T0587.template-lib

Sequence_ID	Length	Evalue	FSSP-rep	SCOP_domain
2drhA	355	2.944e-47
1b65A	364	1.165e-43	1b65A	d.154.1.1
2vebA	191	4.508e-01
3ihrA	283	5.827e-01
1ejrC	554	5.859e-01	1ubpC	b.92.1.1
				c.1.9.2
2zexA	148	7.967e-01
2k3nA	161	8.121e-01
2k3oA	130	1.080e+00
1cisA	67	1.656e+00		k.1.1.1
3a7sA	205	1.781e+00
1njhA	109	2.201e+00		b.128.1.1
1qhbA	596	2.208e+00	1qhbA	a.111.1.2
2wdtA	205	2.308e+00
1u4gA	299	2.444e+00		d.92.1.2
1uch	207	3.098e+00	1uch
1zu4A	306	3.105e+00
3lg3A	420	4.532e+00
1kcxA	477	5.167e+00		b.92.1.3
				c.1.9.6
1vpmA	156	5.287e+00		d.38.1.1
1e58A	248	5.512e+00	1qhfA	c.60.1.1
1xd3A	230	5.535e+00		d.3.1.6
1xffA	239	5.702e+00		d.153.1.1
3eqnA	753	6.280e+00
1up8A	598	6.347e+00		a.111.1.2
2bitX	165	6.366e+00		b.62.1.1
3i4eA	413	6.578e+00
3gqhA	164	6.987e+00
2q09A	403	7.301e+00		b.92.1.10
				c.1.9.17
1hyt	317	8.116e+00	1hyt
1vbwA	69	8.297e+00
1go8P	461	8.897e+00		b.80.7.1
				d.92.1.6
1dwmA	70	9.673e+00	1hymA	d.40.1.1
1hymA	45	1.062e+01	1hymA	d.40.1.1
1yndA	165	1.087e+01		b.62.1.1
1rmgA	423	1.092e+01		b.80.1.3
1ypcI	65	1.146e+01	2sniI	d.40.1.1
2jpjA	40	1.154e+01
1coaI	65	1.157e+01	2sniI	d.40.1.1
1qhfA	241	1.200e+01	1qhfA	c.60.1.1
2bkmA	129	1.210e+01
1g31A	108	1.268e+01	1g31A	b.35.1.1
1cmxA	215	1.311e+01	1uch	d.3.1.6
1s8eA	334	1.338e+01		d.159.1.4
3c7tA	260	1.365e+01
1fwcC	567	1.376e+01	1ubpC	b.92.1.1
				c.1.9.2
1ciqA	38	1.379e+01	2sniI	d.40.1.1
1eysH	239	1.391e+01	6prcH	b.41.1.1
				f.23.10.1
1ezm	299	1.401e+01	1hyt
2pjzA	262	1.562e+01
2gokA	405	1.627e+01		b.92.1.10
				c.1.9.17
2amnA	27	1.638e+01
2yvaA	194	1.652e+01
1onxA	390	1.675e+01		b.92.1.7
				c.1.9.13
1q15A	492	1.700e+01		c.26.2.1
				d.153.1.1
2gd9A	178	1.804e+01
2jsnA	97	1.809e+01
1to2I	64	1.836e+01		d.40.1.1
2i2wA	193	1.877e+01
2k75A	107	1.900e+01
1ykhB	115	1.922e+01		a.252.1.1
1ar72	269	1.941e+01	1aym2
1riiA	244	1.948e+01		c.60.1.1
3d4iA	274	2.020e+01
1h80A	434	2.023e+01		b.80.1.8
1ejjA	509	2.074e+01	1ejjA	c.105.1.1
				c.76.1.3
1lw6I	64	2.101e+01		d.40.1.1
2p9bA	408	2.157e+01		b.92.1.10
				c.1.9.17
1wp1A	457	2.200e+01		f.5.1.1
1gycA	500	2.262e+01		b.6.1.3
				b.6.1.3
				b.6.1.3
1fzdA	198	2.305e+01	3fib	d.171.1.1
2xblA	195	2.370e+01
1ujnA	339	2.421e+01		e.22.1.1
8abpA	306	2.437e+01		c.93.1.1
2cobA	71	2.478e+01		a.4.1.15
2aqlA	159	2.534e+01
1svpA	161	2.537e+01	1svpA	b.47.1.3
1jniA	63	2.551e+01		a.138.1.3
2puzA	405	2.573e+01		b.92.1.10
				c.1.9.17
3le2A	394	2.584e+01
1k7gA	456	2.612e+01		b.80.7.1
				d.92.1.6
1kyzA	351	2.650e+01		a.4.5.29
				c.66.1.12
2qniA	195	2.669e+01
2qq2A	157	2.694e+01
1chd	199	2.735e+01	1chd

Sequence_ID	Length	Evalue	FSSP-rep	SCOP_domain
2oqzA	216	2.795e+01		b.100.1.1
2kbnA	110	2.811e+01
2weeA	190	2.823e+01
1dfaA	406	2.845e+01	1vdeA	b.86.1.2
				d.95.2.2
				d.95.2.2
3g79A	476	2.878e+01
1b93A	149	2.893e+01	1b93A	c.24.1.2
2q4wA	492	2.901e+01
1ld4A	152	2.947e+01		i.6.1.1
1bymA	98	2.969e+01	1bi0	b.34.1.2
1fbtA	191	2.984e+01	1bif	c.60.1.4
1r17A	322	2.994e+01		b.2.3.4
				b.2.3.4
1ngkA	127	2.997e+01		a.1.1.1
1wxrA	1036	3.052e+01
2x3yA	203	3.073e+01
2p75A	172	3.142e+01
3fpfA	265	3.212e+01
1ct9A	498	3.326e+01	1ct9A	c.26.2.1
				d.153.1.1
2jhmF	218	3.407e+01
3kt9A	103	3.439e+01
1wi5A	120	3.466e+01		b.40.4.5
1ejxC	557	3.480e+01		b.92.1.1
				c.1.9.2
3d5kA	456	3.520e+01
1qyrA	253	3.556e+01		c.66.1.24
3h04A	273	3.578e+01
1af0A	471	3.591e+01	1sat	b.80.7.1
				d.92.1.6
2vdxA	367	3.710e+01
1avpA	205	3.721e+01	1avpA	d.3.1.7
1aopA	457	3.841e+01		d.58.36.1
				d.58.36.1
				d.134.1.1
				d.134.1.1
2ip2A	331	3.972e+01

Please cite the following papers:

Karplus, K. and Karchin, R. and Barrett, C. and Tu, S. and Cline, M. and Diekhans, M. and Grate, L. and Casper, J. and Hughey, R. ``What is the value added by human intervention in protein structure prediction?'' Proteins: Structure Function and Genetics 45(S5):86-91,2001
Karplus, K. and Karchin, R. and Draper, J. and Casper, J. and Mandel-Gutfreund, Y. and Diekhans, M. and Hughey, R. ``Combining local-structure, fold-recognition, and new-fold methods for protein structure prediction'' Proteins: Structure Function and Genetics53(S6):491-496,15 Oct 2003
Rachel Karchin, Melissa Cline, Yael Mandel-Gutfreund, and Kevin Karplus. ``Hidden Markov models that use predicted local structure for fold recognition: alphabets of backbone geometry.'' Proteins: Structure, Function, and Genetics, 51(4):504--514, June 2003.