Sequencing proteins with transverse ionic transport in nanochannels

TL;DR

This paper introduces a novel de novo protein sequencing method using transverse ionic transport in nanochannels, which distinguishes amino acids by their ionic current signatures, potentially overcoming limitations of mass spectrometry.

Contribution

The study proposes a new sequencing technique based on measuring ionic currents in nanochannels, combining Monte Carlo simulations and molecular dynamics for amino acid differentiation.

Findings

Ionic current distributions are statistically distinct for all 20 amino acids.

The method shows potential for accurate de novo protein sequencing.

Simulations suggest feasibility of distinguishing amino acids in practice.

Abstract

{\it De novo} protein sequencing is essential for understanding cellular processes that govern the function of living organisms and all post-translational events and other sequence modifications that occur after a protein has been constructed from its corresponding DNA code. By obtaining the order of the amino acids that composes a given protein one can then determine both its secondary and tertiary structures through structure prediction, which is used to create models for protein aggregation diseases such as Alzheimer's Disease. Mass spectrometry is the current technique of choice for {\it de novo} sequencing. However, because some amino acids have the same mass the sequence cannot be completely determined in many cases. Here, we propose a new technique for {\it de novo} protein sequencing that involves translocating a polypeptide through a synthetic nanochannel and measuring the ionic current of each amino acid through an intersecting {\it perpendicular} nanochannel. To calculate the transverse ionic current blockaded by a given amino acid we use a Monte Carlo method along with Ramachandran plots to determine the available flow area, modified by the local density of ions obtained from molecular dynamics and the local flow velocity ratio derived from the Stokes equation. We find that the distribution of ionic currents for each of the 20 proteinogenic amino acids encoded by eukaryotic genes is statistically distinct, showing this technique's potential for {\it de novo} protein sequencing.