# BEDB: a comprehensive binding energy database for molecular docking and dynamics: insights into Human Metapneumovirus (HMPV) Inhibitors

## TL;DR

BEDB is a new database providing binding energy data for molecular docking and dynamics, with insights into potential inhibitors for Human Metapneumovirus.

## Contribution

BEDB is a novel, freely accessible database compiling binding energies and molecular properties for 1321 compounds, supporting molecular docking and dynamics research.

## Key findings

- Molecular docking identified MK-3207 and Etoposide as strong HMPV inhibitors with scores of −10.3 and −9.6.
- MD simulations confirmed stable binding interactions of top compounds with the viral protein.
- Additional compounds were analyzed for their binding mechanisms and therapeutic potential.

## Abstract

Biological databases play a crucial role in life sciences research by organizing vast amounts of data, enabling efficient access and analysis. Numerous databases have been published across various research areas, yet there remains a need for updated platforms in the field of molecular docking and molecular dynamics simulation research. To address this gap, we have developed an extensive and user-friendly platform focused on compiling the binding energies of compounds associated with a wide range of biological activities. The database offers free access to data on 1321 compounds, including abstracts, references, isomeric SMILES, and 22 molecular properties. Researchers can also securely store their docking and screening data. To demonstrate its capabilities, molecular docking was performed on the top 10 compounds with the best binding energies against human metapneumovirus (HMPV) using AutoDock Vina and the crystal structure (PDB ID: 8FPJ). MK-3207 and Etoposide exhibited docking scores of −10.3 and −9.6, respectively. The top two compounds were further selected for MD simulations, confirming stable binding interactions with the viral protein. Additional compounds, including Teniposide, UK432097, 85019940, Setileuton, Orvepitan, Cep-11981, Tadalafil, and VS-5584, were also analyzed, providing further insights into their binding mechanisms and potential therapeutic relevance. The database is developed using PHP, HTML, CSS, JavaScript, and Python and is freely accessible at https://www.pbed.habdsk.org/.