Application of integrated computational strategies for the identification and prioritization of human telomerase inhibitors as a therapeutic approach against cancer
Human telomerase is reactivated in the majority of tumors and plays a central role in telomere maintenance and the unlimited proliferative capacity of cancer cells, making its catalytic subunit, hTERT, a promising target for the development of new therapeutic strategies. This project proposes the development and application of integrated computational strategies for the identification and prioritization of potential human telomerase inhibitors. The approach combines virtual screening, different docking and rescoring methods, protein-ligand interaction analysis, and molecular dynamics. Strategies will be explored to increase the robustness of candidate prioritization, as well as to expand the chemical diversity of the selected set. Thus, the project aims to establish a systematic and robust computational workflow capable of exploring large chemical libraries and selecting structurally diverse candidates with greater potential for interaction with telomerase.
Team: Amanda Macedo Leandro, Danielle Jesus Marques