HUT: HAPTIC2/HEPTAD User Toolkit

Links to web interfaces for components of HUT:

1. HIP: represents peptidic antigens using FASTA-style format (e.g., for use with HAPTIC2 and HEPTAD)
2. HAPTIC2: estimates affinity of paratopes for cognate disordered peptidic antigens, allowing for variable-length B-cell epitopes with temperature-dependent conformational flexibility.
3. HEPTAD: HAPTIC2-like epitope prediction tool for analyzing peptidic antigens each comprising exactly one cysteine residue pair with an intramolecular disulfide bond

Notes:

1. HUT is a more comprehensive and physically realistic replacement for HAPTIC.
2. HIP facilitates tagging of antigen residues for exclusion from downstream analyses by HAPTIC2 and HEPTAD.
3. HAPTIC2 (unlike HAPTIC) captures the temperature dependence of disordered peptidic antigen conformational flexibility while also regarding glycine and proline as residues that form hydrogen bonds with paratopes.
4. HEPTAD (unlike HAPTIC2) expects each input peptidic antigen sequence to contain exactly two cysteine residues, which are assumed to form a disulfide-bonded pair.

References:

1. Caoili SE (2006) A structural-energetic basis for B-cell epitope prediction. Protein & Peptide Letters 13(7):743-751 (PMID: 17018020)
2. Caoili SE (2010) Immunization with peptide-protein conjugates: impact on benchmarking B-cell epitope prediction for vaccine design. Protein & Peptide Letters 17(3):386-398 (PMID: 19594433)
3. Caoili SE (2012) On the meaning of affinity limits in B-cell epitope prediction for antipeptide antibody-mediated immunity. Advances in Bioinformatics 2012:346765, doi: 10.1155/2012/346765 (PMID: 23209458)
4. Caoili SE (2014) Benchmarking B-cell epitope prediction with quantitative dose-response data on antipeptide antibodies: towards novel pharmaceutical product development. BioMed Research International 2014:867905, doi: 10.1155/2014/867905 (PMID: 24949474)
5. Caoili SE (2014) Hybrid methods for B-cell epitope prediction. Methods in Molecular Biology 1184:245-283, doi: 10.1007/978-1-4939-1115-8_14 (PMID: 25048129)
6. Caoili SE (2015) An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies. Journal of Immunological Methods 427:19-29, doi: 10.1016/j.jim.2015.09.002 (PMID: 26410103)
7. Caoili SE (2021) Beyond B-cell epitopes: curating positive data on antipeptide paratope binding to support peptide-based vaccine design. Protein & Peptide Letters 28(8):953-962, doi: 10.2174/0929866528666210218215624 (PMID: 33602065)
8. Caoili SE (2022) Prediction of variable-length B-cell epitopes for antipeptide paratopes using the program HAPTIC. Protein & Peptide Letters 29(4):328-339, doi: 10.2174/0929866529666220203101808 (PMID: 35125075)
9. Caoili SE (2022) Comprehending B-cell epitope prediction to develop vaccines and immunodiagnostics. Frontiers in Immunology 13:908459, doi: 10.3389/fimmu.2022.908459 (PMID: 35874755)
10. Caoili SE (2024) B-cell epitope prediction for antipeptide paratopes with the HAPTIC2/HEPTAD User Toolkit (HUT). Methods in Molecular Biology 2821:9-32, doi: 10.1007/978-1-0716-3914-6_2 (PMID: 38997477)

Author Information: