Evaluation of Flavonoids Derivatives from Amazon Plants by Computational Drug Development Approach for the Potential as Influenza Inhibitory Drug

30 Pages Posted: 16 Nov 2023

See all articles by Md. Mohaimenul Tareq

Md. Mohaimenul Tareq

Jashore University of Science and Technology

Sadia Jannat Tauhida

Jashore University of Science and Technology

Partha Biswas

Jashore University of Science and Technology

Md Ridoy Hossain

Jashore University of Science and Technology

Md. Jaber Hossain

Government of the United States of America - Centers for Disease Control and Prevention (CDC)

Daniel R. Perez

University of Georgia - Department of Population Health

Md. Nazmul Hasan Zilani

Jashore University of Science and Technology

Md. Nazmul Hasan

Jashore University of Science and Technology

Abstract

Avian Influenza (AI), or bird flu predominantly caused infection and disease to the birds.  The highly pathogenic avian influenza (HPAI) causes enormous socioeconomic losses in the poultry industry worldwide. The surface glycoproteins hemagglutinin (HA) and (NA) the influenza viruses. Highly pathogenic H5N1 subtype of avian influenza spreading throughout the world and caused serious threat to the poultry and human as well. Due to the continuous emergence of novel strains and ineffective antiviral drugs, suitable and effective therapeutics against this virus must be developed. Computational methods have accelerated drug development, and this study utilizes them to rationally design avian influenza antiviral molecules. The research designs avian influenza antiviral drugs using compound library molecular docking, MDS, QM, and thermal post-MDS MMGBSA. Flavonoids, natural polyphenolic phytochemicals with pharmacological and antiviral properties, are used to create ligand libraries. A dedicated database provides flavonoid compounds for protonation and tautomeric state expansion to create the library. Due to its pharmacological resistance, neuraminidase glycoprotein (2HTU) is targeted. The Protein Data Bank provides 2HTU's crystal structure and natural binding molecule. Schrodinger's Protein Preparation Wizard optimizes protein structure. Glide molecular docking creates a receptor grid for virtual ligand screening and discovery. Site-specific super-molecular docking predicts ligand binding affinity and orientation. Use glide scores to analyze interactions and find effective neuraminidase inhibitors. Post-docking analysis and Molecular Dynamics Simulations evaluate protein-ligand binding consistency and stability. The rational creation of avian influenza antiviral drugs is possible using computational methods. This study helps create avian influenza treatments by concentrating on flavonoids as ligands. The suggested strategy optimizes the drug design process to efficiently find lead compounds with improved binding affinities and antiviral activities. The results suggest flavonoids might be used to produce new avian influenza drugs to address the worldwide health crisis.

Keywords: Avian influenza, neuraminidase glycoprotein, quantum mechanics, molecular dynamics simulation, antiviral compounds, rational drug design.

Suggested Citation

Tareq, Md. Mohaimenul and Tauhida, Sadia Jannat and Biswas, Partha and Hossain, Md Ridoy and Hossain, Md. Jaber and Perez, Daniel R. and Zilani, Md. Nazmul Hasan and Hasan, Md. Nazmul, Evaluation of Flavonoids Derivatives from Amazon Plants by Computational Drug Development Approach for the Potential as Influenza Inhibitory Drug. Available at SSRN: https://ssrn.com/abstract=4628498 or http://dx.doi.org/10.2139/ssrn.4628498

Md. Mohaimenul Tareq

Jashore University of Science and Technology ( email )

Bangladesh

Sadia Jannat Tauhida

Jashore University of Science and Technology ( email )

Bangladesh

Partha Biswas

Jashore University of Science and Technology ( email )

Bangladesh

Md Ridoy Hossain

Jashore University of Science and Technology ( email )

Bangladesh

Md. Jaber Hossain

Government of the United States of America - Centers for Disease Control and Prevention (CDC) ( email )

United States

Daniel R. Perez

University of Georgia - Department of Population Health ( email )

Md. Nazmul Hasan Zilani

Jashore University of Science and Technology ( email )

Bangladesh

Md. Nazmul Hasan (Contact Author)

Jashore University of Science and Technology ( email )

Bangladesh

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