Molecular Dynamics Simulation on Protein Sequencing by Graphene Nanoslit Sensor
DescriptionNanopore sequencing technique is promising in breaking the limitation of the traditional sequencing method and reducing sequencing time in clinical applications, which would speed up disease diagnostics and enable precision medicine. Nanopore sensing based on2D materials has attracted extensive attention for its atomic-scale resolution since the thickness of sensor is a single-atom layer. However, this novel technique is confronted with difficulties in sensor selection, stable driving force and distinguishable sensingsignals. Among these difficulties, the selection of sensing signals is the most challenging due to the diversity of amino acids (AAs). So far no single detecting signal has been reported to reliably distinguish all the 20 AAs.Our goal is to identify all the 20 types of AAs by their characteristic signals. To achieve this, graphene nanoslit is adopted as sensor, by whose special geometry multidimensional sensing signals could be collected to enhance the distinguishability. We propose to simultaneously measure the constant-velocity pulling force and ionic current during residue permeation to provide improved distinguishability. Based on that, the translocation processes of 20 homogeneous polypeptide consisting one type of AA aresimulated to obtain characteristic signals and get the force-ionic current profile of the residues. The primary relationship of signals and AA types will be established. We will also study the translocation of heterogeneous peptide chains consisting several types ofAAs. The collected data will be used to train machine learning models, through whose classification function the ultimate relationship of signals and AAs will be established and all residues will be identified. Molecular Dynamics (MD) will be used to simulate the sequencing process during the translocation of different peptide through graphene nanoslit in potassium chloride solution. The peptide chain is facilitated through nanoslit by constant-velocity pulling under applied bias. Characteristic force and current signals could be collected during the translocation of every single residue, thus achieving sensing. The corresponding experiments will also be performed to verify our simulation predictions.Herein, force and current signals will be detected simultaneously using MD simulations, which provides a new way of sensing. Other sensing signals could also be combined to further address the difficulty of distinguishing all 20 types residues. Studying the correlation between signals and residues in different sequences will give insights on the sequencing mechanism. Most importantly, completely identifying different residues will pave the way for rapid diagnosis of diseases and personalized precision medicine.
|Effective start/end date||1/01/21 → …|