This paper reports a copper(II)-functionalized *Mycobacterium smegmatis* porin A (MspA) nanopore with the N91H substitution, enabling direct identification of all 20 proteinogenic amino acids using a machine-learning algorithm (99.1% accuracy, 30.9% signal recovery). The system also quantifies amino acids at the nanomolar range and analyzes post-translational modifications, an unnatural amino acid, and peptides using exopeptidases, including clinically relevant peptides from Alzheimer's disease and cancer. The method distinguishes peptides differing by a single amino acid, offering potential for peptide sequence inference.

Ming Zhang, Chao Tang, Zichun Wang, Shanchuan Chen, Dan Zhang, Kaiju Li, Ke Sun, Changjian Zhao, Yu Wang, Mengying Xu, Lunzhi Dai, Guangwen Lu, Hubing Shi, Haiyan Ren, Lu Chen, Jia Geng