ArticleScientific reports2024
QSPR/QSAR study of antiviral drugs modeled as multigraphs by using TI's and MLR method to treat COVID-19 disease.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Graph-Theoretical Approach for Predicting Physicochemical Properties of Stiff-Person Syndrome Drugs.ChemistryOpen · 2026Article
- Predictive performance and QSPR analysis of SARS-CoV-2 and tuberculosis drugs using distance-based topological descriptors.Scientific reports · 2026Article
- Integrated Computer-Aided Drug Design: Advances in GPCR Natural Ligand Discovery.Cell biochemistry and biophysics · 2026Review
- Degree-based topological indices and their graph energies in the QSPR analysis and ranking of UV-filter compounds.Frontiers in chemistry · 2026Article
- Developing a QSPR model for Alzheimer's drugs using topological indices and M-polynomial: A computational study.Scientific reports · 2025Article
- Titania: an integrated tool for in silico molecular property prediction and NAM-based modeling.Molecular diversity · 2025Article
- Computational insights and study of drugs for dry eye disease through QSPR and MCDM approaches using topological indices.Scientific reports · 2025Article
- On QSPR analysis of pulmonary cancer drugs using python-driven topological modeling.Scientific reports · 2025Article
- Quantitative structure-property relationship modeling and ranking of necrotizing fasciitis drugs via degree-based topological indices.Frontiers in chemistry · 2025Article
- Topological insights into breast cancer drugs: a QSPR approach using resolving topological indices.Frontiers in chemistry · 2025Article
- QSPR graph model to explore physicochemical properties of potential antiviral drugs of dengue disease through novel coloring-based topological indices.Frontiers in chemistry · 2025Article
- Predictive modelling and ranking:Frontiers in chemistry · 2025Article
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4 authors.
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Abstract
The ongoing COVID-19 pandemic continues to pose significant challenges worldwide, despite widespread vaccination. Researchers are actively exploring antiviral treatments to assess their efficacy against emerging virus variants. The aim of the study is to employ M-polynomial, neighborhood M-polynomial approach and QSPR/QSAR analysis to evaluate specific antiviral drugs including Lopinavir, Ritonavir, Arbidol, Thalidomide, Chloroquine, Hydroxychloroquine, Theaflavin and Remdesivir. Utilizing degree-based and neighborhood degree sum-based topological indices on molecular multigraphs reveals insights into the physicochemical properties of these drugs, such as polar surface area, polarizability, surface tension, boiling point, enthalpy of vaporization, flash point, molar refraction and molar volume are crucial in predicting their efficacy against viruses. These properties influence the solubility, permeability, and bio availability of the drugs, which in turn affect their ability to interact with viral targets and inhibit viral replication. In QSPR analysis, molecular multigraphs yield notable correlation coefficients exceeding those from simple graphs: molar refraction (MR) (0.9860), polarizability (P) (0.9861), surface tension (ST) (0.6086), molar volume (MV) (0.9353) using degree-based indices, and flash point (FP) (0.9781), surface tension (ST) (0.7841) using neighborhood degree sum-based indices. QSAR models, constructed through multiple linear regressions (MLR) with a backward elimination approach at a significance level of 0.05, exhibit promising predictive capabilities highlighting the significance of the biological activity
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