The idea is to model contact probability coefficient/energy with smth like Kidera factors. This way we can both derive factors that influence amino acid preferences in TCR:antigen contacts and compute missing values from Kidera factors of corresponding amino acids.
Not that this problem can perhaps be solved automatically when more data becomes available
There are some missing values for amino acid contact probability coefficients and energies
(Is in contact?) ~ Calpha distance + AA1:AA2 coef
GLM with a binomial link, see https://github.com/antigenomics/tcr-pmhc-study/blob/master/model/model_simple.Rmd#amino-acid-preferences-and-calpha-distance and https://github.com/antigenomics/tcr-pmhc-study/blob/master/model/eval/aa_pairwise_contact_coef.txt (note the latter is symmetric)The idea is to model contact probability coefficient/energy with smth like Kidera factors. This way we can both derive factors that influence amino acid preferences in TCR:antigen contacts and compute missing values from Kidera factors of corresponding amino acids.
Not that this problem can perhaps be solved automatically when more data becomes available