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Computational Modelling Strategies for Exploring Triazolopyridazine PIM1 Kinase Inhibitors as Anticancer Agents
Vinayak Walhekar1, Chandrakant Bagul1, Dileep Kumar1
1Department of Pharmaceutical Chemistry, BVDU'S Poona College of Pharmacy, Erandwane Pune-411038, Maharashtra, India.
Background:
PIM (Proviral Integration site for Moloney Murine Leukemia virus) kinases are members of the class of kinase family serine/threonine kinases, which play a crucial role in cancer development. As there is no drug in the market against PIM-1, kinase has transpired as a budding and captivating target for discovering new anticancer agents targeting PIM-1 kinase.
Aim:
The current research pondered the development of new PIM-1 kinase inhibitors by applying a ligand-based and structure-based drug discovery approach involving 3D QSAR, molecular docking, and dynamics simulation.
Methods:
In this study, association allying the structural properties and biological activity was undertaken using 3DQSAR analysis. The 3D-QSAR model was generated with the help of 35 compounds from which the best model manifested an appreciated cross-validation coefficient (q2) of 0.8866 and conventional correlation coefficient (r2) of 0.9298, respectively and the predicted correlation coefficient (r2 pred) was obtained as 0.7878.
Results:
The molecular docking analysis demonstrated that the analogs under analysis occupied the active site of the PIM-1 kinase receptor and interactions with Lys67 in the catalytic region, Asp186 in the DFG motif, and Glu171 were noticed with numerous compounds.
Discussion:
Furthermore, the molecular dynamics simulation study stated that the ligand portrayed strong conformational stability within the active site of PIM-1 kinase protein, forming two hydrogen bonds until 100 ns, respectively.
Conclusion:
Overall outcomes of the study revealed that applications of the ligand-based drug discovery approach and structure-based drug discovery strategy conceivably applied to discovering new PIM-1 kinase inhibitors as anticancer agents.
Insights
Researchers developed novel PIM-1 kinase inhibitors for cancer treatment using computational methods. Molecular docking and dynamics simulations confirmed their potential as effective anticancer agents targeting PIM-1 kinase.
Area of Science:
- Medicinal Chemistry
- Computational Drug Discovery
- Oncology
Background:
- PIM (Proviral Integration site for Moloney Murine Leukemia virus) kinases are serine/threonine kinases crucial in cancer development.
- PIM-1 kinase is a promising target for novel anticancer agents due to the lack of existing drugs.
- This study focuses on developing new PIM-1 kinase inhibitors.
Purpose of the Study:
- To develop novel PIM-1 kinase inhibitors using integrated ligand-based and structure-based drug discovery approaches.
- To explore the potential of 3D QSAR, molecular docking, and dynamics simulations in identifying new anticancer agents.
Main Methods:
- 3D-QSAR analysis was employed to correlate structural properties with biological activity.
- A 3D-QSAR model was built using 35 compounds, achieving high cross-validation (q2=0.8866) and correlation (r2=0.9298) coefficients.
- Molecular docking and dynamics simulations were performed to assess ligand-receptor interactions and stability.
Main Results:
- Molecular docking revealed that analyzed analogs bind to the PIM-1 kinase active site.
- Key interactions were observed with residues Lys67, Asp186 (DFG motif), and Glu171.
- Molecular dynamics simulations showed stable ligand conformation within the active site, forming hydrogen bonds up to 100 ns.
Conclusions:
- The study successfully applied ligand-based and structure-based drug discovery strategies.
- The findings suggest a viable approach for discovering new PIM-1 kinase inhibitors as anticancer agents.
- Computational methods are effective in identifying potential drug candidates for PIM-1 kinase.
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