Research Article
Machine Learning-Assisted in Silico Identification of Phytoconstituents as Potential NS5 RdRp Inhibitors for Dengue Therapeutics
Issue:
Volume 12, Issue 2, June 2026
Pages:
29-45
Received:
27 June 2026
Accepted:
20 July 2026
Published:
10 August 2026
Abstract: The escalating global burden of dengue virus (DENV) infection and the lack of specific antiviral therapies necessitate the development of effective therapeutics targeting the highly conserved non-structural protein 5 RNA-dependent RNA polymerase (NS5 RdRp). This study employed an integrated computer-aided drug discovery (CADD) and machine learning (ML) framework to screen a library of 14 phytoconstituents against DENV-2 NS5 RdRp. Following molecular docking, the top-ranked compounds were evaluated for pharmacokinetic safety through cross-docking with CYP3A4, OATP1B1, and OATP1B3, complemented by ADMET prediction using SwissADME and ProTox-II. In parallel, ML-based quantitative structure-activity relationship (QSAR) models using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) were developed using hybrid descriptors comprising Morgan fingerprints, physicochemical properties, experimental IC50 values, and docking scores derived from validated DENV RdRp inhibitors. Docking analysis identified Glycyrrhizin, Curcumin, Boswellic acid, Mangiferin, Azadirachtin, and Forskolin as promising inhibitors, exhibiting binding affinities comparable to or greater than those of remdesivir. Although several lead compounds demonstrated potential interactions with CYP3A4, their weak binding to OATP1B1 and OATP1B3 suggested a reduced risk of transporter-mediated toxicity and favorable hepatic safety, supported by ADMET predictions indicating favorable drug-like properties. Among the developed ML- based QSAR models, XGBoost outperformed RF in predicting nonlinear structure-activity relationships. Overall, the integrated molecular docking, pharmacokinetic profiling, and ML-based QSAR analyses identified Glycyrrhizin, Curcumin, Boswellic acid, and Azadirachtin as the most promising antiviral lead scaffolds and demonstrate the value of AI-driven drug discovery for accelerating antiviral lead identification. Further in vitro and in vivo studies are warranted to validate their therapeutic efficacy and safety.
Abstract: The escalating global burden of dengue virus (DENV) infection and the lack of specific antiviral therapies necessitate the development of effective therapeutics targeting the highly conserved non-structural protein 5 RNA-dependent RNA polymerase (NS5 RdRp). This study employed an integrated computer-aided drug discovery (CADD) and machine learning ...
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Research Article
Evaluation of Anti-gout Activity of Eugenol and Quercetin from Herbal Sources Using Computational and Analytical Approaches
Issue:
Volume 12, Issue 2, June 2026
Pages:
46-62
Received:
23 July 2026
Accepted:
5 August 2026
Published:
11 September 2026
Abstract: Gout is a metabolic disorder characterized by hyperuricemia, which results in the deposition of monosodium urate crystals in joints, leading to recurrent episodes of inflammation, pain, and progressive joint damage. Xanthine oxidase (XO), the key enzyme involved in the final steps of uric acid biosynthesis, is an important therapeutic target for gout management. Although conventional XO inhibitors such as allopurinol are effective, their long-term use may be associated with adverse effects, highlighting the need for safer, plant-derived alternatives. The present study aimed to investigate the antigout potential of the phytochemicals eugenol and quercetin through phytochemical characterization, molecular docking, and in silico pharmacokinetic analysis.Methanolic extracts of clove (Syzygiumaromaticum), bitter melon (Momordicacharantia), and betel leaf (Piper betle) were subjected to preliminary phytochemical screening to identify the presence of bioactive secondary metabolites. Thin Layer Chromatography (TLC) was performed to separate and identify the major phytochemical constituents, while Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was employed to characterize functional groups and confirm the presence of eugenol and quercetin. Molecular docking studies were carried out using the SwissDock platform to evaluate the binding affinity and interaction patterns of these compounds with the xanthine oxidase enzyme. Furthermore, ADMETlab 2.0 was utilized to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles of the selected phytochemicals, thereby assessing their drug-likeness and safety.The molecular docking analysis demonstrated favorable binding interactions of both eugenol and quercetin with the active site of xanthine oxidase, indicating their potential inhibitory activity. ADMET predictions suggested acceptable pharmacokinetic properties and low toxicity, supporting their suitability as potential therapeutic candidates. Overall, the findings suggest that eugenol and quercetin possess promising antigout activity and may serve as natural xanthine oxidase inhibitors. This integrated experimental and computational approach provides a scientific basis for further in vitro and in vivo investigations to validate their efficacy and facilitate the development of safer, plant-based therapies for gout management.
Abstract: Gout is a metabolic disorder characterized by hyperuricemia, which results in the deposition of monosodium urate crystals in joints, leading to recurrent episodes of inflammation, pain, and progressive joint damage. Xanthine oxidase (XO), the key enzyme involved in the final steps of uric acid biosynthesis, is an important therapeutic target for go...
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,
Jeevan Karthik Madavareddi
