Protein sequencing articles from across Nature Portfolio
Protein sequencing refers to methods for determining the amino acid sequence of proteins (or peptides) and analysis of the sequence, for example to infer protein conformation. Techniques include mass spectrometry and the Edman degradation reaction as well as prediction of the protein sequence from the encoding DNA or mRNA sequence.
Latest Research and Reviews
Toward single-molecule protein sequencing using nanopores
Maglia and colleagues discuss advances in nanopore technology en route to single-molecule protein sequencing
- Chunzhe Lu
- Andrea Bonini
- Giovanni Maglia
PEPPI-MS: gel-based sample pre-fractionation for deep top-down and middle-down proteomics
This protocol outlines a cost-effective and rapid protein sample pre-fractionation strategy based on highly efficient passive elution from gels, recovering intact proteins for top-down proteomics or partially digested proteins for middle-down proteomics.
- Ayako Takemori
- Philipp T. Kaulich
- Nobuaki Takemori
De novo protein sequencing of antibodies for identification of neutralizing antibodies in human plasma post SARS-CoV-2 vaccination
The antibody response to infection and vaccination is an essential component of the anti-infective immune response. Here the authors present a de novo protein sequencing method for antibody discovery from polyclonal IgG from human plasma and characterise the antibody response to the Moderna Spikevax COVID-19 vaccine.
- Thierry Le Bihan
- Teresa Nunez de Villavicencio Diaz
- Bin Ma
Multi-pass, single-molecule nanopore reading of long protein strands
A technique for threading long protein strands through a nanopore by electrophoresis and back using a protein unfoldase motor, ClpX, enables single protein molecules to be analyzed multiple times with single-amino-acid sensitivity.
- Keisuke Motone
- Daphne Kontogiorgos-Heintz
- Jeff Nivala
Accurate prediction of protein function using statistics-informed graph networks
Understanding protein function is vital for biomedicine. Here, authors develop a method using statistics-informed graph networks to predict functions from sequences. The method integrates evolutionary couplings and residue communities to improve the accuracy of function annotations for proteins.
- Yaan J. Jang
- Qi-Qi Qin
- Benoît Kornmann
PLMSearch: Protein language model powers accurate and fast sequence search for remote homology
Homologous protein search is one of the most commonly used methods for protein analysis. Here, authors propose PLMSearch, a search method that takes only sequences as input and can search millions of protein pairs in seconds while maintaining sensitivity comparable to SOTA structure search methods.
- Wei Liu
- Ziye Wang
- Shanfeng Zhu
News and Comment
Paleoproteomics sheds light on million-year-old fossils
Ancient proteins can provide phylogenetic information at a timescale that supersedes ancient DNA. Paleoproteomics could thus provide invaluable evolutionary insights, including into human evolution.
- Ryan Sinclair Paterson
- Palesa Petunia Madupe
- Enrico Cappellini
Nanopores for sequencing proteins
Developments in nanopore-based peptide detection and sequencing show promise of a breakthrough.
- Arunima Singh
Electroosmotic flow across nanopores for single-molecule protein sequencing
By using fixed charges to engineer a strong electroosmotic flow, we achieve the unidirectional transport of natural polypeptides across nanopores. Our approach enables native proteins to be transported enzymatically and non-enzymatically in the absence of denaturant and electrophoretic tags, with potential applications for protein sequencing.
Nanopore-based detection of phosphorylation
- Arunima Singh
Not if but when nanopore protein sequencing meets single-cell proteomics
The nanopore community is stepping toward a new frontier of single-molecule protein sequencing. Here, we offer our opinions on the unique potential for this emerging technology, with a focus on single-cell proteomics, and some challenges that must be overcome to realize it.
- Keisuke Motone
- Jeff Nivala