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Antibacterial flavonoid derivatives: in silico ADMET, DFT, Molecular Docking, MD Simulation and in vitro verification.

PubMed
Authors: Ishfaq A, Tajammal A, Maira R, Qureshi AW, Aleeza B, Basra MAR

Year

2026

Paper ID

68613

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

260

Citations

0

Abstract

UNLABELLED: Computer-Aided drug design (CADD) integrating the pharmacokinetic and toxicity prediction is increasingly used as a best approach to prioritize the lead drug candidates. In current study, previously synthesized flavonoid derivatives (2a-4b) were evaluated as antibacterial agents using a combined and approaches. ADME, toxicity class, solubility, drug likeness and binding affinity towards biological targets were assessed using web tools pkCSM, ProTox, and SwissADME, and density functional theory (DFT) at B3LYP/6-31G was employed to obtain the optimized geometries, frontier molecular orbitals and quantum chemical descriptors. Molecular docking against the 1MOQ protein was performed to calculate the binding affinity, while antibacterial and antibiofilm activities were determined against (IRLO‑2), (IRLY‑2) and (IB‑4). The derivatives 3b and 4b possessing significant binding energy of -8.7 and -8.6 kcal/mol for the 1MOQ target protein and 2a, 3b, and 4a exhibited better ADME characteristics whereas 3a to 4b were found very less toxic by ProTox. Compound 3b was further validated by molecular dynamic simulation with trajectory analysis of structural stability metrics RMSD, RMSF and Rg. All compounds were found to exhibit high dipole moment consistent with their activeness to biological targets. Bioassay showed moderate to considerable inhibitory activity when compared to the reference drug. Compounds 2a and 2b have consistently shown antibacterial and anti-biofilm properties especially against and and also they have shown high Pa values towards DNA gyrase and β-lactamase. These flavonoid derivatives can emerge as promising antibacterial and antibiofilm leads that warrant further optimization in future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-026-00644-1.

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  • UNLABELLED: Computer-Aided drug design (CADD) integrating the pharmacokinetic and toxicity prediction is increasingly used as a best approach to prioritize the lead drug...

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