Introduction

The algorithm SMMPMBEC models binding interactions between MHC class I molecules and peptide ligands. Given a list of (peptide, affinity), it returns a PSSM capturing binding energy contributions of residues at various positions.

Reference

Kim Y, Sidney J, Pinilla C, Sette A, and Peters B. "Derivation of an amino acid similarity matrix for peptide:MHC binding and its application as a Bayesian prior" BMC Bioinformatics 2007. http://www.ncbi.nlm.nih.gov/pubmed/19948066

Requirements

1. Linux environment with a gcc compiler (e.g. Ubuntu).
2. Gnu Scientific Library(GSL) [http://www.gnu.org/software/gsl/]

Compiling

Simply issue the command 'make' within the folder. This should generate an executable 'smmpmbec'.

Training

See ./example/run_smmpmbec.sh for a training example. Trained model is a position specific scoring matrix (PSSM). For binding data set for peptides of 9 residues, the matrix has dimensions of 20 residues by 9 positions: 20x9.

Making predictions

For a given peptide, its predicted binding affinity in log10(IC50) is a sum of corresponding entries in the PSSM.