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Computational Investigation of Molnupiravir Synthetic Intermediates: DFT and Molecular Simulation
Jianjun Zhou1, Yanni Wang2, Huanhuan Xia2
1Department of Burns, the Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325200, Zhejiang, China.
Current Medicinal Chemistry
|July 29, 2026
Summary
Computational chemistry identified M-SI3 as a promising anti-COVID-19 drug candidate. This Molnupiravir-related compound shows superior target binding affinity and favorable drug-like properties compared to existing treatments.
Area of Science:
- Computational chemistry
- Drug discovery
- Molecular modeling
Background:
- SARS-CoV-2 mutations necessitate novel antiviral agents.
- Molnupiravir is an existing antiviral, but new candidates are needed.
- The study focuses on Molnupiravir synthetic intermediates.
Purpose of the Study:
- To systematically evaluate Molnupiravir-related compounds as potential anti-COVID-19 drugs.
- To identify lead compounds with high target affinity and stability.
- To assess druggability and pharmacokinetic properties.
Main Methods:
- Quantum chemical calculations (ωB97XD/6-311++G(2d,p)) for molecular analysis.
- Assessment of reactivity, molecular electrostatic potential (MEP), and molecular dynamics.
- Molecular docking and ADMET/druggability predictions using ACD/Percepta.
Main Results:
- M-SI10 geometry aligns with crystallographic data.
- M-SI3, M-SI5, and M-SI6 demonstrate good thermodynamic stability.
- M-SI3 exhibits high target binding affinity, superior to Molnupiravir, and potential blood-brain barrier penetration.
Conclusions:
- M-SI3 is identified as a lead compound due to high target affinity and stability.
- Computational methods successfully screened and selected a potent antiviral candidate.
- M-SI3 offers improved pharmacological properties and target binding over Molnupiravir.
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