Nanopore Sensing of Single-Biomolecule: A New Procedure to Identify Protein Sequence Motifs from Molecular Dynamics
Solid-state nanopores have emerged as one of the most versatile tools for single-biomolecule detection and characterization. Nanopore sensing is based on measuring the variations in ionic current as charged biomolecules immersed in an electrolyte translocate through nanometer-sized channels, in response to an external voltage applied across the membrane. The passage of the biomolecule through the pore yields information about its structure and chemical properties, as demonstrated experimentally with sub-microsecond temporal resolution. However, extracting the sequence of the biomolecule without the information about its position remains challenging due to the fact there is a large variability of sensing events recorded. In this paper, we performed mi- crosecond time scale all-atom non-equilibrium Molecular Dynamics (MD) simulations of peptide translocation (motifs of alpha-synuclein, associated to Parkinson disease) through single-layer MoS2 nanopores. First, we present an analysis based on current threshold to extract and char- acterize meaningful sensing events from ionic current time series computed from MD. Second, a mechanism of translocation is established, for which side chains of each amino acid are ori- ented parallel to the electric field when they are translocating through the pore and perpendicular otherwise. Third, a new procedure based on permutation entropy (PE) algorithm is detailed to identify protein sequence motifs related to ionic current drop speed. PE is a technique used to quantify the complexity of a given time series and it allows to detect regular patterns. Here, PE patterns were associated to protein sequence motifs composed of 1, 2 or 3 amino acids. Finally, we demonstrate that this very promising procedure allows the detection of biological mutations and could be tested experimentally, despite the fact that reconstructing the sequence information remains unachievable at this time.