DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES

Dengue Hemorrhagic Fever (DHF) is caused by the dengue virus (DENV), which is transmitted by Aedes mosquitoes. In recent years, DHF cases in Indonesia have continued to rise, emphasizing the need for more efficient and effective diagnostic methods. This research aims to develop a peptide-based bi...

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Main Author: Aliya, Farisa
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/85146
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:85146
spelling id-itb.:851462024-08-19T15:27:44ZDESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES Aliya, Farisa Indonesia Final Project DENV, NS1, Peptide, Graphene, Carbon nanotube, PBSE, GROMACS INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/85146 Dengue Hemorrhagic Fever (DHF) is caused by the dengue virus (DENV), which is transmitted by Aedes mosquitoes. In recent years, DHF cases in Indonesia have continued to rise, emphasizing the need for more efficient and effective diagnostic methods. This research aims to develop a peptide-based biosensor that can detect the NS1 biomarker of the dengue virus. Previous research by Putri (2023) designed a peptide named Mut 11, which has a high affinity for the NS1 protein. The follow-up research aims to immobilize the peptide on graphene and carbon nanotube (CNT) substrates. The stability of the interaction between the peptide and the substrate is enhanced by adding the linker 1-pyrenebutanoic acid succinimidyl ester (PBSE) to the peptide. The research process includes substrate selection, peptide bioconjugation with the linker, simulation of peptide-substrate interactions, and analysis of interaction stability. Molecular dynamics simulations were conducted using GROMACS software. The simulation stages included energy minimization, temperature and pressure equilibration, and production simulation for 10 nanoseconds. The parameters used were the GROMOS54a7 force field, SPC water system, and environmental conditions maintained at 300 K and 1 bar pressure. The simulation results showed that peptide Mut 11 was unstable when interacting with graphene and CNT. After the addition of the PBSE linker to the Mut11 peptide, the interaction between the peptide and CNT resulted in an average RMSD value of 2.703 ± 0.844 nm and an average radius of gyration of 1.211 ± 0.115 nm. The conjugated peptide and CNT system became the most stable system compared to the Mut 11 peptide and substrate systems. The conclusion of this research is that peptide bioconjugation with the PBSE linker effectively enhances the stability of peptide interactions with the CNT substrate. This indicates the potential for developing peptide-based biosensors for dengue virus detection. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Dengue Hemorrhagic Fever (DHF) is caused by the dengue virus (DENV), which is transmitted by Aedes mosquitoes. In recent years, DHF cases in Indonesia have continued to rise, emphasizing the need for more efficient and effective diagnostic methods. This research aims to develop a peptide-based biosensor that can detect the NS1 biomarker of the dengue virus. Previous research by Putri (2023) designed a peptide named Mut 11, which has a high affinity for the NS1 protein. The follow-up research aims to immobilize the peptide on graphene and carbon nanotube (CNT) substrates. The stability of the interaction between the peptide and the substrate is enhanced by adding the linker 1-pyrenebutanoic acid succinimidyl ester (PBSE) to the peptide. The research process includes substrate selection, peptide bioconjugation with the linker, simulation of peptide-substrate interactions, and analysis of interaction stability. Molecular dynamics simulations were conducted using GROMACS software. The simulation stages included energy minimization, temperature and pressure equilibration, and production simulation for 10 nanoseconds. The parameters used were the GROMOS54a7 force field, SPC water system, and environmental conditions maintained at 300 K and 1 bar pressure. The simulation results showed that peptide Mut 11 was unstable when interacting with graphene and CNT. After the addition of the PBSE linker to the Mut11 peptide, the interaction between the peptide and CNT resulted in an average RMSD value of 2.703 ± 0.844 nm and an average radius of gyration of 1.211 ± 0.115 nm. The conjugated peptide and CNT system became the most stable system compared to the Mut 11 peptide and substrate systems. The conclusion of this research is that peptide bioconjugation with the PBSE linker effectively enhances the stability of peptide interactions with the CNT substrate. This indicates the potential for developing peptide-based biosensors for dengue virus detection.
format Final Project
author Aliya, Farisa
spellingShingle Aliya, Farisa
DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
author_facet Aliya, Farisa
author_sort Aliya, Farisa
title DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
title_short DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
title_full DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
title_fullStr DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
title_full_unstemmed DESIGN AND EVALUATION OF LINKER IN PEPTIDE BASED BIOSENSOR FOR DETECTING DENGUE VIRUS (DENV) USING IN SILICO APPROACHES
title_sort design and evaluation of linker in peptide based biosensor for detecting dengue virus (denv) using in silico approaches
url https://digilib.itb.ac.id/gdl/view/85146
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