HLA3D

Choose prediction methods

Mutation Prediction

PSIPRED ( Predict sequence secondary structure)

Peptide Prediction

Neoantigen (Search for Tumor neoantigens)

Proto-peptide (Generate overlapping peptides containing mutations)

PeptideBuilder (Construct the peptide structures)

Immunogenicity Assessment

MHCflurry (MHC-Ⅰ Binding Affinity Prediction)

Docking Simulation

CoDockPP (Dock the peptide to HLA structure)

Submission details

Past protein sequence in FASTA format

Restrictions:

At most 10,000 sequences and 4,000,000 amino acids per submission; each sequence not more than 8,000 amino acids.

Confidentiality:

The sequences are kept confidential and will be deleted after processing.

CITATION

1.    Moller, M.D.R. Croning, R. Apweiler. Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics, 17(7):646-653, July 2001. (medline)

2.    A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, 305(3):567-580, January 2001.

3.    E. L.L. Sonnhammer, G. von Heijne, and A. Krogh. A hidden Markov model for predicting transmembrane helices in protein sequences. In J. Glasgow, T. Littlejohn, F. Major, R. Lathrop, D. Sankoff, and C. Sensen, editors, Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology, pages 175-182, Menlo Park, CA, 1998. AAAI Press.

Past protein sequence in FASTA format

Protein Sequence
Email
Job ID
;
Past protein sequence in PEPTIDE format Paste a single or several peptides inFASTA format:
Type of input
Peptide

Paste a single sequence of several sequences in PEPEIDE format info the field below.

Paste a single or several peptides in FASTA format info the field below(note,all peptides musts be of equal length):

or submit a file in PEPTIDE format direcity from your local disk

or submit a file in FASTA format direcity from your local disk(note,all peptides musts be of equal length):

Type allele names:

(ie HLA-A01:01) separated by commas (and no spaces). Max 20 alleles per submission

For list of allowed allele names click here List of MHC alleles names

-->

ADDITIONAL CONFIGURATION

Threshold for strong binder :% Rank

Threshold for weak binder:% Rank:

Include affinity predictions
No
Sort by score
No sort

Restrictions:

At most 5000 sequences per submission; each sequence not more than 20,000 amino acids and not less than 8 amino acids. Max 20 MHC alleles per submission.

Confidentiality:

The sequences are kept confidential and will be deleted after processing.

CITATION

Pan-specific prediction of peptide-MHC-I complex stability; a correlate of T cell immunogenicity 

Michael Rasmussen, Emilio Fenoy, Mikkel Harndahl, Anne Bregnballe Kristensen, Ida Kallehauge Nielsen, Morten Nielsen, Soren Buus. Accepted for publication Journal of Immunology, June 2016

;
Past protein sequence in PEPTIDE format PPaste a single or several peptides inFASTA format:
Type of input
Peptide

Paste a single or several peptides in PEPEIDE format info the field below(note,all peptides musts be of equal length):

Paste a single sequence of several sequences in FASTA format info the field below:

or submit a file in PEPTIDE format direcity from your local disk(note,all peptides musts be of equal length):

or submit a file in FASTA format direcity from your local disk

Type allele names:

For list of allowed allele names click here

-->

ADDITIONAL CONFIGURATION

Threshold for strong binder :% Rank

Threshold for weak binder:% Rank:

Filtering thteshold for %Rank (leave -99 to print all)

Include BA predictions

Submit Check Result Result Example Tutorial
Input HLA Protein(larger): [Explanation]
Input Peptide(small): [Explanation]
Enter Your Email:

Option:

HLA Constraint Site Residue: [Explanation]

Peptide Constraint Site Residue: [Explanation]

Constraint Type: Ambiguous Multiple

[Explanation]

Please enter your job ID:





Institute of Bioinformatics and Medical Engineering

For questions or comments regarding this website,please Contact Us

苏ICP备18032747号，Copyright 2018-2023 Shan Chang

Past protein sequence in FASTA format

Set your parameters

Original Residue:
Position:
New Residue:
Length:
>Create an extended conformation
Input Peptide Sequence
Angle ϕ = -120° Ψ = 140°
>Create a specific conformation
Start from the first residue
  • Res1 ϕ1 Ψ1 +
  • Res2 ϕ2 Ψ2
  • Res3 ϕ3 Ψ3
  • Res4 ϕ4 Ψ4
  • Res5 ϕ5 Ψ5
Add OXT to the final residue

>MHCflurry predict

HLA allele Peptide n_flank c_flank
Input：
+

…or upload a file in csv format directly from your local disk

>MHCflurry predict scan

Input： HLA allele：
Protein sequence in fasta format：

…or upload a file in fasta format directly from your local disk

Note：1. Instead of individual alleles (in a CSV or on the command line), you can also give a comma separated list of alleles giving a sample genotype. In this case, the tightest binding affinity across the alleles for the sample will be returned.
2. If you want to determine whether the peptide will be presented, you can optionally enter the upstream sequence before each peptide at n_flank and the downstream sequence after each peptide at c_flank.

HELP with output formats

#plot in postscript,script for making the plot in gunplot,data for plot

Note：For publication of results, please cite:
1.E. L.L. Sonnhammer, G. von Heijne, and A. Krogh. A hidden Markov model for predicting transmembrane helices in protein sequences. In J. Glasgow, T. Littlejohn, F. Major, R. Lathrop, D. Sankoff, and C. Sensen, editors, Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology, pages 175-182, Menlo Park, CA, 1998. AAAI Press.
2.A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, 305(3):567-580, January 2001.
Back

HELP with output formats

Download
Strand Helix Coil
Note：For publication of results, please cite:
Jones, D.T. (1999) Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol. 292:195-202.
Back

HELP with output formats

Note：For publication of results, please cite:
Pan-specific prediction of peptide-MHC-I complex stability; a correlate of T cell immunogenicity Michael Rasmussen, Emilio Fenoy, Mikkel Harndahl, Anne Bregnballe Kristensen, Ida Kallehauge Nielsen, Morten Nielsen, Soren Buus. Accepted for publication Journal of Immunology, June 2016
Back

HELP with output formats

Note：For publication of results, please cite:
1.NetMHCpan-4.0: Improved Peptide MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity DataVanessa Jurtz, Sinu Paul, Massimo Andreatta, Paolo Marcatili, Bjoern Peters and Morten Nielsen The Journal of Immunology (2017) ji1700893; DOI: 10.4049/jimmunol.1700893
2.NetMHCpan, a method for MHC class I binding prediction beyond humans Ilka Hoof, Bjoern Peters, John Sidney, Lasse Eggers Pedersen, Ole Lund, Soren Buus, and Morten Nielsen Immunogenetics 61.1 (2009): 1-13 PMID: 19002680
Back

Download

Models
Top 1 Top 2 Top 3 Top 4 Top 5 Top 6 Top 7 Top 8 Top 9 Top 10
Note：For publication of results, please cite:
Kong R, Wang F, Zhang J, Xu X J, Chang S. CoDockPP: a multistage approach for global and site-specific protein-protein docking. Journal of Chemical Information and Modeling, 2019, 59(8): 3556-3564.
Back
Back
Note：For publication of results, please cite:
Tien MZ, Sydykova DK, Meyer AG, Wilke CO. 2013. PeptideBuilder: A simple Python library to generate model peptides. PeerJ 1:e80 https://doi.org/10.7717/peerj.80
Back