Jul 2026· International Journal of Advanced Research in Science, Communication and Technology· pp. 130· 0 citations· 37 references
TL;DR
The article emphasizes that docking scores are hypothesis-generating outputs and must be interpreted with binding-pose quality, residue relevance, pharmacokinetic feasibility and safety prediction.
Abstract
Inflammation involves coordinated activation of vascular, immune, lipid mediator, cytokine, transcriptional and inflammasome pathways. Modern anti-inflammatory lead discovery increasingly uses computer-aided drug design to identify plausible protein-ligand interactions before costly laboratory studies. This review summarizes the rationale for target selection, molecular docking, ADMET prediction, toxicity screening and Quality by Design-based documentation in anti-inflammatory computational pharmacology. The article emphasizes that docking scores are hypothesis-generating outputs and must be interpreted with binding-pose quality, residue relevance, pharmacokinetic feasibility and safety prediction. Selected natural scaffolds such as curcumin, quercetin, luteolin, apigenin, resveratrol, berberine, boswellic acid, andrographolide, withaferin A, gallic acid and ellagic acid are discussed as examples of chemically diverse candidates for pathway-based screening
C25, the pyrazolin derivative represents a novel multi-target ligand with potential applications as an anti-inflammatory, analgesic, and anti-neoplastic agent and highlights its promise as a lead scaffold for future drug development.
Mst Neha Islam Ema, A. Ashraful, K. Fatema et al.· Bangladesh Pharmaceutical Jo...· 0 citations
This study highlights natural diterpenoids and coumarin glycosides as promising scaffolds for caspase-1 inhibition and demonstrates that integrating QSAR modeling with structure-based approaches provides an efficient strategy for discovering potential anti-inflammatory drug candidates.
Yusuf Şeflekçi, Alper Yılmaz, Abdulilah Ece· Molecules· 0 citations
Among the screened compounds, L114 emerged as the most promising EPCR inhibitor, suggesting that selected phytochemicals may serve as potential lead molecules for developing safer anti-inflammatory therapies targeting EPCR.
Aishwarya Jadhav, Elangbam Singh, Sagar S. Bhayye· International Journal of Dru...· 0 citations
Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by inflammatory, fibrotic, and immune-mediated mechanisms, with limited therapeutic options. In this study, an integrative computational strategy combining network pharmacology, molecular docking, molecular dynamics simulation, MM-GBSA binding free energy estimation, and ADMET prediction was applied to explore the potential multi-target effects of Gomisin N and Schisandrin B. A total of 48 overlapping targets between PSC-related genes and compound-predicted targets were identified, suggesting a convergent target network involving key hubs such as SRC, EGFR, and HSP90AA1. Functional enrichment analysis indicated the involvement of PI3K–Akt, VEGF, and ErbB signaling pathways, which are associated with inflammation, cell survival, and fibrosis. Molecular docking suggested moderate binding affinities of both compounds toward selected hub proteins, with interactions involving functionally relevant residues. Molecular dynamics simulations over 100 ns indicated stable trajectories, limited residue fluctuations, preserved compactness, and persistent intermolecular interactions, particularly for SRC–ligand complexes. MM-GBSA analysis further supported favorable binding free energies, with Schisandrin B showing stronger energetic stability toward SRC than Gomisin N. Drug-likeness and ADMET predictions suggested acceptable physicochemical and preliminary safety profiles, although potential CYP450-related drugdrug interactions require consideration. Overall, these findings provide computational support for the potential role of Gomisin N and Schisandrin B as multi-target candidates in PSC-related therapeutic research. However, experimental validation is required to confirm their biological activity, pharmacokinetic behavior, and safety.
Nedjwa Mansouri, O. Benserradj, O. Benslama et al.· Journal of Computational Bio...· 0 citations
Meta-iPPAR is developed, an integrative in silico framework combining stacked machine learning, molecular docking, and molecular dynamics simulations for the identification of PPAR-γ agonists that will be an effective computational tool for screening and prioritizing potential compounds targeting PPAR-γ in the early stage of drug development pipelines.
Phasit Charoenkwan, Ittipat Meewan, N. Schaduangrat et al.· Molecular diversity· 0 citations
The findings from molecular docking, 500-ns molecular dynamics simulations, MM-GBSA calculations, and alanine scanning analyses collectively corroborate a stable binding mode of BTB11556 within the MPO active site, support further investigation of BTB11556 as a candidate compound associated with MPO-targeted therapeutic strategies.
Maysoon Raed Alnajdawi, H. Wahab, Belal Alnajjar et al.· Journal of Computer-Aided Mo...· 0 citations
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