A binary/digital approach to amino acid identification and its application to peptide sequencing and protein identification.

Abstract

A binary/digital method is proposed in theory for the identification of single amino acids (AAs) in the bulk or with a few molecules from a single binary measurement. Combined with Edman degradation (or other cleaving method), it can be used to sequence a peptide or identify the parent protein from a partial sequence. The approach is centered on the superspecificity property of transfer RNAs (tRNAs). Markedly different from conventional and recent single molecule (SM) sequencing methods based on analog measurements, it changes the analytical question 'Which AA is it?' to the much simpler one 'Is there an AA in the detection space?'. Each of 20 terminal residues cleaved from 20 copies of a peptide enters a different cavity with a unique tRNA; tRNA charging (or binding with AA) occurs only in the cavity with the cognate AA. The bound AA or the AA separated from the tRNA is detected with a single binary measurement; its identity is known from the position of the single high bit in the resulting 20-bit output. Alternatively, a 20-stage pipeline can be used with sparse samples. Detection of the bound AA can be done optically by tagging the AAs with a fluorescent dye, or of the freed AA electrically with a nanopore. Necessary conditions for accurate AA identification are satisfied in principle; related computations and simulation results are presented. A modified version that can be used for de novo sequencing in parallel of large numbers of peptides immobilized on a glass slide with the tRNAs carrying a fluorescent tag is also proposed. Both methods can be used for protein identification from partial sequences containing 2 or 3 AA types by using only the corresponding tRNAs. Experiments may be performed to validate them, followed by translation into practice with existing technology; potential implementation issues are discussed. Binary/digital amino acid identification for peptide sequencing.