Cancer has been a major public health problem worldwide for years as well as the second leading cause of death in the United States. There is an estimate of 1,958,310 new cancer cases for both sexes for 2023 alone. With the decrease in accessible and immediate healthcare due to the influx of COVID-19 cases throughout the past few years, many cases have gone longer without being identified and properly treated. Despite the increase in efficient anticancer drugs and prevention methods, an effective cure has yet to be found for many types of cancer.
Many medicinal drug candidates consist of organic compounds, but metal complexes provide various mechanisms which organic compounds do not. Platinum-based drugs were critical in the movement of metal complexes as anti-tumor agents causing other metal agents to peak interest in anticancer agents. Ruthenium complexes are currently in clinical trials already because of the useful biological properties and anticancer activity.
This project uses computational chemistry to dock variations of (p-Cymene)Ru(curcuminato)chloro in DNA strands to find the best affinity for the potential anti-cancer drugs. First the geometry of the Ru-cur complex will be optimized via an inexpensive quantum mechanical method, using he GAMESS6 program. Ru-cur complex has been chosen as the metal anticancer complex because it is not very toxic, selective for cancer cells, and similar to the ligand exchange kinetics of platinum.
Once the geometry of the complex has been optimized, docking programs can be explored to find the best docking poses and binding energies for the complex in DNA strands. Promising positions of the complex will be refined using molecular dynamics programs such as Amber5 and Charmm4. Charmm-GUI7 will further modify and modify the complex with the PDB8,9 manipulator offered in program. MSI resources are necessary for the optimization of the Ru-cur complex at a higher level of theory as well as the docking procedure itself, which requires many configurations of this complicated system to be generated and evaluated.