The PD value, a measure of similarity between amino acids, is one way to assess protein sequences. In this study, we used the PD value to evaluate the predictive power of a peptide search. We found that the PD values of osmotin peptides were positively correlated with each other. This suggests that a peptide search is useful for predicting the presence of antibodies.
To calculate the peptide similarity score, we used the BLOSUM35 matrix. Unlike a BLOSUM, an ensemble of peptides does not share the same identity. The average similarity score among a pair of proteins is then calculated using the total amino acid composition. This method has a high reproducibility rate and is widely used in biological research. This metric helps scientists determine whether two amino acid sequences have a high probability of being related.
In this study, we used the dot matrix as a measure of peptide similarity. For this purpose, the sequence of one peptide was placed on a horizontal plane, and the peptides of the other were on the vertical plane. The number of dots on the diagonal of these two peptides was computed, with a higher score for a broader set of compared proteins. The calculated peptide similarity scores are then used to rank peptides that are highly similar to each other.
To determine whether two peptides are similar, we calculated the average peptide similarity scores for each peptide. The score was derived by dividing the peptide lengths by the number of amino acids in the molecule. The gapless Total Similarity score is a measure of the difference between two peptides. This index measures the similarity between a peptide and a group of unrelated oligopeptides.
Although peptides are not identical, they share a common structural feature. For example, they are highly similar to each other in size and shape. This means that these two peptides are highly similar, but they have different functional properties. Moreover, they may be cross-reactive or inactive. A clone that has high immunogenic activity to certain antigens is more likely to be a positive candidate for disease.
To assess the homogeneity of HIV peptides, we use the NetCTL antigen presentation score to predict their immunogenicity. Similarly, a peptide with high self-similarity is unlikely to be immunogenic. It is, however, not yet clear whether the same peptides are cross-reactive. In other words, if a peptide is cross-reactive, it will have a higher antigenicity score than the corresponding peptide from the same virus.
A peptide that is similar to another peptide is said to be more biochemically similar than the others. The two peptides may have different functions. Some of these overlapping strands are also biochemically unrelated. This fact has led to a wide range of hypotheses. While it is not yet clear how TCRs recognize unrelated agonists and antagonists, it is still possible to identify the types of peptides that are similar.