Abstract:
The aim of this thesis was to identify new inhibitors of the SGLT2 transporter, a therapeutic target
used in the treatment of type 2 diabetes. To achieve this, we conducted an in silico study based on the
known structures of marketed gliflozins. Similar molecules were searched in the PubChem database
and virtually tested through molecular docking. The results showed that several analogues formed
more stable complexes than the reference drugs, particularly one analogue of Sotagliflozin. A
molecular dynamics simulation confirmed the stability of this complex. Finally, using artificial
intelligence tools (Machine Learning), we evaluated the ADMET properties of these compounds,
which proved to be very favorable. This work highlights the potential of the approach used for
discovering new drug candidates, although experimental validation is still required
