Iedb Prediction Tools

Configuration File: iedb_prediction_tools.json Tool Type: Local Tools Count: 4

This page contains all tools defined in the iedb_prediction_tools.json configuration file.

Available Tools

IEDB_predict_antigen_processing (Type: IEDBPredictionTool)

Predict MHC class I antigen processing using the IEDB Analysis Resource processing tool. Unlike r…

IEDB_predict_antigen_processing tool specification

Tool Information:

  • Name: IEDB_predict_antigen_processing

  • Type: IEDBPredictionTool

  • Description: Predict MHC class I antigen processing using the IEDB Analysis Resource processing tool. Unlike raw binding prediction, this chains proteasomal cleavage + TAP transport + MHC-I binding into a combined processing_score and total_score, predicting peptides that are naturally processed and presented to CD8+ T cells. Given a protein sequence and HLA allele, returns per-peptide proteasome_score, tap_score, mhc_score, processing_score, total_score and ic50_score (nM). Use for neoantigen and epitope prioritization beyond binding affinity. No authentication required.

Parameters:

  • sequence (string) (required) Protein sequence (single-letter amino acids), e.g. ‘SLYNTVATLYCVHQRIDV’. Aliases: sequence_text.

  • sequence_text (string) (optional) Alias for sequence.

  • allele (string) (optional) MHC class I allele. Human: ‘HLA-A*02:01’, ‘HLA-B*07:02’. Mouse: ‘H-2-Kd’. Default: HLA-A*02:01

  • method (string) (optional) MHC-I binding method used in the chain: ‘netmhcpan’ (default), ‘ann’, ‘smm’, ‘comblib_sidney2008’.

  • length (integer) (optional) Peptide length (8-14 for MHC-I, typically 9).

Example Usage:

query = {
    "name": "IEDB_predict_antigen_processing",
    "arguments": {
        "sequence": "example_value"
    }
}
result = tu.run(query)

IEDB_predict_bcell_epitopes (Type: IEDBPredictionTool)

Predict linear B-cell (antibody) epitopes along a protein sequence using the IEDB B-cell tool (de…

IEDB_predict_bcell_epitopes tool specification

Tool Information:

  • Name: IEDB_predict_bcell_epitopes

  • Type: IEDBPredictionTool

  • Description: Predict linear B-cell (antibody) epitopes along a protein sequence using the IEDB B-cell tool (default BepiPred). Scores every residue and returns the contiguous regions predicted to be antibody-accessible epitopes, plus the per-residue scores. Use for vaccine antigen design and antibody target selection. Example: a viral surface protein sequence returns its predicted surface-exposed epitope stretches.

Parameters:

  • sequence (string) (required) Protein amino-acid sequence (single-letter codes), e.g. an antigen of interest.

  • method ([‘string’, ‘null’]) (optional) Prediction method: ‘Bepipred’ (default, BepiPred-2.0), ‘Emini’ (surface accessibility), ‘Kolaskar-Tongaonkar’ (antigenicity), ‘Parker’ (hydrophilicity), ‘Chou-Fasman’ (beta-turn).

Example Usage:

query = {
    "name": "IEDB_predict_bcell_epitopes",
    "arguments": {
        "sequence": "example_value"
    }
}
result = tu.run(query)

IEDB_predict_mhci_binding (Type: IEDBPredictionTool)

Predict MHC class I peptide binding using NetMHCpan via the IEDB Analysis Resource API. Given a p…

IEDB_predict_mhci_binding tool specification

Tool Information:

  • Name: IEDB_predict_mhci_binding

  • Type: IEDBPredictionTool

  • Description: Predict MHC class I peptide binding using NetMHCpan via the IEDB Analysis Resource API. Given a protein sequence and HLA allele, predicts which peptides will bind and be presented on the cell surface. Returns peptides ranked by percentile rank (lower = stronger binding). Essential for vaccine design, neoantigen prediction, and epitope mapping. Supports human HLA-A/B/C and mouse H-2 alleles.

Parameters:

  • sequence (string) (required) Protein sequence (amino acid letters, e.g., ‘TYQRTRALVFQRTRALKMFAL’). Multiple peptides can be concatenated.

  • allele (string) (optional) MHC allele name. Human: ‘HLA-A*02:01’, ‘HLA-B*07:02’. Mouse: ‘H-2-Kd’, ‘H-2-Db’. Default: HLA-A*02:01

  • method (string) (optional) Prediction method. ‘netmhcpan_el’ (recommended, eluted ligand), ‘netmhcpan_ba’ (binding affinity), ‘ann’, ‘smm’

  • length (integer) (optional) Peptide length (8-14 for MHC-I, typically 9)

Example Usage:

query = {
    "name": "IEDB_predict_mhci_binding",
    "arguments": {
        "sequence": "example_value"
    }
}
result = tu.run(query)

IEDB_predict_mhcii_binding (Type: IEDBPredictionTool)

Predict MHC class II peptide binding using NetMHCIIpan via the IEDB Analysis Resource API. Predic…

IEDB_predict_mhcii_binding tool specification

Tool Information:

  • Name: IEDB_predict_mhcii_binding

  • Type: IEDBPredictionTool

  • Description: Predict MHC class II peptide binding using NetMHCIIpan via the IEDB Analysis Resource API. Predicts CD4+ T helper cell epitopes. Given a protein sequence and HLA-DR/DP/DQ allele, returns predicted binding peptides ranked by percentile rank. Essential for vaccine design (helper epitopes) and autoimmunity research.

Parameters:

  • sequence (string) (required) Protein sequence (amino acid letters)

  • allele (string) (optional) MHC-II allele. Examples: ‘HLA-DRB1*01:01’, ‘HLA-DRB1*15:01’. Default: HLA-DRB1*01:01

  • method (string) (optional) Prediction method: ‘netmhciipan_el’ (recommended), ‘netmhciipan_ba’, ‘nn_align’

Example Usage:

query = {
    "name": "IEDB_predict_mhcii_binding",
    "arguments": {
        "sequence": "example_value"
    }
}
result = tu.run(query)