
PFRMAT RR
TARGET T0123
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
VEVTPIMTEL DTQKVAGTWH TVAMAVSDVS LLDAKSSPLK AYVEGLKPTP 
EGDLEILLQK RENDKCAQEV LLAKKTDIPA VFKINALDEN QLFLLDTDYD 
SHLLLCMENS ASPEHSLVCQ SLARTLEVDD QIREKFEDAL KTLSVPMRIL PAQLEEQCRV
66	158	0	8	0.864
95	104	0	8	0.826
82	105	0	8	0.825
58	104	0	8	0.819
58	105	0	8	0.818
82	95	0	8	0.818
58	103	0	8	0.813
82	94	0	8	0.81
94	104	0	8	0.806
84	105	0	8	0.803
95	103	0	8	0.803
58	94	0	8	0.801
82	102	0	8	0.8
82	107	0	8	0.799
94	103	0	8	0.797
82	103	0	8	0.797
84	103	0	8	0.796
95	105	0	8	0.795
82	104	0	8	0.792
56	92	0	8	0.791
92	103	0	8	0.788
71	103	0	8	0.788
58	72	0	8	0.788
56	103	0	8	0.787
95	102	0	8	0.787
43	103	0	8	0.786
58	102	0	8	0.785
58	95	0	8	0.785
56	82	0	8	0.784
46	54	0	8	0.78
57	103	0	8	0.779
94	105	0	8	0.778
58	82	0	8	0.776
82	92	0	8	0.774
43	84	0	8	0.772
66	106	0	8	0.771
82	93	0	8	0.77
58	92	0	8	0.77
56	94	0	8	0.769
56	71	0	8	0.769
72	103	0	8	0.761
56	104	0	8	0.761
43	107	0	8	0.761
43	82	0	8	0.761
43	105	0	8	0.761
56	84	0	8	0.76
43	95	0	8	0.76
92	107	0	8	0.76
57	95	0	8	0.758
84	94	0	8	0.758
54	105	0	8	0.757
43	56	0	8	0.753
56	105	0	8	0.753
58	86	0	8	0.752
54	103	0	8	0.752
43	81	0	8	0.751
58	106	0	8	0.75
84	102	0	8	0.75
93	104	0	8	0.749
92	105	0	8	0.749
95	106	0	8	0.748
43	94	0	8	0.748
82	106	0	8	0.748
92	104	0	8	0.747
71	95	0	8	0.747
54	71	0	8	0.746
58	84	0	8	0.746
57	94	0	8	0.745
72	95	0	8	0.744
54	104	0	8	0.744
84	104	0	8	0.743
84	92	0	8	0.743
56	95	0	8	0.742
55	83	0	8	0.742
43	92	0	8	0.742
57	105	0	8	0.741
72	104	0	8	0.741
58	71	0	8	0.741
56	102	0	8	0.74
71	104	0	8	0.739
56	107	0	8	0.738
71	82	0	8	0.737
72	105	0	8	0.736
103	149	0	8	0.736
58	107	0	8	0.734
57	104	0	8	0.734
43	71	0	8	0.733
46	107	0	8	0.732
56	72	0	8	0.73
46	102	0	8	0.73
71	102	0	8	0.73
58	93	0	8	0.729
71	105	0	8	0.729
94	102	0	8	0.728
43	102	0	8	0.726
46	56	0	8	0.726
93	106	0	8	0.725
84	107	0	8	0.725
57	81	0	8	0.725
41	103	0	8	0.724
72	82	0	8	0.724
72	94	0	8	0.724
43	58	0	8	0.723
57	82	0	8	0.723
57	93	0	8	0.723
46	103	0	8	0.722
46	71	0	8	0.722
42	104	0	8	0.722
84	106	0	8	0.721
54	94	0	8	0.721
66	102	0	8	0.721
54	86	0	8	0.72
71	92	0	8	0.718
46	105	0	8	0.716
73	102	0	8	0.715
56	81	0	8	0.714
43	104	0	8	0.714
54	72	0	8	0.712
54	84	0	8	0.712
54	92	0	8	0.711
104	149	0	8	0.709
19	158	0	8	0.709
54	149	0	8	0.709
57	102	0	8	0.708
19	54	0	8	0.708
73	104	0	8	0.707
57	92	0	8	0.706
94	106	0	8	0.706
86	103	0	8	0.706
57	71	0	8	0.705
73	95	0	8	0.705
73	82	0	8	0.705
71	94	0	8	0.704
41	107	0	8	0.704
94	107	0	8	0.703
71	106	0	8	0.703
54	95	0	8	0.702
72	107	0	8	0.7
54	82	0	8	0.699
80	107	0	8	0.699
73	103	0	8	0.699
72	86	0	8	0.698
93	103	0	8	0.698
55	70	0	8	0.697
84	95	0	8	0.697
58	85	0	8	0.697
95	107	0	8	0.697
56	86	0	8	0.697
54	107	0	8	0.696
55	94	0	8	0.695
59	102	0	8	0.695
73	94	0	8	0.695
85	105	0	8	0.695
58	149	0	8	0.693
92	106	0	8	0.693
85	106	0	8	0.693
71	107	0	8	0.692
95	149	0	8	0.691
92	102	0	8	0.689
73	105	0	8	0.689
44	102	0	8	0.688
83	104	0	8	0.688
46	94	0	8	0.688
72	102	0	8	0.688
56	106	0	8	0.687
46	72	0	8	0.687
19	39	0	8	0.685
80	95	0	8	0.684
43	57	0	8	0.684
80	92	0	8	0.683
43	72	0	8	0.683
93	105	0	8	0.682
57	149	0	8	0.682
46	58	0	8	0.682
57	86	0	8	0.682
80	105	0	8	0.68
80	106	0	8	0.68
55	91	0	8	0.68
43	86	0	8	0.68
85	103	0	8	0.679
59	107	0	8	0.679
46	92	0	8	0.679
40	55	0	8	0.679
86	102	0	8	0.678
41	82	0	8	0.677
72	92	0	8	0.676
46	95	0	8	0.676
43	54	0	8	0.676
55	93	0	8	0.676
71	84	0	8	0.676
41	104	0	8	0.674
58	73	0	8	0.674
71	86	0	8	0.673
58	81	0	8	0.673
44	83	0	8	0.673
83	95	0	8	0.672
56	93	0	8	0.672
46	66	0	8	0.671
46	104	0	8	0.671
59	94	0	8	0.67
58	83	0	8	0.67
42	93	0	8	0.669
46	73	0	8	0.669
41	94	0	8	0.668
41	56	0	8	0.668
83	106	0	8	0.667
57	106	0	8	0.666
43	106	0	8	0.666
80	104	0	8	0.666
54	102	0	8	0.666
80	103	0	8	0.666
46	86	0	8	0.665
59	86	0	8	0.665
72	106	0	8	0.664
19	66	0	8	0.663
80	102	0	8	0.663
83	103	0	8	0.663
105	149	0	8	0.663
72	93	0	8	0.663
80	94	0	8	0.663
83	93	0	8	0.661
83	94	0	8	0.661
85	95	0	8	0.659
73	92	0	8	0.659
57	107	0	8	0.659
39	149	0	8	0.658
55	105	0	8	0.658
91	106	0	8	0.657
57	72	0	8	0.657
42	94	0	8	0.656
55	102	0	8	0.656
55	104	0	8	0.655
57	84	0	8	0.654
71	81	0	8	0.654
42	56	0	8	0.653
93	102	0	8	0.653
42	148	0	8	0.653
41	105	0	8	0.653
42	106	0	8	0.653
83	92	0	8	0.652
84	93	0	8	0.652
55	92	0	8	0.652
19	103	0	8	0.652
86	106	0	8	0.652
40	96	0	8	0.652
55	95	0	8	0.652
59	106	0	8	0.651
80	149	0	8	0.651
55	106	0	8	0.651
57	83	0	8	0.65
41	92	0	8	0.65
57	91	0	8	0.65
42	58	0	8	0.649
72	149	0	8	0.649
54	80	0	8	0.649
59	103	0	8	0.648
72	84	0	8	0.648
107	149	0	8	0.646
56	73	0	8	0.646
59	104	0	8	0.646
42	82	0	8	0.645
59	105	0	8	0.645
59	72	0	8	0.644
102	149	0	8	0.644
20	66	0	8	0.644
42	95	0	8	0.644
86	104	0	8	0.643
80	93	0	8	0.643
55	72	0	8	0.643
58	80	0	8	0.643
73	107	0	8	0.642
39	86	0	8	0.642
40	86	0	8	0.642
42	83	0	8	0.641
19	105	0	8	0.64
40	104	0	8	0.639
85	102	0	8	0.639
41	84	0	8	0.639
40	93	0	8	0.639
40	106	0	8	0.638
85	104	0	8	0.638
59	92	0	8	0.637
46	84	0	8	0.637
86	94	0	8	0.637
59	95	0	8	0.636
58	91	0	8	0.636
44	91	0	8	0.635
55	81	0	8	0.635
54	66	0	8	0.635
71	93	0	8	0.634
83	102	0	8	0.634
106	158	0	8	0.634
46	82	0	8	0.633
46	57	0	8	0.632
71	80	0	8	0.631
66	82	0	8	0.631
44	106	0	8	0.631
56	149	0	8	0.63
44	93	0	8	0.63
72	81	0	8	0.63
41	57	0	8	0.63
55	82	0	8	0.629
55	86	0	8	0.629
86	107	0	8	0.629
39	54	0	8	0.629
81	103	0	8	0.629
41	95	0	8	0.628
19	58	0	8	0.628
83	105	0	8	0.627
54	87	0	8	0.625
15	46	0	8	0.625
72	85	0	8	0.625
42	92	0	8	0.625
54	106	0	8	0.625
42	103	0	8	0.625
80	87	0	8	0.624
91	107	0	8	0.624
40	85	0	8	0.624
66	107	0	8	0.624
73	106	0	8	0.624
END

