posted on 2024-01-24, 13:06authored byXiaojun Wei, Dumei Ma, Junlin Ou, Ge Song, Jiawei Guo, Joseph W. F. Robertson, Yi Wang, Qian Wang, Chang Liu
The
rapid progress in nanopore sensing has sparked interest in
protein sequencing. Despite recent notable advancements in amino acid
recognition using nanopores, chemical modifications usually employed
in this process still need further refinements. One of the challenges
is to enhance the chemical specificity to avoid downstream misidentification
of amino acids. By employing adamantane to label proteinogenic amino
acids, we developed an approach to fingerprint individual amino acids
using the wild-type α-hemolysin nanopore. The unique structure
of adamantane-labeled amino acids (ALAAs) improved the spatial resolution,
resulting in distinctive current signals. Various nanopore parameters
were explored using a machine-learning algorithm and achieved a validation
accuracy of 81.3% for distinguishing nine selected amino acids. Our
results not only advance the effort in single-molecule protein characterization
using nanopores but also offer a potential platform for studying intrinsic
and variant structures of individual molecules.