In their previous work, the members of the center have been engaged in the in silico design of new pharmacophores, as well as in the investigation of mechanisms and prediction of their toxicological properties. Proteins that are the protagonists of certain pathophysiological conditions have been chosen as the main targets in their research. A significant part of the Center’s research is focused on the development of new scintillators and the investigation of the effects of harmful ionizing radiation. In the coming period, the aforementioned research will continue and will be expanded to the development of new biocompatible materials that exhibit a certain activity or improve both the activity and selectivity of certain active molecular species towards specific targets. The center’s accelerated development strategy will involve the use of the latest tools for predicting biological activities, which are based on machine learning and artificial intelligence. This involves the use of molecular and QSAR/QSPR modeling, virtual screening, as well as the use of molecular dynamics and data mining techniques.

Integrating machine learning and artificial intelligence techniques into the Center’s workflows will enable the development of predictive models for physicochemical properties, biological activity (antitumor, antioxidant, antimicrobial…), toxicity and other relevant endpoints using machine learning algorithms. This will enable the testing of a large number of molecular libraries in a realistically short time interval on systematically selected proteins, which will significantly save resources. A significant part of the research will be focused on determining the antioxidant potential of polyhydroxycoumarins using various tests (DPPH, ABTS, ORAC and FRAP). It is planned to continue testing the antiradical activity of selected compounds against biologically important reactive oxygen species. Antioxidant mechanisms (HAА, RAF, HAA-RA, RAF-HAA, SPLET-RAF, SPLET and SET-PT) will be examined in different solvents, and based on thermodynamic and kinetic parameters, the dominant mechanism of antioxidant action will be determined. It is planned to develop completely new mechanistic approaches to antioxidant action, SPLHAT-RAF and SPLET-RAF.

In the framework of radiation physics, it is planned to expand the model for estimating the distribution of alpha particle traces on LR-115 and macrofol detectors in radon diffusion chambers, using adequate V-response functions and critical detection angle functions. In the coming period, in the field of medical physics, it is planned to continue the application of FOTELP-VOX software, in order to determine the absorbed dose in the humerus in patients with breast cancer who underwent postoperative radiotherapy using simulations. The comparison will be made with the radiotherapy plan obtained by the 3D-CRT technique. The application of HBO (hyperbaric oxygen) therapy will be examined for potential radiobiological efficacy immediately before radiotherapy, during or after treatment, when symptoms of late radiation toxicity appear. In the field of bioengineering, the development of atherosclerosis in the carotid and coronary arteries will be studied, and the application of numerical and experimental approaches to determining FFR (Fractional flow reserve) will be studied.