Analyzing HLA Sequences to Predict Organ Rejection and Find Targets for Precise Immunosuppression

~ Samhitha Bodangi

Grant Proposal

The objective is to improve organ rejection prediction and medicine by creating a model that can predict rejection by finding strong donor-derived peptides that contain solvent-accessible mismatches. By focusing on peptide presentation, the most significant peptides can be used as targets as they have the highest chance of immunogenicity.

The work proposed will increase the accuracy of predicting rejection and provide precise immunosuppressive targets to decrease the side effects of broad immunosuppressors. Further research is needed in this field as current medications can severely deplete the health of the recipient. Focusing on precise immunosuppression can lead to new therapies that keep both the organ and patient safe.

Pictures of Server Code

Figure 1: NetSurfP Output

Figure 2: NetMHCIIpan Peptide Clusters


Pictures of Web Application

Figure 3: PIPSA Home Page

Figure 4: Sample Output from PIPSA

Project Logbook

Project Notes


Project Proposal

Project Thesis