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<p>The papain-like protease (PLpro), essential for viral replication, is an attractive target for pharmacotherapy against SARS-CoV-2. This study explores the effectiveness of chalcone-amide analogs as inhibitors of SARS-CoV-2 PLpro by virtual screening of a library containing 2,170 novel compounds using various computational methods, including 3D-QSAR models, molecular docking, molecular dynamics simulation, quantum mechanical calculations, ADMET analysis, and assessments of drug-likeness. A set of 35 chalcone-amide derivatives was used to build 3D QSAR models to suggest new bioactive molecules. Both the comparative molecular field analysis (CoMFA, Q<sup>2</sup> = 0.58, R<sup>2</sup> = 0.83, r<sup>2</sup><sub>pred</sub> = 0.67) model and the comparative molecular similarity indices analysis (CoMSIA, Q<sup>2</sup> = 0.51, R<sup>2</sup> = 0.73, r<sup>2</sup><sub>pred</sub> = 0.62) model showed a strong correlation between predicted and experimental activities. A comparison of the sorted compounds, based on the predicted pIC<sub>50</sub> values from the CoMFA and CoMSIA models, reveals that 52 compounds are shared among the top 100 compounds in both models. Then, a comprehensive sharing was made for the structural screening process between the results of molecular docking studies and the predicted inhibitory activities by the CoMFA and CoMSIA models, which explored 6 shared compounds within the top 100 compounds in three sets. Appropriate substitutions have been placed on the part of the chalcone-amide compounds defined as the backbone, forming superior chalcone-amide compounds. Molecular dynamics simulations validated the stability of ligand-enzyme complexes in solvent. MM-GB(PB)SA analysis showed consistent relative stabilities, while quantum mechanical calculations (ONIOM and AIM) confirmed relative interaction energies. Additionally, ADMET properties were evaluated.</p> Graphical Abstract <p></p>

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Designing Chalcone-Amide Derivatives as Novel Inhibitors of SARS-CoV-2 Papain-like Protease using 3D-QSAR Modeling, Molecular Docking, Quantum Mechanical Calculations, and Molecular Dynamics Simulations

  • 期刊论文

  • 发表日期：

    2026年2月6日

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  • Mona Khaksefidi,
  • Ali Ebrahimi,
  • Najmeh Mostafavi

摘要

The papain-like protease (PLpro), essential for viral replication, is an attractive target for pharmacotherapy against SARS-CoV-2. This study explores the effectiveness of chalcone-amide analogs as inhibitors of SARS-CoV-2 PLpro by virtual screening of a library containing 2,170 novel compounds using various computational methods, including 3D-QSAR models, molecular docking, molecular dynamics simulation, quantum mechanical calculations, ADMET analysis, and assessments of drug-likeness. A set of 35 chalcone-amide derivatives was used to build 3D QSAR models to suggest new bioactive molecules. Both the comparative molecular field analysis (CoMFA, Q2 = 0.58, R2 = 0.83, r2pred = 0.67) model and the comparative molecular similarity indices analysis (CoMSIA, Q2 = 0.51, R2 = 0.73, r2pred = 0.62) model showed a strong correlation between predicted and experimental activities. A comparison of the sorted compounds, based on the predicted pIC50 values from the CoMFA and CoMSIA models, reveals that 52 compounds are shared among the top 100 compounds in both models. Then, a comprehensive sharing was made for the structural screening process between the results of molecular docking studies and the predicted inhibitory activities by the CoMFA and CoMSIA models, which explored 6 shared compounds within the top 100 compounds in three sets. Appropriate substitutions have been placed on the part of the chalcone-amide compounds defined as the backbone, forming superior chalcone-amide compounds. Molecular dynamics simulations validated the stability of ligand-enzyme complexes in solvent. MM-GB(PB)SA analysis showed consistent relative stabilities, while quantum mechanical calculations (ONIOM and AIM) confirmed relative interaction energies. Additionally, ADMET properties were evaluated.

Graphical Abstract