Electronic Structure, Bonding Characteristics, and Antibacterial Activity of Aconitic Acid: Insights from DFT and Molecular Dynamics Simulations
Abstract Aconitic acid serves as an intermediary compound in the aconitase enzyme‐catalyzed stage of the citric acid cycle, which generates energy in the body. Aconitic acid was analyzed structurally, molecularly, and vibrationally, employing experimental and theoretical approaches. FMO analysis and Quantum chemical characteristics were used to examine the molecule's reactivity and stability, revealing a predicted energy gap of 5.711 eV indicating high kinetic stability, with a computed dipole moment of 5.121 D. TDM and electron‐hole analyses are employed to assess the orbital interactions within the molecule. Topology investigations were done to determine the molecule's biological reactivity. Local interaction descriptions can show how physiologically favoured molecular frameworks combine to create novel medicinal drugs. Biological properties were determined using drug‐likeness. ADMET profiling indicated good pharmacokinetic potential, with all Lipinski's rule of five criteria satisfied (HBD = 3, HBA = 6, consensus log P = 2.87). Molecular docking with bacterial proteins (1BDD, 1A6F, 6P8U, 1GNK) showed strong binding affinities, particularly with Bacillus subtilis (−8.58 kcal mol −1 ), supported molecular dynamics simulations, confirming stability of protein–ligand complexes. In vitro assays demonstrated notable antibacterial activity, with aconitic acid showing stronger inhibitory effects than the standard drug amikacin. These results indicate that aconitic acid could serve as a promising antibacterial candidate.
Authors
- N. R. Sheela
- Riya Sebastian
- J. Subha
- A. Prabakaran
Institutions
- Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN)
- Sri Venkateswara University (IN)
- Sri Venkateswara Veterinary University (IN)
- SRM Dental College (IN)
Publication Details
- Journal
- ChemistrySelect
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1002/slct.202503669
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00