Computational Investigation of Molnupiravir Synthetic Intermediates: DFT and Molecular Simulation

SARS-CoV-2's continual mutation poses a major global health threat, underscoring the urgent need for new antivirals.

The study aims to systematically evaluate Molnupiravir-related compounds, especially synthetic intermediates, as anti-COVID-19 drug candidates.

The ωB97XD/6-311++G(2d,p) method was used to analyze molecular structures, spectroscopic properties, and reactivity profiles. Global and local reactivity descriptors, molecular electrostatic potential (MEP), molecular docking, and molecular dynamics simulation were computed. Druggability and ADMET properties were assessed using established predictive models and ACD/Percepta software.

M-SI10's optimized geometry closely matches crystallographic data. Reactivity analysis shows M-SI3, M-SI5, and M-SI6 exhibit favorable thermodynamic stability. Most compounds meet drug-likeness criteria; several, including M-SI3, are predicted to cross the blood-brain barrier. Docking reveals M-SI3 binds the target protein with significantly higher affinity than Molnupiravir.

This study systematically evaluated the binding affinity and structural stability of candidate compounds through computational chemistry methods and ultimately selected M-SI3 as a lead compound with high target affinity and excellent conformational stability.

Integrated analysis identifies M-SI3 as the top candidate, combining balanced pharmacological properties with superior target binding and exceeding Molnupiravir's affinity.