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Article . 2021
License: CC BY
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Article . 2021
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INSILICO DOCKING AND MOLECULAR DYNAMIC SIMULATION STUDIES OF NUCLEOCAPSID PROTEIN FROM HUMAN T-LYMPHOTROPHIC VIRUS

Authors: Ummehani A. Kallawala, Sharav A. Desai*;

INSILICO DOCKING AND MOLECULAR DYNAMIC SIMULATION STUDIES OF NUCLEOCAPSID PROTEIN FROM HUMAN T-LYMPHOTROPHIC VIRUS

Abstract

This work was conducted to find out a natural compound capable of inhibiting the Nucleocapsid protein present in the HTLV-1 virus. HTLV-1 virus belongs to delta retroviruses that do not contain protooncogene in their genome. Computer-aided drug design approach was used to obtain inhibitory compounds. A total of 109 natural compounds were identified by conducting a literature survey. PubChem database was utilized to retrieve the compound structure in 2D format. HTLV-1 NC (Nucleocapsid) protein was taken from the protein data bank. Molecular docking method was used to find out the compound capable of binding with the target protein. Compounds with good binding affinity were selected and further ADMET analysis was done. The final list of the compound with satisfactory ADMET profile and binding score were scrutinized using protein and ligand interaction results. The compound Miraxanthine_V was found to have a good binding affinity with said ADMET properties and was further studied for its structural stability with the target protein. Molecular dynamic simulation studies for 10 ns were done to check the stability of the protein and ligand complex during a simulation. Parameters like RMSD, RMSF, and radius of gyration were observed to understand the fluctuations and stability. the values obtained with simulations were found to come under the acceptance limit. We are proposing Miraxanthine_V as a potential inhibitor for HTLV- infection

Keywords

HTLV-1, Molecular Docking, Simulation, Nucleocapsid, RMSD, RMSF.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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