In Degoot123/PeptideMHC2Prediction: Prediction of Peptide:MHC-II Molecules Interactions

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PeptideMHC2Prediction

An R package implementing biophysical methods for prediction of peptide and MHC-II molecules interactions, developed by Degoot and colleagues \url (https://www.frontiersin.org/articles/10.3389/fimmu.2018.01410/full). It predicts the probability of binding affinity between peptide of any length that greater than or equal 9 and 35 HLA-II molecules belonging to the three MHC-II loci of human genes: DRB, DP, and DQ. Use the supportedMolecules( ) function to see the molecules that covered by the current version of the package.

Getting started

First load the package

##library(PeptideMHC2Prediction)

Prediction for individual peptides

To predict the probability of binding affinity between peptide, for example say,

pep <- "ADAGYAPATPAAAGA"

and an MHC-II molecule, for examples say DRB1_0401, based on trans-allelic method, you can use the following:

##predictBinding(pep, "DRB1_0401", "DRB", 2)

Or using the intra-allelic method as follows:

##predictBinding(pep, "DRB1_0401", "DRB", 1)

Please call this

# supportedMolecules()

function to see the 35 MHC-II molecules covered by the current version of the package.

The output of the function predictBinding is vector containg four items as follows:

#   "ADAGYAPATPAAAGA", "DRB1_0401",x= "0.xxx", y= {0 or 1}

The first and second items are the peptide and the MHC-II molecule, respectively. The third item is a value for binding probability of the interaction between the peptide and MHC-II molecule as predicted by the model. The last item is a binarized value of the probability, it returns zero (0) if the probability less than 0.5 and 1 otherwise.

Prediction for set peptides

Instead of making predictions for individual peptides, the package also allows to make predictions for set of peptides and MHC-II molecules, together organized in form of a dataframe of the three columns. The columns of the dataframe must be in the following order: th peptide, the name of MHC-II moleclue, and the locus. For example, let us assume that we have a dataframe called dataset, which has the following structure.

Peptide | MHC | Locus | |:---------------:|:--------:|:---------:| |AAAGAEAGKATTEEQ| DRB1_0301| DRB | |AFALVLLFCALASSC| DRB3_0101| DRB | |AAAGAEAGKATTEEQ| DRB1_1501| DRB | |SGLVWGQKYFKGNFQ| DPB10401| DP | |SSNPTILSEGNSFTA| DQB10201| DQ |

Then you call the function predictBindingSet to get prediction of the above dataset as follows:

##predictBindingSet(dataset, opt = 1)

The parameter opt specifies the prediction method, 1 for intra-allelic method and 2 for trans-allelic method. The output of function predictBindingSet is a dataframe of four columns, which has the below structure:

Peptide | MHC | Probability |Binary Value| |:---------------:|:--------:|:---------:|:---------:| |AAAGAEAGKATTEEQ| DRB1_0301| 0.176 | 0 | |AFALVLLFCALASSC| DRB3_0101| 0.549 | 1 | |AAAGAEAGKATTEEQ| DRB1_1501| 0.679 | 1 | |SGLVWGQKYFKGNFQ| DPB10401| 0.300 | 0 | |SSNPTILSEGNSFTA| DQB10201| 0.026 |0|

References

Abdoelnaser M. Degoot, Chirove Faraimunashe, and Ndifon Wilfred (2018) Trans-Allelic Model for Prediction of Peptide:MHC-II Interactions, Frontiers in Immunology. URL:https://www.frontiersin.org/article/10.3389/fimmu.2018.01410.

Degoot123/PeptideMHC2Prediction documentation built on May 21, 2019, 10:15 a.m.