DETERMINATION OF CONFORMATIONAL ENSEMBLES IN ANTIGENIC PEPTIDES: REFINEMENT OF COMPUTATIONAL APPROACHES FROM NMR EXPERIMENTAL DATA

During an immune response, the adaptive cells, responsible for the specificity of the immune system, recognize protein parts or fragments called epitopes. Epitopes have primary and tertiary structure compositions that are highly specific for these peptide types. The sequences of known epitopes are used extensively in databases for vaccine development and prediction of new sequences. Less explored are tertiary structures of the epitopes, which comprehend a unique and difficult field of study. Following the concept developed by Dyson and Wright in 1960, here we show that antigenic peptides in aqueous solutions possess unique conformational ensembles. Because data from NMR NOE provide us with little information about nuclei distances, once epitopes tend to be in a nascent helical state (dαβi,i+3) or in a reversed turn (dαNi,i+2), we optimized a structure calculation protocol to identify the predominant conformational states using NMR data as a starting step. The protocol uses the ARIA2.3 software and the UCSF Chimera clusterization tools. SARS-CoV-2 epitopes from the N and S proteins were used for our proof of concept. Our results provide a refined model for calculating epitope conformations and demonstrate the importance of three-dimensional analysis of epitopes in antigenicity determination. We anticipate that our results may be critical for vaccine design and expect to be able to distinguish epitope structures for recognition by B and T cells in future studies.