Determination of inhibitory activities of the constituents of Curcuma longa (l) against Streptococcus pneumoniae by molecular docking simulation

Streptococcus pneumoniae is a major cause of community-acquired pneumonia (CAP), particularly affecting children, the elderly, and immunocompromised individuals. Its polysaccharide capsule helps it evade immune defenses, leading to lung infections characterized by fever, cough, and respiratory distress. The bacteria spread through respiratory droplets, posing a significant public health risk. Although pneumococcal vaccines have reduced the incidence of pneumonia, non-vaccine serotypes and antibiotic resistance continue to challenge prevention and treatment efforts. This study aimed to utilize computational methods and tools to predict, analyze, and understand the potential anti-pneumonial effects of phytochemical compounds derived from Curcuma longa on the bacterium responsible for causing pneumonia. To accomplish this, a target protein of Streptococcus pneumoniae was selected from the Protein Data Bank for further analysis. The receptor (4IVV) was prepared using Chimera-1.10.1, PyMOL-2.3.0, and Autodock Tools-1.5.6, with the same preparation process applied to the reference ligand (EDO). Phytochemicals were selected from Drug Bank and PubChem database, then screened using Data Warrior based on Lipinski's Rule of Five and toxicity criteria. The screened phytochemicals were subsequently extracted and prepared with Autodock Tools-1.5.6. The docking protocol was validated, followed by molecular docking using autodock-vina. The docking results were then analyzed and visualized using PyMOL-2.3.0. After completing the procedures, the reference ligand exhibited a mean binding energy of -2.5 Kcal/mol. In comparison, the 105 phytoconstituents, including the top 10 candidates, showed lower binding energies, ranging from -8.1 Kcal/mol to -6.5 Kcal/mol, indicating a stronger binding affinity than the reference ligand.