ProtNLM
Protein function prediction analyzes a protein’s amino acid sequence to identify its roles. ProtNLM, a T5-based model, predicts multiple functions for each sequence. These predictions help scientists explore potential functions of new proteins and evaluate computer-designed proteins, with sequence comparison to known proteins as a common first step.
Predict the structure of ‘DIHICGICKQQFNNLDAFVAHKQSGSQ’
| Name | Score |
|---|---|
| C2H2-type domain-containing protein | 0.54 |
| General transcription factor II-I repeat ... | 0.02 |
| Zinc finger protein | 0.019 |
Inputs
- Amino Acid Sequence: The protein’s primary structure, provided in a standard format (e.g., FASTA)
Outputs
- Name(s): Short text descriptions of the protein, ranked by confidence scores (0.0 to 1.0).
- Score(s): Confidence levels for each name (softmax), with higher scores indicating better predictions. Scores below 0.2 are deemed low confidence, and all scores sum to 1.0.
Predict the function of M4332
| Name | Score |
|---|---|
| Tyrosine-protein kinase | 0.592 |
| 2.7.10.2 | 0.249 |
| Non-specific protein-tyrosine kinase | 0.019 |
Load Q9UPY3 and predict its function
| Name | Score |
|---|---|
| Endoribonuclease Dicer | 0.466 |
| 3.1.26.3 | 0.409 |
| Endoribonuclease Dcr-1 | 0.033 |
Analyzing ProtNLM Results
Analyzing ProtNLM results involves evaluating predicted protein functions and sequences. Key aspects include reviewing designed amino acid sequences, assessing confidence scores, and comparing predicted functions with known data. This analysis informs potential roles and guides experimental validation.
Confidence Scores in Protein Predictions
Examine the confidence scores associated with each predicted function to assess their reliability. Higher scores indicate more trustworthy predictions, guiding research priorities.
Comparing Protein Sequences with Known Data
Compare the predicted sequences to known sequences in databases to identify similarities and evolutionary relationships. This comparison enhances understanding of the protein’s characteristics and potential functions.
Protein Structural Features and Functional Motifs
Look for key structural features or motifs within the predicted sequences that may inform their function. Identifying active sites and binding domains can provide insights into the protein’s biological activities.