Backgroud:
Kinases are proteins that control many biological functions. They are involved in cellular regulation, and many of them are deregulated in cancer proliferation. The evidence of this deregulation in many pathologies served as the origin of kinases as a therapeutic class and constitutes the motive that leads numerous teams to search for inhibitors of these targets.
Objective: Based on 3D-QSAR studies and the molecular docking approach, we have developed new potential inhibitors that could be optimized and transformed into colon cancer drugs.
Objective:
Based on 3D-QSAR studies and the molecular docking approach, we have developed new potential inhibitors that could be optimized and transformed into colon cancer drugs.
Method:
To design new bioactive molecules and study their interactions with the cyclin-depend kinase type 2 (CDK2) enzyme, we used two virtual screening methods: 3D-QSAR modeling and molecular docking on a series of 28 pyrimidine-based benzothiazole derivatives.
Results:
To develop models (3D QSAR) we used CoMFA and CoMSIA techniques using SYBYL-X2.0 molecular modeling software. The statistical parameters reveal that the good CoMFA model displays (Q²= 0.587; R²= 0.895) and that of CoMSIA displays (Q²= 0.552; R²= 0.768) which are considered to be very good internal prediction values, while an external validation of a test series of 5 compounds not included in the model development series gives R²test values of 0.56 for CoMFA and R²test values of 0.51 for CoMSIA. The molecular docking approach with AutoDockTools-1.5.6 is introduced in this work to enrich the interpretations extracted from the CoMFA and CoMSIA contour maps, and to provide an in silico research method for the most favorable mode of interaction of an inhibitor within its receptor (CDK2).
Conclusion:
We have constructed and validated a quantitative 3D model of structure-activity relation-ships of pyrimidine-based benzothiazole derivatives as CDK2 inhibitors. This model allows us to identify the nature and position of the groups that enhance the activity, giving us directions to discover new, more powerful molecules in a limited time.
In Silico Screening of Natural Products as Potential Inhibitors of SARS-CoV-2 Using Molecular Docking Simulation
