	0	8	0.745
133	153	0	8	0.743
18	156	0	8	0.743
5	79	0	8	0.743
7	91	0	8	0.743
5	32	0	8	0.742
91	124	0	8	0.742
29	91	0	8	0.74
77	122	0	8	0.74
29	76	0	8	0.739
22	29	0	8	0.738
29	123	0	8	0.738
7	99	0	8	0.738
78	99	0	8	0.736
30	89	0	8	0.736
18	159	0	8	0.736
22	153	0	8	0.736
5	99	0	8	0.735
31	120	0	8	0.735
89	96	0	8	0.733
79	121	0	8	0.733
3	28	0	8	0.733
2	98	0	8	0.733
29	154	0	8	0.732
133	156	0	8	0.731
22	129	0	8	0.73
3	79	0	8	0.729
4	96	0	8	0.727
79	120	0	8	0.723
30	74	0	8	0.723
99	153	0	8	0.723
75	120	0	8	0.722
18	133	0	8	0.722
3	30	0	8	0.721
2	32	0	8	0.72
7	89	0	8	0.72
4	32	0	8	0.719
6	89	0	8	0.719
18	32	0	8	0.719
4	121	0	8	0.718
18	31	0	8	0.716
4	30	0	8	0.715
7	79	0	8	0.715
98	124	0	8	0.714
5	89	0	8	0.713
123	130	0	8	0.711
2	78	0	8	0.711
2	124	0	8	0.711
98	120	0	8	0.71
99	120	0	8	0.71
31	121	0	8	0.71
31	123	0	8	0.71
7	77	0	8	0.709
32	79	0	8	0.709
96	121	0	8	0.709
122	131	0	8	0.709
17	123	0	8	0.708
3	76	0	8	0.708
28	79	0	8	0.708
76	120	0	8	0.707
22	98	0	8	0.707
122	153	0	8	0.706
23	31	0	8	0.706
75	123	0	8	0.706
7	133	0	8	0.705
4	79	0	8	0.704
79	96	0	8	0.704
22	79	0	8	0.704
31	124	0	8	0.704
6	18	0	8	0.704
29	133	0	8	0.703
32	97	0	8	0.703
77	120	0	8	0.703
2	123	0	8	0.703
78	121	0	8	0.703
91	98	0	8	0.702
22	78	0	8	0.701
97	121	0	8	0.701
89	99	0	8	0.7
5	91	0	8	0.699
19	32	0	8	0.698
22	123	0	8	0.697
96	124	0	8	0.697
22	132	0	8	0.697
18	29	0	8	0.696
75	124	0	8	0.695
31	133	0	8	0.695
21	122	0	8	0.695
22	138	0	8	0.695
89	122	0	8	0.694
5	123	0	8	0.693
3	98	0	8	0.693
1	32	0	8	0.693
32	121	0	8	0.693
2	99	0	8	0.693
29	90	0	8	0.691
123	132	0	8	0.69
22	121	0	8	0.69
37	99	0	8	0.69
2	96	0	8	0.689
49	153	0	8	0.689
32	131	0	8	0.689
31	79	0	8	0.689
76	123	0	8	0.689
31	91	0	8	0.689
57	122	0	8	0.689
79	88	0	8	0.688
29	153	0	8	0.688
22	99	0	8	0.687
96	119	0	8	0.687
28	96	0	8	0.686
79	122	0	8	0.686
7	124	0	8	0.686
133	154	0	8	0.685
124	133	0	8	0.685
80	96	0	8	0.685
2	89	0	8	0.684
29	156	0	8	0.684
23	97	0	8	0.684
141	153	0	8	0.683
22	91	0	8	0.682
18	120	0	8	0.682
30	124	0	8	0.681
9	122	0	8	0.681
4	91	0	8	0.681
99	131	0	8	0.679
89	98	0	8	0.679
18	124	0	8	0.679
7	123	0	8	0.678
22	152	0	8	0.678
22	100	0	8	0.677
30	95	0	8	0.677
3	123	0	8	0.676
6	91	0	8	0.676
19	97	0	8	0.676
3	31	0	8	0.676
57	133	0	8	0.675
3	74	0	8	0.675
2	91	0	8	0.674
99	129	0	8	0.674
7	97	0	8	0.673
55	122	0	8	0.672
22	159	0	8	0.672
3	77	0	8	0.672
7	121	0	8	0.672
96	129	0	8	0.671
22	155	0	8	0.671
4	18	0	8	0.671
91	122	0	8	0.671
29	95	0	8	0.671
7	18	0	8	0.67
91	120	0	8	0.669
4	89	0	8	0.669
91	99	0	8	0.669
129	154	0	8	0.669
79	90	0	8	0.669
37	153	0	8	0.669
100	122	0	8	0.668
98	121	0	8	0.667
3	96	0	8	0.667
79	95	0	8	0.666
75	121	0	8	0.666
7	74	0	8	0.665
66	153	0	8	0.664
3	97	0	8	0.664
23	37	0	8	0.664
22	57	0	8	0.664
74	97	0	8	0.664
23	131	0	8	0.664
END



