How to interpret AlphaFold confidence scores?

Understanding AlphaFold Confidence Scores

• AlphaFold provides a per-residue confidence score called the Predicted Local Distance Difference Test (pLDDT) score, which ranges from 0 to 100. Higher scores suggest more confident predictions for that particular region of the protein structure.

 

• Generally, a pLDDT score above 90 is considered to reflect high confidence in the predicted structure, suggesting that the backbone atoms of this region are likely accurate to within a few angstroms.

 

• Scores between 70 and 90 indicate moderate confidence, suggesting that these regions may require further validation through experimental methods for complete certainty.

 

• Scores between 50 and 70 suggest low confidence, meaning the predicted structure in these regions might be unreliable and subject to larger deviations.

 

• Scores below 50 indicate very low confidence. These regions often need significant experimental verification as they might represent flexible or disordered regions in the protein.

Reviewing Model Predictions

• Initial review of the model predictions should focus on regions with high pLDDT scores to understand the stable parts of the structure. Stable regions can be more confidently used in further analysis or applications.

 

• Use interactive molecular visualization tools to examine and emphasize critical areas in the protein model, allowing for the identification of high-confidence regions in the context of protein function.

 

• Examine regions with lower scores closely to assess potential flexibility or disorder. This analysis may also suggest areas where experimental efforts should be prioritized.

Integrate Structural Data

• Compare AlphaFold predictions with known experimental structures, if available, to assess predictive accuracy, particularly in regions of low confidence. Consider aligning the predicted structure with similar protein structures from crystallography or NMR studies to evaluate congruency.

 

• Use the information provided by the confidence scores in conjunction with sequence alignments and evolutionary conservation data, aiding the interpretation of functional relevance and domain organization within the protein.

 

• Employ confidence scores as part of a broader structural biology strategy, incorporating them with other in silico predictions and wet lab validations to synthesize a comprehensive understanding of the protein of interest.