Peptide Forum Hub Team Sharing the insights from the research paper named,
An Engineered Nanopore Identifies Saccharides, Amino Acids, Peptides and Ribonucleotides
Peptide Research Paper Published on September 14, 2026, in Nature Biotechnology
In this journal Nature Biotechnology describes an engineered nanopore called MspA-FPBA, which was developed by scientists at Nanjing University.
The main name of the sensor is MspA-FPBA, and it uses a chemical adaptor called maleimido-C2-FPBA to identify many types of small biomolecules with high accuracy.
What The Research on Means in Plain Language
Imagine a tiny hole in a wall. When you push different objects through the hole, each object blocks the hole in a slightly different way. A camera on the other side records the blockage pattern. From that pattern, you can tell what the object was.
That is what this nanopore does, but at the molecular scale. The researchers made the hole chemically smart so it can interact with many kinds of molecules. Then they used artificial intelligence to recognize the patterns.
The result is a sensor that can tell the difference between dozens of amino acids, sugars, nucleotides and peptides. It works even in a messy mixture like yeast extract. And it can sometimes identify molecules it has never seen before, as long as they belong to a chemical class it already knows.
This is not a finished product. It is a proof of concept. But it shows that a single nanopore platform could one day analyze proteins, RNAs and sugars together something no current technology can do.
Abstract
Researchers at Nanjing University have built an engineered protein nanopore that can identify a wide range of small biomolecules using a single sensor. The pore is called MspA-FPBA. It is a modified version of a natural protein pore from the bacterium Mycobacterium smegmatis.
The team inserted a chemical adaptor called maleimido-C2-FPBA at the narrowest point of the pore. This adaptor has two reactive chemical groups. One group binds reversibly to amines, which are found on amino acids and peptides. The other group binds reversibly to cis-diols, which are found on sugars and ribonucleotides.
When a molecule passes through the pore, it briefly changes the electrical current. Each type of molecule creates a distinct electrical signature. Machine learning then classifies these signatures.
The sensor successfully identified 21 proteinogenic amino acids, three post-translationally modified amino acids, four canonical nucleoside monophosphates, three epigenetically modified nucleoside monophosphates, four monosaccharides and five peptides. The overall accuracy reached 98.7%.
Meet The Team at Nanjing University
The work was led by Prof. Shuo Huang (黄硕) at the School of Chemistry and Chemical Engineering, Nanjing University. The first author is Lang Yao (姚琅), a doctoral student in Huang’s group. The paper was published on September 14, 2026 in Nature Biotechnology. It is the first nanopore research paper from China to appear in that journal.
What Is the Goal Behind this Research?
The goal is to create a single nanopore platform that can analyze proteins, RNAs and glycans together. Currently, scientists use separate technologies to study each of these molecule classes. The researchers want to unify that analysis on one sensor.
A second goal is to move toward a “chop and measure” strategy. In this approach, large biomolecules are cut into smaller pieces by enzymes. Each piece then passes through the nanopore for identification. If the pore can read amino acids, nucleotides and sugars, it could eventually help sequence proteins, RNAs and glycans in one system.
What They Tried to Find Out?
The team asked whether a single engineered pore could recognize chemically different classes of molecules. They used generative artificial intelligence to help design the FPBA adaptor. The team tested whether the pore could:
- Distinguish all 21 standard amino acids
- Detect post-translationally modified amino acids
- Tell apart canonical and epigenetically modified nucleotides
- Identify different monosaccharides
- Read short peptides
They also wanted to see how the system would handle real biological samples. So they turned to yeast cell extract, a messy, complex mix of many molecules. Even there, the machine learning model could pick out components without needing a pre-recorded signature for every exact molecule.
How It Impacts Peptide Science in 2026?
Peptide science has long needed better tools for single-molecule analysis. This work brings that closer in three ways.
First, the sensor can identify post-translationally modified amino acids. These modifications are critical for understanding how proteins function in cells. Many diseases involve errors in these modifications.
Second, the sensor can read peptides of different lengths and sequences. This is a step toward reading peptide sequences directly, rather than relying on mass spectrometry or other bulk methods.
Third, the team demonstrated analysis of G2 glycopeptides, peptides with sugar chains attached. Glycopeptides are notoriously difficult to study. A nanopore that can see both the peptide and the sugar part could open new doors in glycoproteomics.
How It Impacts the Industry?
The nanopore sensing industry has mostly focused on DNA and RNA sequencing. This work pushes the technology into proteomics, glycomics and metabolomics.
For pharmaceutical companies, the sensor could help with quality control of biologic drugs. Many therapeutic proteins are glycosylated, meaning they carry sugar chains. The sugar pattern affects drug safety and efficacy. A nanopore that can read both the protein and sugar parts could streamline that analysis.
For diagnostics, the sensor could enable point-of-care devices that detect amino acids, nucleotides and sugars in blood or urine. The Huang group has already shown nanopore analysis of urine metabolites for nutrition and sport monitoring.
For research institutions, the platform could reduce reliance on expensive instruments like mass spectrometers and nuclear magnetic resonance machines. A single nanopore sensor could handle many types of small molecules.
Who Are the Scientists Behind This Engineered Nanopore Research, September 2026?
Prof. Shuo Huang (黄硕) is the corresponding author and the leader of the Nanopore Group at Nanjing University. His research focuses on single-molecule nanopore biosensors, nanopore-based single-molecule microscopy and clinical applications of nanopore technology.
He has published nanopore work in Nature, Nature Nanotechnology, Science Advances, Matter and other high-impact journals. His group has developed nanopore methods for chiral amino acid discrimination, glycan sequencing by fragment assembly, and analysis of alcoholic beverages and metal ions.
Lang Yao (姚琅) is the first author and a doctoral student in Huang’s group. He has previously published on nanopore identification of nicotinamide adenine dinucleotide and its derivatives. He also contributed to a 2025 Nature Nanotechnology paper on single-molecule DNA analysis using covalent organic framework nanopores.
The other authors include Zixuan Wang (王子璇), Jialu Chen (陈佳璐), Wen Sun (孙雯), Kefan Wang (王可凡), Yunqi Xiao (肖云麒), Hanhan Zhang (张含含), Wenzheng Li (李文正), Yifan Wang (王逸凡), Lulu Zhao (赵露露), Xinyi Dai (代馨怡), Lu Qian (钱璐) and Panke Zhang (张盼科). Panke Zhang is a researcher at the State Key Laboratory of Analytical Chemistry for Life Sciences and has co-authored many nanopore papers with Huang.
Organizations
The primary organization is Nanjing University, specifically the School of Chemistry and Chemical Engineering. The university is one of China’s leading research institutions and has a strong program in analytical chemistry and single-molecule sensing.
The State Key Laboratory of Analytical Chemistry for Life Sciences provided major support. This is a national research platform that combines analytical chemistry with life sciences and clinical research.
The Chemistry and Biomedicine Innovation Center (ChemBIC) at Nanjing University also supported the work. ChemBIC was founded in 2019 to promote interdisciplinary research between chemistry and biomedical sciences.
Funding came from the National Key R&D Program of China, the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities and the China Postdoctoral Science Foundation.
Leave a Reply