Network pharmacology-guided and molecular dynamics-validated insights into rubia phytocompounds as potential therapeutics for pneumonia
Year: 2025
Type: article
Abstract: Pneumonia caused by Streptococcus pneumoniae, Klebsiella pneumoniae, Mycoplasma pneumoniae, various viruses, and fungi, represents a significant nosocomial pathogen that affects the alveolar space within the lungs, primarily through the induction of inflammation. This inflammatory response can culminate in the accumulation of fluid and pus, resulting in a marked impairment of gas exchange and, in severe cases, leading to respiratory failure. Serotonin, beta-sitosterol, and rubiarbonol A were recognized as the main active components in Rubia cordifolia and Rubia tinctorum with encouraging therapeutic effect against pneumonia. By constructing a compound–target network and the analysis, five central hub genes were identified: SRC, HSP90AA1, STAT3, EGFR, and ESR1. GO and KEGG enrichment analyses pointed out that treatment mechanisms are mainly the modulation of immune-inflammatory processes, regulation of oxidative stress, antimicrobial activity, alleviation of symptoms, tissue healing, and inhibition of cell migration. These plant-derived compounds mostly target the pathways associated with bacterial pneumonia, thus indicating their possible use against pneumococcal infections. Molecular docking results showed strong binding between the dieases-associated targets and the leading compounds. Rubia phytochemicals with inflammation-related proteins, like SRC and STAT3, reveals their potential as additional treatments in the control of pneumonia. Molecular dynamics simulations also confirmed the structural stability and interaction consistency of the complexes. Network pharmacology and ADMET evaluation assured the drug-likeness and the safety profile of the targeted phytochemicals. collectively, the therapeutic of Rubia-derived phytochemicals as new drug candidates for pneumonia treatment.
Authors: Nachammai Kathiresan, Akshayaswarna Alagarsamy, Nageswar Paramasivam, P. Sangavi, Deepali Desai, Chitra Nagarajan, Langeswaran Kulanthaivel
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,300
OpenAlex ID: W7128918090
