Summary
Highlights
Kalumpang is a native plant known for its antibacterial and medicinal properties. Despite its strong antibacterial qualities, no study had previously tested its compounds against specific Xanthomonas using advanced techniques. This study aimed to identify which phytochemicals in Kalumpang effectively bind to and inhibit a key protein of Xanthomonas, specifically the decomposing active bacterial enzyme essential for denitrification, as a potential weakness.
The study was conducted through computer-based molecular docking simulations to predict inhibitory potential and analyze its ability to halt bacterial proliferation. The steps involved: 'Ligand Approval' to collect 44 phytochemicals from the PubChem database, 'Protein Selection' to obtain the 3D structure of the target protein from the PDB database, 'Binding Simulation' using AutoDock software to compute how compounds bind to active sites, 'Docking Optimization' to test multiple random positions for precise fitting, 'Conformational Analysis' to analyze interaction effects on shapes and supporting amino acids, and 'Post-Docking Analysis' for careful analysis, visualization, and statistical validation of results.
Table 1 demonstrated moderate inhibitory effects among 10 tested models, with an average binding energy of 6.48-7.17.3 kcal/mol, indicating partial slowing of bacterial replication. Table 2 identified compounds with the strongest antibacterial ability, exhibiting a negative binding energy of -8.68 kcal/mol and 0.43 micromolar, highly effective in preventing essential denitrification. In contrast, compounds in Table 3 showed very weak or low antibacterial activity with positive energy values, indicating ineffectiveness. Table 4 showed similar results to Table 1, demonstrating high moderate inhibitory potential. The figures illustrate precise inhibition, forming specific amino acid hydrogen bonds and maintaining binding stability.
The accuracy of predictions was ensured by validating the setup with known molecules, running multiple docking trials, and comparing predictions to verify reliability, ensuring the simulated interactions closely match actual experiments. This study benefits local farmers' production and medical researchers, aligning with sustainable development goals related to food and health.