Immunogenic Breadth Prediction Tool (IBPT)


The Immunogenic Breadth Prediction Tool (IBPT) tool evaluates virus proteome diversity, as determined by prevalence of conserved Predicted CD8 T-cell epitopes, within IAVI Protocol C Transmitted Founder viruses and circulating HIV sequences from within the LANL database (10908 viruses as of 12th February 2020).

This tool can be used to generate metrics on specific virus sequences measured against either the available Protocol C sequences or the LANL database. The tool is derived from hypothesis pre-published on BioRxiv [1] and PrePrints [2]. Briefly, for each virus proteome a NetMHCpan 4.1 simulation is performed for each of 46 Human Leukocyte Antigen (HLA) files. The 46 NetMHCpan result files for a virus proteome are then filtered to extract the peptide, HLA and rank binding where the rank binding is <= 2 (lower value is stronger binding [3]). This data is then loaded into a PostgreSQL database where an analysis tool is implemented in SQL stored procedures to identifies key peptides which appear in at least X viruses strains. The conservation metric X is defaulted to 2.2% of the total number of viruses initially being analyzed. The analysis tool then selects the virus that contributes the most of these key peptides. The selected virus and associated key peptides are then removed from the process and the next virus that contributes the most of the remaining key peptides is selected. The ranking process continues until all the key peptides are accounted for.

Users can select viruses to be evaluated, create custom parameters for analysis, run analysis, view and download the results.

To gain access, please Sign Up and register. After registering please contact Jonathan Hare, email:, who can then provide authorisation.

E. McGowan et al., “Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated 2 HIV Response 3,” bioRxiv, p. 2020.08.15.250589, Aug. 2020.
J. Hare et al., “Selective HLA restriction permits the evaluation and interpretation of immunogenic breadth at comparable levels to autologous HLA,” Aug. 2020.
V. Jurtz, S. Paul, M. Andreatta, P. Marcatili, B. Peters, and M. Nielsen, “NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data,”J. Immunol., vol. 199, no. 9, pp. 3360–3368, Nov. 2017.

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