Identification of NEK7 inhibitors: structure based virtual screening, molecular docking, density functional theory
Mubashir Aziz1, Syeda Abida Ejaz1, Hafiz Muzzammel Rehman2,3
1Department of Pharmaceutical Chemistry, Faculty of Pharmacy, The Islamia University of Bahawalpur, Pakistan.
Abstract:
NEK7 is a NIMA related-protein kinase that plays a crucial role in spindle assembly and cell division. Dysregulation of NEK7 protein leads to development and progression of different types of malignancies including colon and breast cancers. Therefore, NEK7 could be considered as an attractive target for anti-cancer drug discovery. However, few efforts have been made for the development of selective inhibitors of NIMA-related kinase but still no FDA approved drug is known to selectively inhibit the NEK7 protein. Dacomitinib and Neratinib are two Enamide derivatives that were approved for treatment against non-small cell lung cancer and breast cancer respectively. Drug repurposing is a time and cost-efficient method for re-evaluating the activities of previously authorized medications. Thus, the present research involves the repurposing of two FDA-approved medications via comprehensive in silico approach including Density functional theory (DFTs) studies which were conducted to determine the electronic properties of the Dacomitinib and Neratinib. Afterward, binding orientation of selected drugs inside NEK7 activation loop was evaluated through molecular docking approach. Selected drugs exhibited potential molecular interactions engaging important amino acid residues of active site. The docking score of Dacomitinib and Neratinib was -30.77 and -26.78 kJ/mol, respectively. The top ranked pose obtained from molecular docking was subjected to Molecular Dynamics (MD) Simulations for investigating the stability of protein-ligand complex. The RMSD pattern revealed the stability of protein-ligand complex throughout simulated trajectory. In conclusion, both drugs displayed inhibitory efficacy against NEK7 protein and provide a prospective therapy option for malignant malignancies linked with NEK7.
Insights
This study repurposed Dacomitinib and Neratinib as potential NEK7 inhibitors for cancer therapy. Computational methods confirmed their efficacy, suggesting a new avenue for treating NEK7-related malignancies.
Area of Science:
- Biochemistry
- Computational Chemistry
- Oncology
Background:
- NEK7 protein kinase is vital for cell division and its dysregulation is linked to cancers like colon and breast cancer.
- Targeting NEK7 offers a promising strategy for anti-cancer drug discovery, but selective inhibitors are lacking.
- Drug repurposing presents an efficient approach to identify new therapeutic applications for existing medications.
Purpose of the Study:
- To investigate the potential of repurposing FDA-approved drugs, Dacomitinib and Neratinib, as NEK7 inhibitors.
- To evaluate the molecular interactions and binding stability of these drugs with the NEK7 protein using computational methods.
Main Methods:
- Density Functional Theory (DFT) studies were performed to analyze the electronic properties of Dacomitinib and Neratinib.
- Molecular docking simulations were used to assess the binding orientation and interactions of the drugs within the NEK7 activation loop.
- Molecular Dynamics (MD) simulations were conducted to evaluate the stability of the protein-ligand complexes.
Main Results:
- DFT analysis provided insights into the electronic characteristics of the candidate drugs.
- Molecular docking revealed that both Dacomitinib and Neratinib form significant molecular interactions with key amino acid residues in the NEK7 active site, with docking scores of -30.77 kJ/mol and -26.78 kJ/mol, respectively.
- MD simulations demonstrated the stability of the Dacomitinib-NEK7 and Neratinib-NEK7 complexes throughout the simulated trajectory.
Conclusions:
- Dacomitinib and Neratinib exhibit inhibitory potential against NEK7 protein.
- These repurposed drugs represent prospective therapeutic options for managing NEK7-associated malignancies.
- The study highlights the utility of computational approaches in drug repurposing for oncology.
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