In Silico Pharmacological Exploration of Antioxidant Molecules for Anti-Cancer Potential

Lung cancer remains one of the most lethal malignancies worldwide, accounting for 11.4% of newly diagnosed cancers and 18% of cancer-related deaths globally (who, 2023). Tobacco smoking is the primary etiological factor, while environmental carcinogens and genetic mutations further contribute to disease development. Current treatments, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, provide limited survival benefits, highlighting the urgent need for safer and more effective therapeutic strategies. Oxidative stress plays a crucial role in lung carcinogenesis by inducing DNA damage and dysregulating cellular signaling, making antioxidant-based therapies a promising avenue. This study investigates coumarin derivatives, naturally occurring benzopyrone compounds with documented antioxidant and anticancer properties, as potential inhibitors of lung cancer-associated proteins 1m17 and 8dc4. Eleven antioxidant molecules were selected based on literature evidence and chemically prepared using chemdraw 16 and openable. Molecular docking was performed using autodock vina, while adme properties and pharmacokinetics were predicted via swissadme, and toxicity was assessed with protox-iii. Docking studies identified molecule 5 (c₁₆h₁₇cln₂o₅s) as the most potent inhibitor, exhibiting binding affinities of –8.7 kcal/mol and –7.5 kcal/mol against 1m17 and 8dc4, respectively, with strong hydrogen bonding, halogen bonding, and hydrophobic interactions. Adme analysis indicated molecule 2 (c₁₅h₁₀o₂) as having the best pharmacokinetic profile, including high gastrointestinal absorption, blood-brain barrier penetration, and no lipinski violations. Toxicity prediction highlighted molecule 1 as the safest compound, showing no adverse endpoints across organ systems. Collectively, these findings suggest that while molecule 5 demonstrates the highest binding efficacy and structural compatibility for therapeutic development. This integrative computational study underscores the potential of antioxidant coumarin derivatives as promising anticancer agents and provides a strong basis for subsequent in vitro and in vivo validation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-24
DOI
https://doi.org/10.5281/zenodo.19724730
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

In Silico Pharmacological Exploration of Antioxidant Molecules for Anti-Cancer Potential

Akhil Malik, Kumari Neha, Debjit Das
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

In Silico Pharmacological Exploration of Antioxidant Molecules for Anti-Cancer Potential

Akhil Malik, Kumari Neha, Debjit Das
article en

Abstract

Lung cancer remains one of the most lethal malignancies worldwide, accounting for 11.4% of newly diagnosed cancers and 18% of cancer-related deaths globally (who, 2023). Tobacco smoking is the primary etiological factor, while environmental carcinogens and genetic mutations further contribute to disease development. Current treatments, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, provide limited survival benefits, highlighting the urgent need for safer and more effective therapeutic strategies. Oxidative stress plays a crucial role in lung carcinogenesis by inducing DNA damage and dysregulating cellular signaling, making antioxidant-based therapies a promising avenue. This study investigates coumarin derivatives, naturally occurring benzopyrone compounds with documented antioxidant and anticancer properties, as potential inhibitors of lung cancer-associated proteins 1m17 and 8dc4. Eleven antioxidant molecules were selected based on literature evidence and chemically prepared using chemdraw 16 and openable. Molecular docking was performed using autodock vina, while adme properties and pharmacokinetics were predicted via swissadme, and toxicity was assessed with protox-iii. Docking studies identified molecule 5 (c₁₆h₁₇cln₂o₅s) as the most potent inhibitor, exhibiting binding affinities of –8.7 kcal/mol and –7.5 kcal/mol against 1m17 and 8dc4, respectively, with strong hydrogen bonding, halogen bonding, and hydrophobic interactions. Adme analysis indicated molecule 2 (c₁₅h₁₀o₂) as having the best pharmacokinetic profile, including high gastrointestinal absorption, blood-brain barrier penetration, and no lipinski violations. Toxicity prediction highlighted molecule 1 as the safest compound, showing no adverse endpoints across organ systems. Collectively, these findings suggest that while molecule 5 demonstrates the highest binding efficacy and structural compatibility for therapeutic development. This integrative computational study underscores the potential of antioxidant coumarin derivatives as promising anticancer agents and provides a strong basis for subsequent in vitro and in vivo validation.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 4%
Computational Drug Discovery Methods
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