| CPC G16B 15/30 (2019.02) [G16B 40/20 (2019.02); G16B 40/30 (2019.02)] | 19 Claims |
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1. A method of identifying one or more selected candidate peptides capable of binding a class I major histocompatibility complex (MHC) molecule of a single human leukocyte antigen (HLA) allele, the method comprising:
a. generating at least 100 models simulating occupancy for each of one or more candidate peptides on an HLA binding pocket, wherein the HLA binding pocket is in (i) a crystal structure of the MHC molecule of the single HLA allele or (ii) a crystal structure of a similar MHC molecule;
b. extracting structural features indicative of occupancy from the at least 100 models of step (a); and
c. providing the structural features extracted in step (b) to a machine learning algorithm, wherein the machine learning algorithm has been trained using a prior dataset comprising:
peptide sequence features of one or more binding peptides on the HLA binding pocket,
peptide sequence features of one or more non-binding peptides on the HLA binding pocket,
structural features of one or more binding peptides on the HLA binding pocket, and
structural features of one or more non-binding peptides on the HLA binding pocket,
whereby the machine learning algorithm outputs selected candidate peptides for binding the MHC molecule of the single HLA allele
thereby identifying one or more selected candidate peptides capable of binding the MHC molecule of the single HLA allele.
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