Ricerc@Sapienza

This project represents a piece of a wider long-term research aimed at the identification of the most probable molecular targets of a set of natural substances showing pharmacological potential within the recurrent medulloblastoma, a malignant pediatric brain tumor. Initially the main focus will be given to Curcumin that has been shown to have anti-proliferative effects on multiple cancers through targeting several pathways involved in tumorigenesis. The main goal of this part of the work will be the identification of the Curcumin targets in the inhibition of cell proliferation. To this purpose, the docking-based inverse virtual screening technique will be adopted. In this technology, a molecular docking process is employed to screen a protein database for a query ligand, and then to select an enriched subset containing possible targets of the ligand.
This specific part of the project is aimed at the development of an in-house pipeline implementing a strategy using free academic software and the computational power available at Sapienza (TeraStat). Docking engines will be AutoDock and AutoDock Vina, well known and tested free-software produced in the academic context. A Python envelope will be written to run docking experiments in batch and to automatize as far as possible the entire procedure. After the set up and testing of the pipeline, the flow of the project will consists of these steps: 1) selection from the Protein Data Bank of a set of potential Curcumin targets; 2) application of the in-house pipeline; 3) scrutiny and detailed analysis of the results and prioritization of the targets. The project will take advantage from the collaboration with other two units providing expertise in software development and in theoretical simulation of biological molecular systems, and in molecular pathology and cellular biotechnology, respectively. Once tested, the procedure will be applied to probe a number of natural substances on a wider ensemble of potential targets.