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Updated: Feb 17, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Structural Probing, Screening and Structure-Based Drug Repositioning Insights into the Identification of Potential
Uma Devi Bommu1, Kranthi Kumar Konidala1, Rishika Pamanji1
1Department of Zoology, Sri Venkateswara University, Tirupati, A.P, 517502, India.
Abstract:
The rate-limiting enzyme cyclooxygenase-2 (COX-2) is considered as an insightful prognostic target for non-small cell lung cancer (NSCLC) therapy. Now, administration and prolonged utilization of selective COX-2 inhibitors (COXIBs) towards moderating the NSCLC has been associated with different side effects. In the present study, we focused on the structure-based drug repositioning approaches for predicting therapeutic potential de novo candidates for human COX-2. Due to discrepancies in the eminence of x-ray diffraction structures, creates a big barrier in drug discovery approach. Hence, the adaptable COX-2 structure was investigated using multi-template modeling method. Next, a dataset of twenty-six celebrex-associated optimized scaffolds were screened from ZINC database. Comparative docking approaches were then utilized to identify five compounds as best binders to the active site of COX-2 structures and strongly agree with enormous experimental consequences. MD simulations of regarded protein-ligand complexes reveals that lead molecules were stabilized dynamically in inside the cyclooxygenase site by forming potential salt bridges with Tyr348, Tyr385 and Ser530 residues. These significant results revealed that, identified druggables could prevent the tyrosyl radicals and prostaglandin production that reduces NSCLC progression. Furthermore, pharmacokinetics assets of respected ligands were analyzed, which incorporates similarity ensemble approach, druglikeness and ADMET properties. Finally, the identified novel candidates could serve as COX-2 inhibitors for NSCLC therapy, and coxibs are the best choices for designing new scaffolds to treat cyclooxygenases regard disorders.
Insights
Researchers identified novel drug candidates for non-small cell lung cancer (NSCLC) therapy by targeting cyclooxygenase-2 (COX-2). These compounds show potential as effective COX-2 inhibitors, offering an alternative to existing treatments with fewer side effects.
Area of Science:
- Biochemistry
- Pharmacology
- Computational Chemistry
Background:
- Cyclooxygenase-2 (COX-2) is a key prognostic target in non-small cell lung cancer (NSCLC) therapy.
- Selective COX-2 inhibitors (COXIBs) show therapeutic potential but are linked to adverse effects.
- Drug discovery for COX-2 is hindered by structural data limitations.
Purpose of the Study:
- To identify novel therapeutic candidates for NSCLC by repositioning drugs targeting human COX-2.
- To overcome challenges in drug discovery posed by variable X-ray diffraction structures of COX-2.
- To explore structure-based drug repositioning for developing new NSCLC treatments.
Main Methods:
- Utilized multi-template modeling to generate an adaptable COX-2 structure.
- Screened 26 celebrex-associated scaffolds from the ZINC database.
- Employed comparative docking and molecular dynamics (MD) simulations to assess binding affinity and stability.
Main Results:
- Identified five compounds exhibiting strong binding to the COX-2 active site, consistent with experimental data.
- MD simulations confirmed dynamic stabilization of lead molecules within the cyclooxygenase site via salt bridges.
- Discovered that identified compounds inhibit tyrosyl radicals and prostaglandin production, crucial for reducing NSCLC progression.
Conclusions:
- The identified novel drug candidates show promise as COX-2 inhibitors for NSCLC treatment.
- These compounds represent potential alternatives to current COXIBs, possibly with improved safety profiles.
- The study highlights the utility of structure-based drug repositioning for developing new therapies for cyclooxygenase-related disorders.
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