CASP8 TS Evaluations

CASP8 Preliminary Results of Tertiary Structure Predictions Based on 120 Targets

1. The ranking of TS methods by the sum of TM scores of the NO. 1 models based on 120 targets:

RANK	Method Name	Sum of TM Scores
1	Zhang-Server	84.6741
2	pro-sp3-TASSER	82.2468
3	METATASSER	81.835
4	RAPTOR	81.3194
5	Phyre_de_novo	80.8532
6	HHpred5	80.8194
7	MULTICOM-REFINE	80.8163
8	BAKER-ROBETTA	80.6332
9	MULTICOM-CLUSTER	80.562
10	HHpred4	80.5485
11	HHpred2	80.5366
12	MUProt	80.3992
13	MUSTER	79.8696
14	FAMSD	79.8674
15	Pcons_multi	79.493
16	MULTICOM-RANK	79.3057
17	GS-KudlatyPred	79.1314
18	MULTICOM-CMFR	79.0311
19	SAM-T08-server	78.8856
20	COMA-M	78.8515
21	3DShot2	78.7949
22	PS2-server	78.1421
23	circle	78.1055
24	Phyre2	77.912
25	FFASsuboptimal	77.8319
26	FEIG	77.5552
27	PSI	77.4123
28	COMA	77.0552
29	Phragment	76.986
30	FFASstandard	76.5338
31	Poing	76.3948
32	FFASflextemplate	76.1363
33	nFOLD3	75.5425
34	FALCON	75.4344
35	mGenTHREADER	75.3265
36	Pcons_dot_net	75.3178
37	3D-JIGSAW_V3	75.2612
38	GeneSilicoMetaServer	75.2327
39	CpHModels	74.949
40	BioSerf	74.7500999999999
41	3D-JIGSAW_AEP	74.6406
42	fais-server	74.4655
43	SAM-T06-server	74.4351
44	GS-MetaServer2	73.9964
45	Pcons_local	72.6828
46	pipe_int	71.4693
47	keasar-server	70.5736
48	FALCON_CONSENSUS	70.093
49	3Dpro	69.6459
50	forecast	66.7771
51	ACOMPMOD	66.1798
52	MUFOLD-Server	65.5483
53	panther_server	65.1929
54	Frankenstein	64.2603
55	Distill	63.5792
56	Pushchino	61.3356
57	rehtnap	60.6139
58	LOOPP_Server	60.3436
59	LEE-SERVER	58.7812
60	Fiser-M4T	53.7415
61	FOLDpro	52.5168
62	YASARA	47.5848
63	mariner1	44.759
64	OLGAFS	38.8945
65	huber-torda-server	37.9116
66	MUFOLD-MD	37.2221
67	RBO-Proteus	33.762
68	schenk-torda-server	18.1892
69	mahmood-torda-server	10.8633
70	BHAGEERATH	1.1778
71	SAM-T02-server_AL1	BLANK
72	SAM-T02-server_AL2	BLANK
73	FUGUE_KM_AL1	BLANK
74	SAM-T02-server_AL4	BLANK
75	FUGUE_KM_AL4	BLANK
76	SAM-T02-server_AL3	BLANK
77	FUGUE_KM_AL3	BLANK
78	SAM-T02-server_AL5	BLANK
79	FUGUE_KM_AL2	BLANK

2. The ranking of TS methods by the sum of TM scores of the best models (with highest TM scores) out of five based on 120 targets:

RANK	Method Name	Sum of TM Scores
1	Zhang-Server	86.6839
2	pro-sp3-TASSER	85.443
3	METATASSER	85.1278
4	MULTICOM-CLUSTER	83.4368
5	RAPTOR	83.1176
6	MUSTER	82.9778
7	BAKER-ROBETTA	82.9047
8	FEIG	82.7523
9	MULTICOM-REFINE	82.7417
10	Phyre_de_novo	82.5638
11	MUProt	82.3528
12	FAMSD	82.0025
13	MULTICOM-CMFR	81.7753
14	MULTICOM-RANK	81.684
15	Pcons_multi	81.6383
16	PS2-server	80.9097
17	circle	80.9043
18	PSI	80.8802
19	HHpred5	80.8194
20	SAM-T08-server	80.6832
21	Phyre2	80.6448
22	nFOLD3	80.549
23	HHpred4	80.5485
24	HHpred2	80.5366
25	COMA-M	80.4428
26	COMA	80.4123
27	GS-KudlatyPred	80.3046
28	fais-server	80.0552999999999
29	Phragment	79.5674
30	FALCON	79.2244
31	Poing	79.1092
32	Pcons_dot_net	79.0436
33	FFASstandard	79.0137
34	3DShot2	78.7949
35	GeneSilicoMetaServer	78.6739
36	FFASsuboptimal	78.5204
37	SAM-T06-server	78.3112
38	GS-MetaServer2	78.0042
39	FALCON_CONSENSUS	77.6219
40	Pcons_local	76.8315
41	3D-JIGSAW_V3	76.7841
42	FFASflextemplate	76.5286
43	3D-JIGSAW_AEP	76.294
44	mGenTHREADER	75.3265
45	BioSerf	75.0700999999999
46	CpHModels	74.949
47	keasar-server	74.3033
48	3Dpro	73.0953
49	pipe_int	72.5291
50	panther_server	71.2625
51	ACOMPMOD	71.0643
52	forecast	69.6126
53	LOOPP_Server	68.8962
54	MUFOLD-Server	67.4749
55	Frankenstein	66.8226
56	FOLDpro	65.3353
57	Distill	64.7498
58	rehtnap	62.7222
59	mariner1	61.5025
60	Pushchino	61.3356
61	LEE-SERVER	59.5234
62	Fiser-M4T	53.7415
63	YASARA	48.1938
64	OLGAFS	43.9891
65	MUFOLD-MD	42.2947
66	huber-torda-server	40.7319
67	RBO-Proteus	36.8638
68	schenk-torda-server	20.0959
69	mahmood-torda-server	13.705
70	BHAGEERATH	1.271
71	SAM-T02-server_AL1	0
72	SAM-T02-server_AL2	0
73	FUGUE_KM_AL1	0
74	SAM-T02-server_AL4	0
75	FUGUE_KM_AL4	0
76	SAM-T02-server_AL3	0
77	FUGUE_KM_AL3	0
78	SAM-T02-server_AL5	0
79	FUGUE_KM_AL2	0

3. The ranking of TS methods by the sum of GDT-TS scores of the NO. 1 model based on 120 targets:

RANK	Method Name	Sum of GDT-TS Scores	NO. of Targets
1	Zhang-Server	75.5184	120
2	pro-sp3-TASSER	72.8916	120
3	RAPTOR	72.8145	120
4	Phyre_de_novo	72.2954	120
5	METATASSER	72.0946	120
6	MULTICOM-REFINE	72.0432	120
7	HHpred5	71.9753	120
8	MULTICOM-CLUSTER	71.8341	120
9	MUProt	71.6399	120
10	BAKER-ROBETTA	71.5919	120
11	HHpred4	71.4565	120
12	HHpred2	71.3293	120
13	MULTICOM-RANK	70.7783	120
14	FAMSD	70.723	120
15	MUSTER	70.6397	120
16	GS-KudlatyPred	70.6208	119
17	Pcons_multi	70.3953	120
18	COMA-M	70.2087	120
19	MULTICOM-CMFR	70.1791	120
20	SAM-T08-server	69.8361	120
21	PS2-server	69.6243	120
22	FFASsuboptimal	69.3195	120
23	circle	69.0414	120
24	3DShot2	68.8215	120
25	Phyre2	68.6052000000001	120
26	PSI	68.0729	120
27	FFASstandard	68.0639	120
28	COMA	67.9261	120
29	Phragment	67.8691	120
30	FEIG	67.7988	120
31	FFASflextemplate	67.6155	119
32	mGenTHREADER	67.4272	120
33	Poing	67.2076	120
34	nFOLD3	66.8533	120
35	Pcons_dot_net	66.817	116
36	GeneSilicoMetaServer	66.7971	118
37	3D-JIGSAW_V3	66.7769	120
38	CpHModels	66.6464	119
39	3D-JIGSAW_AEP	66.4101	120
40	FALCON	66.2967	120
41	BioSerf	66.2666	119
42	GS-MetaServer2	65.8756	118
43	SAM-T06-server	65.4717	120
44	fais-server	65.2874	115
45	Pcons_local	64.6366	118
46	pipe_int	63.4154	110
47	keasar-server	63.1432	109
48	3Dpro	61.2953	117
49	FALCON_CONSENSUS	60.5472	119
50	forecast	58.4104	116
51	ACOMPMOD	57.7837	118
52	Frankenstein	57.3292	105
53	panther_server	56.7952	108
54	MUFOLD-Server	56.0461	120
55	Pushchino	55.1259	105
56	LOOPP_Server	53.1347	110
57	LEE-SERVER	53.0883	78
58	rehtnap	53.0614	118
59	Distill	52.9497	119
60	Fiser-M4T	48.7557	75
61	FOLDpro	44.0413	120
62	YASARA	43.7692	60
63	mariner1	37.0272	118
64	OLGAFS	34.3042	105
65	huber-torda-server	34.0846	74
66	MUFOLD-MD	31.2081	117
67	RBO-Proteus	28.2101	119
68	schenk-torda-server	13.7362	109
69	mahmood-torda-server	9.5137	65
70	BHAGEERATH	1.3032	5
71	SAM-T02-server_AL1	BLANK	0
72	SAM-T02-server_AL2	BLANK	0
73	FUGUE_KM_AL1	BLANK	0
74	SAM-T02-server_AL4	BLANK	0
75	FUGUE_KM_AL4	BLANK	0
76	SAM-T02-server_AL3	BLANK	0
77	FUGUE_KM_AL3	BLANK	0
78	SAM-T02-server_AL5	BLANK	0
79	FUGUE_KM_AL2	BLANK	0

4. The ranking of TS methods by the sum of GDT-TS scores of the best models (with highest GDT-TS scores) out of five based on 120 targets:

RANK	Method Name	Sum of GDT-TS Scores
1	Zhang-Server	77.303
2	pro-sp3-TASSER	76.0127
3	METATASSER	75.5572
4	RAPTOR	74.6241000000001
5	MULTICOM-CLUSTER	74.542
6	MUSTER	73.8884
7	Phyre_de_novo	73.8757
8	MULTICOM-REFINE	73.8176
9	BAKER-ROBETTA	73.6128
10	MUProt	73.3601
11	FEIG	73.2191
12	MULTICOM-RANK	72.9559
13	MULTICOM-CMFR	72.8718
14	FAMSD	72.8074
15	Pcons_multi	72.7735999999999
16	PS2-server	72.3126
17	circle	72.0395
18	HHpred5	71.9753
19	SAM-T08-server	71.8698
20	COMA-M	71.8293999999999
21	PSI	71.7834
22	nFOLD3	71.7155
23	Phyre2	71.6903
24	GS-KudlatyPred	71.6727
25	COMA	71.5081
26	HHpred4	71.4565
27	HHpred2	71.3293
28	fais-server	70.786
29	FFASstandard	70.7499
30	Phragment	70.6394
31	Pcons_dot_net	70.5561
32	GeneSilicoMetaServer	70.3614
33	FALCON	70.2147
34	FFASsuboptimal	70.015
35	Poing	69.9928
36	SAM-T06-server	69.9762
37	GS-MetaServer2	69.7067
38	3DShot2	68.8215
39	Pcons_local	68.6524
40	3D-JIGSAW_V3	68.3304
41	FALCON_CONSENSUS	68.3282
42	FFASflextemplate	68.1299
43	3D-JIGSAW_AEP	67.9892000000001
44	mGenTHREADER	67.4272
45	keasar-server	66.7547
46	CpHModels	66.6464
47	BioSerf	66.5123
48	pipe_int	64.5971
49	3Dpro	64.5836
50	panther_server	62.7499
51	ACOMPMOD	62.0536
52	forecast	61.2674
53	LOOPP_Server	60.8152
54	Frankenstein	59.6068
55	MUFOLD-Server	57.9297
56	FOLDpro	55.8344
57	rehtnap	55.4216
58	Pushchino	55.1259
59	Distill	54.2473
60	LEE-SERVER	53.8565
61	mariner1	53.5414
62	Fiser-M4T	48.7557
63	YASARA	44.5067
64	OLGAFS	39.4605
65	huber-torda-server	37.0434
66	MUFOLD-MD	35.4366
67	RBO-Proteus	30.5698
68	schenk-torda-server	14.9786
69	mahmood-torda-server	11.7758
70	BHAGEERATH	1.4038
71	SAM-T02-server_AL1	0
72	SAM-T02-server_AL2	0
73	FUGUE_KM_AL1	0
74	SAM-T02-server_AL4	0
75	FUGUE_KM_AL4	0
76	SAM-T02-server_AL3	0
77	FUGUE_KM_AL3	0
78	SAM-T02-server_AL5	0
79	FUGUE_KM_AL2	0

5. The ranking of TS methods by the sum of MaxSub scores of the NO. 1 models based on 120 targets:

RANK	Method Name	Sum of MaxSub Scores
1	Zhang-Server	71.7875
2	RAPTOR	69.0238
3	pro-sp3-TASSER	68.8298
4	METATASSER	68.7603
5	HHpred5	67.9616
6	Phyre_de_novo	67.9445
7	MULTICOM-REFINE	67.76
8	MULTICOM-CLUSTER	67.7549
9	MUProt	67.4281
10	BAKER-ROBETTA	67.2731
11	HHpred4	67.2624
12	HHpred2	67.1043
13	GS-KudlatyPred	66.5143
14	FAMSD	66.508
15	MULTICOM-RANK	66.3536
16	Pcons_multi	66.336
17	MUSTER	66.1674
18	MULTICOM-CMFR	65.8532
19	COMA-M	65.5762
20	SAM-T08-server	65.4979
21	PS2-server	65.4749
22	3DShot2	65.2904
23	FFASsuboptimal	65.2478
24	circle	64.7389
25	FFASstandard	64.3616
26	Phyre2	64.232
27	FEIG	63.9182
28	FFASflextemplate	63.6672
29	PSI	63.5743
30	COMA	63.511
31	mGenTHREADER	63.3181
32	Phragment	63.2584
33	CpHModels	63.0429
34	Pcons_dot_net	62.9237
35	GeneSilicoMetaServer	62.9146
36	nFOLD3	62.8037
37	Poing	62.4616
38	3D-JIGSAW_AEP	62.2001
39	GS-MetaServer2	62.1667
40	3D-JIGSAW_V3	62.1065
41	BioSerf	61.4808
42	fais-server	61.2056
43	FALCON	61.2031
44	Pcons_local	60.8206
45	SAM-T06-server	60.3159
46	pipe_int	59.1776
47	keasar-server	58.8603
48	3Dpro	57.0689
49	FALCON_CONSENSUS	55.3181
50	forecast	53.4757
51	panther_server	53.338
52	Frankenstein	53.1263
53	ACOMPMOD	52.8045
54	Pushchino	51.5325
55	LEE-SERVER	50.9499
56	MUFOLD-Server	49.7235
57	rehtnap	49.288
58	Distill	48.5941
59	LOOPP_Server	48.4766
60	Fiser-M4T	46.9775
61	YASARA	41.9383
62	FOLDpro	37.9023
63	mariner1	31.4023
64	huber-torda-server	31.3767
65	OLGAFS	30.1681
66	MUFOLD-MD	25.2152
67	RBO-Proteus	22.6004
68	schenk-torda-server	9.4587
69	mahmood-torda-server	6.4457
70	BHAGEERATH	1.034
71	SAM-T02-server_AL1	BLANK
72	SAM-T02-server_AL2	BLANK
73	FUGUE_KM_AL1	BLANK
74	SAM-T02-server_AL4	BLANK
75	FUGUE_KM_AL4	BLANK
76	SAM-T02-server_AL3	BLANK
77	FUGUE_KM_AL3	BLANK
78	SAM-T02-server_AL5	BLANK
79	FUGUE_KM_AL2	BLANK

6. The ranking of TS methods by the sum of MaxSub scores of the best models (with highest MaxSub scores) out of five based on 120 targets:

RANK	Method Name	Sum of MaxSub Scores
1	Zhang-Server	73.7416
2	pro-sp3-TASSER	72.4221
3	METATASSER	72.2778
4	MULTICOM-CLUSTER	71.1492
5	RAPTOR	71.04
6	FEIG	70.1182
7	MUSTER	69.992
8	MULTICOM-REFINE	69.9891
9	Phyre_de_novo	69.9637
10	MUProt	69.4987
11	BAKER-ROBETTA	69.4197
12	FAMSD	69.1658
13	MULTICOM-CMFR	68.9841
14	MULTICOM-RANK	68.9782999999999
15	Pcons_multi	68.7439
16	PS2-server	68.6952
17	SAM-T08-server	68.3605
18	nFOLD3	68.3004
19	PSI	68.1479
20	circle	68.118
21	HHpred5	67.9616
22	Phyre2	67.8316
23	GS-KudlatyPred	67.5971
24	COMA-M	67.5723
25	COMA	67.4151
26	HHpred4	67.2624
27	HHpred2	67.1043
28	FFASstandard	67.0724
29	GeneSilicoMetaServer	66.9689
30	fais-server	66.8724
31	Pcons_dot_net	66.7498
32	Phragment	66.6238
33	SAM-T06-server	66.4499
34	GS-MetaServer2	66.3752
35	FFASsuboptimal	66.2075
36	FALCON	66.014
37	Poing	65.8578
38	3DShot2	65.2904
39	Pcons_local	65.1966
40	FFASflextemplate	64.2136
41	3D-JIGSAW_V3	63.8426
42	3D-JIGSAW_AEP	63.7543
43	FALCON_CONSENSUS	63.6703
44	mGenTHREADER	63.3181
45	keasar-server	63.0618
46	CpHModels	63.0429
47	BioSerf	61.7345
48	3Dpro	60.6666
49	pipe_int	60.6159
50	panther_server	59.3672
51	ACOMPMOD	57.0634
52	forecast	56.826
53	LOOPP_Server	56.6398
54	Frankenstein	56.0937
55	rehtnap	51.9621
56	MUFOLD-Server	51.9297
57	LEE-SERVER	51.8993
58	Pushchino	51.5325
59	FOLDpro	50.4459
60	Distill	50.0814
61	mariner1	48.3764
62	Fiser-M4T	46.9775
63	YASARA	42.872
64	OLGAFS	35.6034
65	huber-torda-server	34.351
66	MUFOLD-MD	29.5871
67	RBO-Proteus	24.7985
68	schenk-torda-server	10.6795
69	mahmood-torda-server	8.1423
70	BHAGEERATH	1.0798
71	SAM-T02-server_AL1	0
72	SAM-T02-server_AL2	0
73	FUGUE_KM_AL1	0
74	SAM-T02-server_AL4	0
75	FUGUE_KM_AL4	0
76	SAM-T02-server_AL3	0
77	FUGUE_KM_AL3	0
78	SAM-T02-server_AL5	0
79	FUGUE_KM_AL2	0

If you have any comments or questions, you are welcome to contact Dr. Jianlin Cheng at chengji@missouri.edu or Zheng Wang at zwyw6@mizzou.edu.

Last modified on Sep 29th, 2008.