Application of antibody phage display to identify potential antigenic neural precursor cell proteins

A normalized differential sequence feature encoding method based on amino acid sequences

Protein interactions are the foundation of all metabolic activities of cells, such as apoptosis, the immune response, and metabolic pathways. In order to optimize the performance of protein interaction prediction, a coding method based on normalized difference sequence characteristics (NDSF) of amino acid sequences is proposed. By using the positional relationships between amino acids in the sequences and the correlation characteristics between sequence pairs, NDSF is jointly encoded. Using principal component analysis (PCA) and local linear embedding (LLE) dimensionality reduction methods, the coded 174-dimensional human protein sequence vector is extracted using sequence features. This study compares the classification performance of four ensemble learning methods (AdaBoost, Extra trees, LightGBM, XGBoost) applied to PCA and LLE features. Cross-validation and grid search methods are used to find the best combination of parameters. The results show that the accuracy of NDSF is generally higher than that of the sequence matrix-based coding method (MOS) coding method, and the loss and coding time can be greatly reduced. The bar chart of feature extraction shows that the classification accuracy is significantly higher when using the linear dimensionality reduction method, PCA, compared to the nonlinear dimensionality reduction method, LLE. After classification with XGBoost, the model accuracy reaches 99.2%, which provides the best performance among all models. This study suggests that NDSF combined with PCA and XGBoost may be an effective strategy for classifying different human protein interactions.

Application of phage display for T-cell receptor discovery

The immune system is tasked to keep our body unharmed and healthy. In the immune system, B- and T-lymphocytes are the two main components working together to stop and eliminate invading threats like virus particles, bacteria, fungi and parasite from attacking our healthy cells. The function of antibodies is relatively more direct in target recognition as compared to T-cell receptors (TCR) which recognizes antigenic peptides being presented on the major histocompatibility complex (MHC). Although phage display has been widely applied for antibody presentation, this is the opposite in the case of TCR. The cell surface TCR is a relatively large and complex molecule, making presentation on phage surfaces challenging. Even so, recombinant versions and modifications have been introduced to allow the growing development of TCR in phage display. In addition, the increasing application of TCR for immunotherapy has made it an important binding motif to be developed by phage display. This review will emphasize on the application of phage display for TCR discovery as well as the engineering aspect of TCR for improved characteristics.