Computational approach: 3D-QSAR, molecular docking, ADMET, molecular dynamics simulation investigations, and retrosynthesis of some curcumin analogues as PARP-1 inhibitors targeting colon cancer
Abstract
As cancer is the second-leading cause of death globally, this study strives to find efficient medications for colon cancer that cause minimal side effects. The computational approach through QSAR methods, molecular docking, simulation of Molecular Dynamics, and ADME-Tox studies has shown great importance in this area. In this context, several curcumin analogues have been investigated against the human colon cancer HCT-116. The best-established QSAR models in this study have the following statistical parameters: Rtrain2 = 0.971, Qcv2 = 0.544, and Rpred2 = 0.653 for the CoMFA model, and Rtrain2 = 0.940, Qcv2 = 0.619, and Rpred2 = 0.871 for the CoMSIA model. These results show the predictive quality of these models and confirm their robustness, which allowed the proposal of five new molecules: P1–P5. Molecular docking showed that most new compounds bind well to the PARP-1 receptor and have important interactions. According to work predictions, compounds P1, P2, P4, and P5 significantly inhibit cancerous colon cell growth through apoptosis. Molecular dynamics simulations confirmed previous findings, indicating that the P1 and P2 ligands remain stable at the PARP-1 receptor site. As a result, a synthesis method for the promoter compound P2 was suggested using retrosynthesis techniques. ADME-Tox studies confirm the proposed molecules’ potential for colon cancer treatments. The current study offers new perspectives for investigating safer, new curcumin-analogue-based drugs.
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