Biomimetic solid-state FET nanopores for enhanced molecular sensing: learning from transmembrane peptides

Introduction
Biological ion channels, particularly transmembrane pores involved in peptide transport, demonstrate exquisite molecular selectivity and dynamic gating. These properties, essential to processes like antigen presentation or viral genome delivery, provide a blueprint for advanced biosensors. Yet, biological nanopores, while sensitive, lack mechanical stability and integration capability. Solid-state nanopores offer robustness and scalability but suffer from low signal-to-noise ratios (SNR) and ultrafast analyte translocation. Inspired by biological translocation mechanisms and channel-gated sensing, we are focusing on a biomimetic solution: a nanopore integrated with a field-effect transistor (NP-FET) based on SiN membranes.

Methods
Our approach mimics the localized field interactions observed in natural peptide translocation by coupling molecular passage through a 2 nm Si₃N₄ pore with FET modulation. Using molecular dynamics (MD) simulations (NAMD with CHARMM27 force fields), we analyzed the electrophoretic transport of synthetic peptides (e.g., PolyAsp, Gly(14)-Phe-Gly(15)) under variable voltages, assessing their velocity, field response, and ability to modulate transistor current.

Results
Simulations revealed strong charge- and volume-dependent transport phenomena. Highly charged peptides like PolyAsp translocated within 0.3 ns, underscoring the need for signal amplification—achievable via NP-FET coupling. In contrast, bulky hydrophobic peptides (e.g., PolyPhe) showed no translocation even under high voltage, aligning with biological channel exclusion behavior. Voltage-current profiles varied significantly across peptides, revealing potential for sequence-specific signal fingerprints.

Conclusion
Our findings validate a biologically inspired FET nanopore architecture that enhances SNR and enables molecular fingerprinting of peptides. This biomimetic approach leverages nature's design principles—charge gating, selective translocation, and conformational filtering—toward solid-state platforms for sequencing and biosensing. This paves the way for future low-cost, label-free, and integratable diagnostics informed by biological transport efficiency.