| 1div |
| ID: | 1471616426 |
Query Sequence |
Download Alignment We filter this alignment to remove positions that have > 50% gaps before running GREMLIN. |
| Length: | 149 (147) | ||
| Sequences: | 3556 (2194.8) | ||
| Seq/Len: | 24.190 | ||
| Nf(neff/√len): | 181.0 |
HHblits Results: (2016_02)
Sequences per length for each position, BEFORE the coverage/gap filter was applied
Legend: Dots above the red line, indicates positions where there is > 5 sequences per length (if visible, green bar = 20 seq/len). Point of this graphic is to give you an idea if resubmitting a sub-portion of your sequence might help increase the overall Seq/Len (which after applying the coverage filter is at: 24.190).
Sequences per length for each position, AFTER the coverage/gap filter was applied
Residue pairs sorted by coevolution strength:
Legend: The darker and larger the blue dots, the higher strength in covariance. Below we provide the list of the top [1.5 x length] covarying residues with sequence seperation > 3. The i and j are positions as given in the input sequence.
| i | j | Scaled score | Prob |
| 2_K | 20_N | 3.253 | 1.00 |
| 62_L | 66_K | 2.895 | 1.00 |
| 103_Q | 109_K | 2.640 | 1.00 |
| 128_N | 140_T | 2.621 | 1.00 |
| 7_K | 35_L | 2.599 | 1.00 |
| 128_N | 142_K | 2.489 | 1.00 |
| 126_Y | 144_H | 2.408 | 1.00 |
| 59_A | 63_A | 2.278 | 1.00 |
| 80_P | 146_T | 2.130 | 1.00 |
| 123_A | 127_T | 2.062 | 1.00 |
| 78_T | 146_T | 1.999 | 1.00 |
| 5_F | 19_K | 1.982 | 1.00 |
| 78_T | 144_H | 1.938 | 1.00 |
| 101_S | 104_A | 1.875 | 1.00 |
| 48_E | 51_K | 1.855 | 1.00 |
| 5_F | 13_G | 1.794 | 1.00 |
| 55_Q | 59_A | 1.778 | 1.00 |
| 67_K | 71_Q | 1.732 | 1.00 |
| 26_A | 31_F | 1.705 | 1.00 |
| 134_H | 137_V | 1.689 | 1.00 |
| 67_K | 70_E | 1.671 | 1.00 |
| 30_L | 36_A | 1.663 | 1.00 |
| 9_V | 35_L | 1.642 | 1.00 |
| 45_K | 48_E | 1.625 | 1.00 |
| 63_A | 66_K | 1.620 | 1.00 |
| 130_P | 138_T | 1.616 | 1.00 |
| 70_E | 73_E | 1.592 | 1.00 |
| 102_L | 110_L | 1.590 | 1.00 |
| 53_K | 57_Q | 1.582 | 1.00 |
| 41_P | 45_K | 1.523 | 1.00 |
| 46_A | 50_Q | 1.522 | 1.00 |
| 65_A | 134_H | 1.512 | 1.00 |
| 56_R | 60_E | 1.472 | 1.00 |
| 64_N | 67_K | 1.466 | 1.00 |
| 99_A | 115_I | 1.465 | 1.00 |
| 66_K | 70_E | 1.459 | 1.00 |
| 63_A | 67_K | 1.452 | 1.00 |
| 77_V | 102_L | 1.443 | 1.00 |
| 69_K | 73_E | 1.405 | 0.99 |
| 1_M | 26_A | 1.389 | 0.99 |
| 77_V | 101_S | 1.380 | 0.99 |
| 2_K | 44_L | 1.349 | 0.99 |
| 52_Q | 55_Q | 1.342 | 0.99 |
| 5_F | 12_K | 1.331 | 0.99 |
| 129_V | 143_V | 1.330 | 0.99 |
| 18_I | 44_L | 1.329 | 0.99 |
| 60_E | 64_N | 1.329 | 0.99 |
| 81_A | 93_I | 1.321 | 0.99 |
| 79_I | 101_S | 1.311 | 0.99 |
| 81_A | 89_L | 1.301 | 0.99 |
| 66_K | 69_K | 1.299 | 0.99 |
| 45_K | 49_A | 1.286 | 0.99 |
| 8_D | 14_K | 1.274 | 0.99 |
| 121_I | 145_V | 1.271 | 0.99 |
| 121_I | 143_V | 1.269 | 0.99 |
| 130_P | 140_T | 1.268 | 0.99 |
| 4_I | 43_N | 1.260 | 0.99 |
| 54_E | 58_A | 1.245 | 0.98 |
| 3_V | 26_A | 1.241 | 0.98 |
| 6_L | 37_I | 1.221 | 0.98 |
| 42_A | 46_A | 1.218 | 0.98 |
| 39_A | 44_L | 1.216 | 0.98 |
| 69_K | 139_A | 1.214 | 0.98 |
| 37_I | 43_N | 1.206 | 0.98 |
| 49_A | 52_Q | 1.198 | 0.98 |
| 51_K | 55_Q | 1.194 | 0.98 |
| 101_S | 105_Q | 1.181 | 0.98 |
| 76_T | 144_H | 1.179 | 0.98 |
| 2_K | 18_I | 1.177 | 0.98 |
| 53_K | 56_R | 1.169 | 0.97 |
| 43_N | 46_A | 1.168 | 0.97 |
| 75_L | 106_H | 1.167 | 0.97 |
| 124_L | 147_E | 1.157 | 0.97 |
| 51_K | 54_E | 1.146 | 0.97 |
| 100_E | 104_A | 1.128 | 0.97 |
| 132_K | 138_T | 1.126 | 0.97 |
| 126_Y | 142_K | 1.099 | 0.96 |
| 57_Q | 61_E | 1.096 | 0.96 |
| 102_L | 106_H | 1.093 | 0.96 |
| 115_I | 131_V | 1.090 | 0.96 |
| 44_L | 48_E | 1.086 | 0.96 |
| 31_F | 34_G | 1.086 | 0.96 |
| 58_A | 61_E | 1.084 | 0.96 |
| 49_A | 53_K | 1.052 | 0.95 |
| 12_K | 25_Y | 1.043 | 0.94 |
| 102_L | 141_L | 1.042 | 0.94 |
| 71_Q | 108_L | 1.031 | 0.94 |
| 42_A | 45_K | 1.024 | 0.93 |
| 58_A | 62_L | 1.019 | 0.93 |
| 92_S | 122_R | 1.001 | 0.92 |
Prob = P(contact | scaled_score, seq/len).
Scaled Score = (raw_score/average(raw_scores)).
- Text file of contact predictions (all 3L/2 predictions)
- Generate restraints for ROSETTA Structure Modeling
- Import to GREMLIN BETA - features includes ability to upload PDB and latest P(contact) calculation based on eLife 2015 fitting to PDB data.
GREMLIN results overlayed on top 10 PDB hits:
Legend: Blue filled circles are GREMLIN results (Scaled Score > 1). The grey/red filled circles underneath are pdb residue contacts (min distance < 5 Angstroms). The shade of the circles is based on 10 HHsearch results which uses the overall probability and per-position alignment confidence. Inter oligomeric contacts in the pdb are in shades of red.
| PDB | M | Cov | P(%) | HHΔ | |
| 1divA | 1 | 1 | 100 | -0.036 | Contact Map |
| 3bboJ | 1 | 0.9866 | 100 | -0.016 | Contact Map |
| 4rb6I | 1 | 0.9799 | 100 | -0.013 | Contact Map |
| 4tp9H | 1 | 0.9866 | 100 | -0.011 | Contact Map |
| 1nkwF | 1 | 0.349 | 100 | 0.004 | Contact Map |
| 3j7yH | 1 | 0.3624 | 100 | 0.082 | Contact Map |
| 2hbaA | 2 | 0.349 | 99.8 | 0.499 | Contact Map |
| 1vw4G | 1 | 0.302 | 99.8 | 0.52 | Contact Map |
| 4qjty | 1 | 0.8591 | 99.7 | 0.564 | Contact Map |
| 3pxgA | 6 | 0.6577 | 30.4 | 0.917 | Contact Map |
Cov = coverage of hit
P(%) = probability
Sequence Conservation (Image Generated using WebLogo v3)