Mutation P84243 at position 4: T → Q (T4Q)
Overview
- Predicted structure (AF):
- AF-P84243-F1-model_v4
- Uniprot entry:
- P84243
- Gene:
- P84243
- Protein length:
- 136 residues
- Mutation:
- T → Q
- Mutation position:
- 4
- D2Deep Prediction:
- 0.530
- Overall confidence:
- 0.203
- Pred. interpretation:
- Pathogenic based on D2Deep prediction
-
BenignPathogenic
- Scores that are greater than or equal to 0.5 are considered "Pathogenic", while scores that are less than 0.5 are considered "Benign".
- Sequence difference
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
|---|---|---|---|---|---|---|---|---|---|
| Original | M | A | R | T | K | Q | T | A | R |
| Target | M | A | R | Q | K | Q | T | A | R |
Predicted original structure
Differences at amino acid level
| Feature | Original «T» | Target «Q» |
|---|---|---|
| Name | Threonine (Thr) | Glutamine (Gln) |
| Molecular Formula | C4H9NO3 | C5H10N2O3 |
| Residue Formula | C4H7NO2 | C5H8N2O |
| Molecular Weight | 119.120 | 146.150 (+27.030) |
| Residue Weight | 101.110 | 128.130 (+27.020) |
| Hydrophobicity index at pH 2 | Neutral | Neutral |
| Hydrophobicity index at pH 7 | Neutral | Neutral |
| Charge | Neutral | Neutral |
| Solutibility | Undetermined | 2.600 |
| Structure Image |  |
 |
| Description | Threonine (Thr) is within reactions in bacteria and metabolic rate in animals. However, the exact effect has not yet been determined. | Glutamine (Gln) is the most abundant amino acid in human bodies, and it performs several functions. It is responsible for regulating toxic ammonia and urea in human bodies. The reason glutamine can remove toxic ammonia is because its carboxyl side chain can act as a donor and acceptor for ammonia (this then allows for the safe transport of ammonia in human bodies). |
Predicted structures comparison
About these 3D Structures: The 3D structure representations of both original and target sequences (trimmed to 400 residues, from 1 to 136) will be modeled using the ESM Metagenomic Atlas tools. ESM Metagenomic Atlas is a web-based tool for protein structure prediction that uses deep learning methods to predict protein folding and structure from protein sequences.
Below the plots, you will find additional details on how to interpret the biophysical results.
Differences at biophysical features
About these plots:
These plots have been generated by using Bio2Byte predictors to plot both the
original and
target sequences.
The biophysical features are calculated when you click on the button below.
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