QSAR, Molecular Docking & ADMET Studies of Pyrrolo[2,3-d] Pyrimidine Derivatives as CDK4 Inhibitors for the Treatment of Cancer

Abstract

Background:: Cancer is caused by dysregulation of the cell cycle, which results in abnormal proliferation and the inability of cells to differentiate or die. Cyclins and cyclin-dependent kinases (CDK4) inhibitors are drugs that target a specific enzyme, CDK4 that controls cell cycle progression in cancer. Aim & Objective:: The aim of this study is to obtain an optimized pharmacophore of pyrrolo[2,3-d] pyrimidine as a CDK4 inhibitor using QSAR studies. This aids in determining the link between structure and activity in newly developed chemical entities (NCE’s). To perform molecular docking and ADMET analysis to determine the binding affinity and drug-likeness of NCE’s. Materials and Methods:: The Multiple linear regression approach (MLR) method was utilised to generate the QSAR Model using the programme QSARINS v.2.2.4. For molecular docking, the Autodock vina software was employed. While the Swiss ADME and ToxiM online tools were used to predict toxicity. Results and Discussion:: The best models generated for 2D QSAR had correlation coefficients of R2= 0.9247 & Q2= 0.924 and for 3D QSAR, coefficients were R2 = 0.9297 and Q2 = 0.876. A novel series of 68 derivatives was designed based on QSAR investigations. Molecule C-58 has shown maximum binding affinity in molecular docking as compared to the standard Ribociclib. result: For 2D QSAR, the best models produced has correlation coefficients of R2= 0.9247 and Q2= 0.924. The 3D-QSAR model obtained with R2= 0.9297 and Q2 = 0.876. Based on QSAR studies, a new series of 68 derivatives was generated Conclusion:: Fifteen compounds have shown potential as CDK4 inhibitors based on docking studies, pharmacokinetic behavior and toxicity profile. The maximum binding affinity was demonstrated by molecule C-58. other: N/A