Quantum chemical and molecular modeling approaches for repurposing anticoagulants against SARS-CoV-2 main protease

Abstract The SARS-CoV-2 pandemic has posed a global health emergency since 2019, driving continuous efforts to discover effective treatments. While vaccines and recommended medications exist, drug repurposing offers a cost-effective and efficient approach to identify new therapeutic options. Anticoagulants, previously used to mitigate hypercoagulability linked to SARS-CoV-2 infection, present promising candidates for repurposing as antiviral agents. This study combines molecular docking, molecular dynamics simulations, and Density Functional Theory (DFT) analysis to evaluate the inhibitory potential of six anticoagulant drugs against the SARS-CoV-2 main protease (Mpro). Molecular docking identified Warfarin and Fluindione as the most potent candidates, exhibiting binding affinities of −6.9 and −6.8 kcal/mol, respectively. Molecular dynamics simulations confirmed the stability of these drug-protease complexes in an aqueous environment, potentially disrupting viral replication. Additionally, DFT calculations provided insights into the electronic properties governing molecular reactivity and stability. Quantum descriptors, including HOMO-LUMO energy gaps, chemical potential, hardness, and electrophilicity, were evaluated to rationalize the docking interactions. The results indicate that Apixaban, characterized by the highest hardness and stability, exhibited robust electron-donating and accepting properties, while Fluindione demonstrated high electrophilicity, correlating with its reactivity. These findings offer a comprehensive computational framework for repurposing anticoagulants as SARS-CoV-2 inhibitors and warrant further experimental validation.

Authors

Institutions

Publication Details

Journal
Chemical Product and Process Modeling
Published
2025-10-16
DOI
https://doi.org/10.1515/cppm-2025-0098
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum chemical and molecular modeling approaches for repurposing anticoagulants against SARS-CoV-2 main protease

Hassan Nour, Samir Chtita, Abdelkbir Errougui, Nouh Mounadi et al.
1 citations
Chemical Product and Process Modeling
Computational Drug Discovery Methods
1.50
article

Quantum chemical and molecular modeling approaches for repurposing anticoagulants against SARS-CoV-2 main protease

Hassan Nour, Samir Chtita, Abdelkbir Errougui, Nouh Mounadi, Bouchra Rossafi, Mohammed Bouachrine
article en
1 citations

Abstract

Abstract The SARS-CoV-2 pandemic has posed a global health emergency since 2019, driving continuous efforts to discover effective treatments. While vaccines and recommended medications exist, drug repurposing offers a cost-effective and efficient approach to identify new therapeutic options. Anticoagulants, previously used to mitigate hypercoagulability linked to SARS-CoV-2 infection, present promising candidates for repurposing as antiviral agents. This study combines molecular docking, molecular dynamics simulations, and Density Functional Theory (DFT) analysis to evaluate the inhibitory potential of six anticoagulant drugs against the SARS-CoV-2 main protease (Mpro). Molecular docking identified Warfarin and Fluindione as the most potent candidates, exhibiting binding affinities of −6.9 and −6.8 kcal/mol, respectively. Molecular dynamics simulations confirmed the stability of these drug-protease complexes in an aqueous environment, potentially disrupting viral replication. Additionally, DFT calculations provided insights into the electronic properties governing molecular reactivity and stability. Quantum descriptors, including HOMO-LUMO energy gaps, chemical potential, hardness, and electrophilicity, were evaluated to rationalize the docking interactions. The results indicate that Apixaban, characterized by the highest hardness and stability, exhibited robust electron-donating and accepting properties, while Fluindione demonstrated high electrophilicity, correlating with its reactivity. These findings offer a comprehensive computational framework for repurposing anticoagulants as SARS-CoV-2 inhibitors and warrant further experimental validation.

Chemical Product and Process Modeling
Université Moulay Ismail de Meknes (MA), University of Hassan II Casablanca (MA)
Openalex Percentile: Top 12%
Computational Drug Discovery Methods
1.50
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.