Q9KLT9
multicom
Q9KLT9
full_length
Q9KLT9
Results of Structure Prediction for Target Name: Q9KLT9 ( Click 
)
Domain Boundary prediction ( View )
>Q9KLT9: 1-145
| 1-60: |
M | S | E | T | N | Q | T | E | T | P | K | V | D | L | E | S | I | S | P | E | L | R | Q | V | L | E | F | D | Q | V | P | E | A | M | F | H | M | V | T | S | I | H | E | V | S | E | E | V | V | R | E | A | W | D | S | L | P | A | S | A |
| 61-119: |
Q | N | I | L | D | N | F | E | Q | F | H | A | L | I | S | V | S | Q | A | F | A | G | L | N | V | M | E | E | F | P | T | L | N | L | P | K | E | M | S | E | E | D | K | D | A | Y | R | A | Q | L | L | D | Q | V | L | H | N | C | V | K |
| 121-145: |
D | M | V | K | Q | I | K | K | A | R | R | D | P | I | L | K | R | D | F | K | D | V | F | A | K |
| 1-60: |
C | C | C | C | C | C | C | C | C | C | C | C | C | C | C | C | C | C | H | H | H | H | H | H | H | H | H | H | C | C | C | H | H | H | H | H | H | H | H | H | H | H | H | H | C | C | H | H | H | H | H | H | H | H | H | C | C | H | H | H |
| 61-119: |
H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | C | C | C | H | H | H | H | H | H | H | H | C | C | C | H | H | H | C | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H | H |
| 121-145: |
H | H | H | H | H | H | H | H | H | H | C | C | C | H | H | H | H | H | H | H | H | H | H | C | C |
| |
| | H(Helix): 108(74.48%) | E(Strand): 0(0%) | C(Coil): 37(25.52%) |
| 1-60: |
E | E | E | E | E | E | E | E | E | E | E | B | E | B | E | E | B | E | E | E | B | E | E | B | B | E | B | E | E | B | E | E | E | B | B | E | B | B | B | B | B | B | E | B | B | E | E | B | B | E | E | B | B | E | E | B | E | E | B | B |
| 61-119: |
E | E | B | B | E | B | B | E | B | B | B | B | B | B | B | B | B | B | B | B | B | B | B | E | B | B | E | B | B | E | E | B | E | B | E | E | E | B | E | E | E | E | E | E | E | B | B | E | E | B | B | E | E | B | B | E | E | B | B | E |
| 121-145: |
E | B | B | E | E | B | E | E | B | E | E | E | E | E | B | E | E | E | B | E | E | B | B | E | E |
| |
| | e(Exposed): 78(53.79%) | b(Buried): 67(46.21%) |
| 1-60: |
T | T | T | T | T | T | T | T | T | T | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| 61-119: |
N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| 121-145: |
N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N | N |
| |
| | N(Normal): 135(93.1%) | T(Disorder): 10(6.9%) |
Predicted contact map and distance map
|
Predicted distance map
|
|
Predicted contact map
|
Probability to Precision
| Long-Range |
Average probability |
Predicted precision |
| TopL/5 |
0.44 |
45.65 |
| TopL/2 |
0.31 |
34.31 |
Note: The linear model (Average probability vs Predicted precision) was trained on CASP14 dataset
|
Predicted Top 1 Tertiary structure
|
|
|
| Long-Range |
Precision |
| TopL/5 |
68.97 |
| TopL/2 |
49.32 |
| TopL |
34.48 |
| Top2L |
22.76 |
| Alignment |
Number |
| N |
151 |
| Neff |
13 |
|
Model comparsion
| Model |
TM-score |
| Model 2 |
0.9707 |
| Model 3 |
0.9776 |
| Model 4 |
0.9667 |
| Model 5 |
0.9647 |
| Average |
0.96993 |
Radius Gyration
|
Similar pdbs
| PDB |
TM-score |
| 2pv4 |
0.56990 |
| 6k7k |
0.55648 |
| 6k7g |
0.55540 |
| 6k7l |
0.55494 |
| 6k7i |
0.55325 |
|
Note: The model is built by ab initio method, no significant templates are found!
|
Predicted Top 2 Tertiary structure
|
|
|
| Long-Range |
Precision |
| TopL/5 |
65.52 |
| TopL/2 |
45.21 |
| TopL |
32.41 |
| Top2L |
21.38 |
| Alignment |
Number |
| N |
151 |
| Neff |
13 |
|
Model comparsion
| Model |
TM-score |
| Model 1 |
0.9707 |
| Model 3 |
0.9665 |
| Model 4 |
0.9598 |
| Model 5 |
0.9707 |
| Average |
0.96693 |
Radius Gyration
|
Similar pdbs
| PDB |
TM-score |
| 2pv4 |
0.57405 |
| 6ajf |
0.56515 |
| 5ztf |
0.56219 |
| 6ajj |
0.56210 |
| 6k7j |
0.56114 |
|
Note: The model is built by ab initio method, no significant templates are found!
|
Predicted Top 3 Tertiary structure
|
|
|
| Long-Range |
Precision |
| TopL/5 |
62.07 |
| TopL/2 |
45.21 |
| TopL |
32.41 |
| Top2L |
21.72 |
| Alignment |
Number |
| N |
151 |
| Neff |
13 |
|
Model comparsion
| Model |
TM-score |
| Model 1 |
0.9776 |
| Model 2 |
0.9665 |
| Model 4 |
0.9624 |
| Model 5 |
0.9649 |
| Average |
0.96785 |
Radius Gyration
|
Similar pdbs
| PDB |
TM-score |
| 2pv4 |
0.58290 |
| 6k7g |
0.55337 |
| 6k7l |
0.55164 |
| 6k7j |
0.55133 |
| 6k7i |
0.55131 |
|
Note: The model is built by ab initio method, no significant templates are found!
|
Predicted Top 4 Tertiary structure
|
|
|
| Long-Range |
Precision |
| TopL/5 |
65.52 |
| TopL/2 |
46.58 |
| TopL |
33.10 |
| Top2L |
21.72 |
| Alignment |
Number |
| N |
151 |
| Neff |
13 |
|
Model comparsion
| Model |
TM-score |
| Model 1 |
0.9667 |
| Model 2 |
0.9598 |
| Model 3 |
0.9624 |
| Model 5 |
0.9730 |
| Average |
0.96547 |
Radius Gyration
|
Similar pdbs
| PDB |
TM-score |
| 2pv4 |
0.57889 |
| 6iia |
0.57146 |
| 3t56 |
0.57112 |
| 6ajg |
0.57040 |
| 3w9i |
0.56920 |
|
Note: The model is built by ab initio method, no significant templates are found!
|
Predicted Top 5 Tertiary structure
|
|
|
| Long-Range |
Precision |
| TopL/5 |
65.52 |
| TopL/2 |
47.95 |
| TopL |
33.10 |
| Top2L |
21.38 |
| Alignment |
Number |
| N |
151 |
| Neff |
13 |
|
Model comparsion
| Model |
TM-score |
| Model 1 |
0.9647 |
| Model 2 |
0.9707 |
| Model 3 |
0.9649 |
| Model 4 |
0.9730 |
| Average |
0.96832 |
Radius Gyration
|
Similar pdbs
| PDB |
TM-score |
| 2pv4 |
0.57453 |
| 6k7l |
0.56064 |
| 6k7g |
0.56045 |
| 6k7i |
0.55996 |
| 6k7j |
0.55975 |
|
Note: The model is built by ab initio method, no significant templates are found!
|
References
[1] Hou, J., Wu, T., Cao, R., & Cheng, J. (2019). Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13. bioRxiv, 552422.
[2] Li, J., Deng, X., Eickholt, J., & Cheng, J. (2013). Designing and benchmarking the MULTICOM protein structure prediction system. BMC structural biology, 13(1), 2.
[3] Cheng, J., Li, J., Wang, Z., Eickholt, J., & Deng, X. (2012). The MULTICOM toolbox for protein structure prediction. BMC bioinformatics, 13(1), 65.
[4] Wang, Z., Eickholt, J., & Cheng, J. (2010). MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8. Bioinformatics, 26(7), 882-888.
