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Updated: Jan 19, 2026
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Quantitative structure-activity relationship and molecular docking studies on human proteasome inhibitors for
Deepika Yadav1, Bhartendu Nath Mishra2, Feroz Khan1
1Department of Metabolic and Structural Biology, CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, Uttar Pradesh, India.
Abstract:
The abnormal ubiquitin-proteasome is found as an important target in various human diseases, especially in cancer, and recently it has received prevalent attention as a challenging therapeutic target. The current work is designed to derive a predictive two-dimensional quantitative structure-activity relationship model for anticancer human proteasome target of NF-κB signaling pathway. The established 2 D-QSAR is dependent on multiple linear regression approach and validated through leave-One-Out and external test set prediction method. The robust QSAR model showed the r2 of 0.83 and q2 of 0.80 and pred_r2 of 0.77. Three chemical properties, electronegativity count, average potential, and T_2_N_6 were identified as significant descriptors to predict the anticancer activities of the proteasome antagonists. Besides, the predicted top hit compounds were considered to check out the compliance with Rule of five and pharmacokinetic parameters for oral bioavailability in the human body. The molecular docking was accomplished to unravel the molecular mode of action of best-predicted compounds which was compatible with the standard drug. Following this approach, lastly two compounds NP and AP were recognized as the best candidates since these top compounds follow all the standard limit point of entire filters and indicated effective and decent docking score. The outcomes of the study sturdily suggested that the developed model and top hit compound's binding conformation are rational in the exploration of unknown antagonist's anticancer activity. The research would be of great support and is supposed to be of immense significance in the development and designing of drug-like candidates in preliminary drug discovery. Communicated by Ramaswamy H. Sarma.
Insights
This study developed a predictive model for anticancer drugs targeting the proteasome and NF-κB pathway. Two novel compounds, NP and AP, were identified as promising drug candidates with favorable properties and docking scores.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Pharmacology
Background:
- Abnormal ubiquitin-proteasome system function is implicated in various human diseases, particularly cancer.
- The proteasome is a challenging yet significant therapeutic target for anticancer drug development.
- The NF-κB signaling pathway plays a crucial role in cancer progression and is a key target for therapeutic intervention.
Purpose of the Study:
- To derive a predictive two-dimensional quantitative structure-activity relationship (2D-QSAR) model for anticancer agents targeting the human proteasome within the NF-κB signaling pathway.
- To identify novel chemical descriptors that correlate with anticancer activity against the proteasome.
- To evaluate potential drug candidates for oral bioavailability and molecular interactions.
Main Methods:
- Development of a 2D-QSAR model using multiple linear regression.
- Validation of the QSAR model using leave-One-Out and external test set prediction.
- Identification of significant chemical descriptors (electronegativity count, average potential, T_2_N_6).
- In silico evaluation of predicted compounds for drug-likeness (Rule of Five) and pharmacokinetic properties.
- Molecular docking to determine the binding mode and affinity of top-ranked compounds.
Main Results:
- A robust QSAR model was established with high statistical significance (r²=0.83, q²=0.80, pred_r²=0.77).
- Electronegativity count, average potential, and T_2_N_6 were identified as key descriptors for predicting anticancer activity.
- Two compounds, NP and AP, demonstrated excellent drug-likeness, favorable pharmacokinetics, and significant docking scores, indicating compatibility with the standard drug's binding mode.
- The predicted compounds' binding conformations were rational and aligned with the molecular target.
Conclusions:
- The developed 2D-QSAR model provides a reliable framework for predicting anticancer activity against the proteasome.
- Compounds NP and AP represent promising lead candidates for further development in anticancer drug discovery.
- This study offers valuable insights for the rational design and discovery of novel proteasome inhibitors.
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