In-silico Analysis and Homology Modeling of Indonesian NS1 Antigen on Diagnostic Sensitivity Test of Dengue

DEWI ASTRIANY, - and HERMAN SUSANTO, - and GINA TAZKYA, - and ARI HARDIANTO, - and MUHAMMAD YUSUF, - and ADE RIZQI, - and TOTO SUBROTO, - (2018) In-silico Analysis and Homology Modeling of Indonesian NS1 Antigen on Diagnostic Sensitivity Test of Dengue. Journal of Pharmaceutical Sciences and Research (JPSR). pp. 29-40. ISSN 0975-1459

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Abstract

Aim: The non-structural glycoprotein-1 (NS1) antigen is one of the device options in laboratory diagnostic test, that can be used to detect either primary or secondary infections in the earliest stages [13]. Nowadays, the sensitivity of the kit currently diagnosed with DHF during surveillance in Indonesia is less than 70% [1]. The aim of this study was to analyze 48 structures of Indonesian NS1 antigenes of DENV1-4 isolates. Methods: In this study, bioinformatics approach was performed on the 48 structures of Indonesian NS1 antigenes of DENV1-4 to obtain the best model using BLAST and Pyre2. Homology modeling was carried out using Modeller 9.19 through templates which have a high homology level with the amino acid sequence NS1 antigen. Results: We obtained the best template of NS1 antigen Indonesia with PDB ID 4O6B_A. The best model of DENV-1, DENV-2, DENV-3, and DENV-4 were NS1/ID/DENV1-20, NS1/ID/DENV2-2, NS1/ID/DENV3-6 and NS1/ID/DENV4-1 with Ramachandran plot value 91.3%, 90.5%, 90.6% and 90.2%, respectively. Conclusion: The results showed that the differences of structures, amino acid residues, and epitopes from templates and each serotype are valuable tools for designing molecular antigen as diagnostic agent to enhance the sensitivity value of dengue diagnostic kits in Indonesia.

Item Type: Article
Uncontrolled Keywords: dengue virus, NS1 antigen, homology modeling, sensitivity, dengue diagnostic kit
Subjects: Q Science > Q Science (General)
Divisions: Lembaga Penelitian dan Pengabdian Masyarakat > Publikasi Penelitian
Depositing User: - Dewi Astriany -
Date Deposited: 20 Aug 2024 06:35
Last Modified: 20 Aug 2024 06:35
URI: http://repository.stfi.ac.id/id/eprint/987

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