Creating NS2A Binding Affinity in Dengue Virus Using Hybrid Method for Antiviral Prediction

DOI

10.2991/978-94-6463-618-5_7How to use a DOI?

Keywords

Binding Affinity; NS2A Protein; Dengue Virus; Hybrid Scoring Function; Antiviral Prediction

Abstract

Dengue fever in Indonesia requires immediate solutions because it poses a threat to life. The NS2A protein within the dengue virus is one of the major causes. Molecular docking is a rapid method for discovering antivirals for dengue fever using computational techniques. The results of this method are binding affinity values that measure the interaction between proteins (as virus) and ligands (as antivirals). The NS2A protein used is 2M0S. The hybrid scoring function, empirical and knowledge-based scoring functions calculated using Autodock Vina show that Krn-7000 has the highest binding affinity value of -10.1 kcal/mol. However, Lipinski’s Rule of Five analysis reveals that Nandrolone Decanoate, ranked 3th with a binding affinity of -9.2 kcal/mol, meets the criteria as an antiviral for the NS2A protein. This study produced a dataset of 1118 entries containing binding affinity values of potential antiviral candidates that could act as NS2A inhibitors. This dataset can be used for research in the field of machine learning as a novel scoring function for antiviral prediction.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Venia Restreva Danestiara
AU  - Marwondo
AU  - Taufik Abdul Aziz
AU  - Iqbal Ismayadi
PY  - 2024
DA  - 2024/12/29
TI  - Creating NS2A Binding Affinity in Dengue Virus Using Hybrid Method for Antiviral Prediction
BT  - Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024)
PB  - Atlantis Press
SP  - 56
EP  - 66
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-618-5_7
DO  - 10.2991/978-94-6463-618-5_7
ID  - Danestiara2024
ER  -