{"title":"单层石墨烯基仿生传感器 SARS-CoV-2 感测的有限元模拟。","authors":"Manisha Makwana","doi":"10.1007/s00894-024-06123-8","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG’s performance as a sensor for biological entities. Altering the sheet’s length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.</p><h3>Methods</h3><p>Finite element method (FEM) analysis is employed to model the sensor’s performance and optimize its design parameters. The simulation results highlight the sensor’s potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10<sup>−18</sup> g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FEM simulation of SARS-CoV-2 sensing in single-layer graphene-based bionanosensors\",\"authors\":\"Manisha Makwana\",\"doi\":\"10.1007/s00894-024-06123-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Context</h3><p>Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG’s performance as a sensor for biological entities. Altering the sheet’s length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.</p><h3>Methods</h3><p>Finite element method (FEM) analysis is employed to model the sensor’s performance and optimize its design parameters. The simulation results highlight the sensor’s potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10<sup>−18</sup> g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.</p></div>\",\"PeriodicalId\":651,\"journal\":{\"name\":\"Journal of Molecular Modeling\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Modeling\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00894-024-06123-8\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Modeling","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s00894-024-06123-8","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
FEM simulation of SARS-CoV-2 sensing in single-layer graphene-based bionanosensors
Context
Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG’s performance as a sensor for biological entities. Altering the sheet’s length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.
Methods
Finite element method (FEM) analysis is employed to model the sensor’s performance and optimize its design parameters. The simulation results highlight the sensor’s potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10−18 g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.
期刊介绍：
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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