Beyond the Static Caliper: Dynamical Translocases and the Mathematical Imperative for Single-Molecule Proteomics

Area of Science:

• Biophysics
• Proteomics
• Genomics
• Machine Learning

Background:

• Single-molecule nanopore sequencing revolutionized genomics by analyzing nucleic acid translocation through static biological pores.
• Extending nanopore technology to single-molecule proteomics faces significant challenges due to the complex heterogeneity of proteins compared to nucleic acids.
• Static nanopores struggle to differentiate proteins based on volumetric measurements due to isosteric and isobaric variants.

Purpose of the Study:

• To address the bottleneck in single-molecule proteomics by proposing the use of dynamical translocases.
• To enable label-free, high-accuracy protein analysis by leveraging the unique translocation dynamics of proteins.
• To develop a method for discriminating amino acid classes based on their distinct biophysical properties.

Main Methods:

• Utilized naturally evolved, protein-handling nanomachines (dynamical translocases) with target-docking clamp architectures.
• Employed active-site conformational dynamics to generate high-dimensional kinetic fingerprints during translocation.
• Integrated dynamical translocases with Physics-Informed Machine Learning (PIML) to decode thermodynamic friction.

Main Results:

• Achieved low nanomolar sensitivity in protein translocation detection.
• Demonstrated >90% accurate classification of chemically distinct amino acid classes.
• Successfully performed label-free amino acid classification without artificial DNA handles.

Conclusions:

• Dynamical translocases offer a powerful solution for single-molecule proteomics, overcoming limitations of static nanopores.
• The combination of dynamical translocases and PIML enables sensitive and accurate protein analysis.
• This approach paves the way for advanced, label-free proteomic analysis and molecular discrimination.