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Updated: Nov 20, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
In silico design of novel FAK inhibitors using integrated molecular docking, 3D-QSAR and molecular dynamics
Pouria Shirvani1, Afshin Fassihi1,2
1Department of Medicinal Chemistry, Faculty of Pharmacy and Pharmaceutical Science, Isfahan University of Medical Science, Isfahan, Iran.
Abstract:
Focal adhesion kinase (FAK) is a cytoplasmic tyrosine kinase that plays a crucial role in integrin signaling that regulates essential cellular functions including growth, motility, proliferation and survival in different types of cells. Interestingly, it has also shown to be up-regulated in various types of tumors, hence it has emerged as a significant therapeutic target for the development of selective inhibitors. In present work, with the aim of achieving further insight into the structural characteristics required for the FAK inhibitory activity, a combined approach of molecular modeling studies including molecular docking, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) simulation were carried out on a series of 7H-pyrrolo[2,3-d]pyrimidine and thieno[3,2-d]pyrimidine FAK inhibitors. The probable binding modes and interactions of inhibitors into the FAK active site were predicted by molecular docking. The 3D-QSAR models were developed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods, with three ligand-based, docking-based and receptor-based alignment techniques. Both CoMFA and CoMSIA models obtained from receptor-based alignment were superior to the ones obtained by other alignment methods. However, the CoMSIA model (q2 = 0.679, r2 = 0.954 and r2pred = 0.888) depicted almost better predictive ability than the CoMFA model (q2 = 0.617, r2 = 0.932 and r2pred = 0.856). The contour map analysis revealed the relationship between the structural features and inhibitory activity. The docking results and CoMFA and CoMSIA contour maps were in good accordance. Based on the information obtained from the molecular docking and contour map analysis, a series of novel FAK inhibitors were designed that showed better predicted inhibitory activity than the most potent compound 31 in the data set. Finally, the stability of the reference molecule 31 and the designed compounds D15 and D27 were evaluated through a 30 ns of MD simulation and their binding free energies were calculated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The result of MD simulation and binding free energy decomposition demonstrated the important role of van der Waals interactions alongside H-bond ones that were in consistent with the docking and contour maps analysis results. In sum, the results from this study may provide a significant insight for developing more effective novel FAK inhibitors.Communicated by Ramaswamy H. Sarma.
Insights
This study used molecular modeling to design novel focal adhesion kinase (FAK) inhibitors. Computational analysis revealed key structural features for improved FAK inhibition, guiding the development of potentially more effective cancer therapeutics.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Drug Discovery
Background:
- Focal adhesion kinase (FAK) is a key regulator of cellular functions and is often overexpressed in tumors.
- FAK is a significant therapeutic target for developing selective inhibitors for cancer treatment.
Purpose of the Study:
- To gain structural insights into FAK inhibitory activity.
- To design novel 7H-pyrrolo[2,3-d]pyrimidine and thieno[3,2-d]pyrimidine based FAK inhibitors.
Main Methods:
- Employed molecular docking, 3D-QSAR (CoMFA, CoMSIA), and molecular dynamics (MD) simulations.
- Utilized ligand-based, docking-based, and receptor-based alignment techniques for 3D-QSAR model development.
- Evaluated stability and binding free energies of novel inhibitors using MD simulations and MM-PBSA.
Main Results:
- Receptor-based alignment yielded superior CoMFA and CoMSIA models, with CoMSIA showing higher predictive ability (q²=0.679, r²=0.954, r²pred=0.888).
- Contour map analysis identified crucial structural features for FAK inhibition, consistent with docking results.
- Designed novel inhibitors demonstrated enhanced predicted activity compared to the reference compound.
- MD simulations and MM-PBSA confirmed the stability of designed compounds and highlighted the importance of van der Waals and H-bond interactions.
Conclusions:
- The study provides significant structural insights for the development of more effective FAK inhibitors.
- The combined computational approach successfully guided the design of novel, potent FAK inhibitors.
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