Novel Thiosemicarbazone Quantum Dots in the Treatment of Alzheimer’s Disease Combining In Silico Models Using Fingerprints and Physicochemical Descriptors

[Image: see text] Searching for thiosemicarbazone derivatives with the potential to inhibit acetylcholinesterase for the treatment of Alzheimer’s disease (AD) is an important current goal. The QSAR(KPLS), QSAR(ANN), and QSAR(SVR) models were constructed using binary fingerprints and physicochemical (PC) descriptors of 129 thiosemicarbazone compounds screened from a database of 3791 derivatives. The R(2) and Q(2) values for the QSAR(KPLS), QSAR(ANN), and QSAR(SVR) models are greater than 0.925 and 0.713 using dendritic fingerprint (DF) and PC descriptors, respectively. The in vitro pIC(50) activities of four new design-oriented compounds N1, N2, N3, and N4, from the QSAR(KPLS) model using DFs, are consistent with the experimental results and those from the QSAR(ANN) and QSAR(SVR) models. The designed compounds N1, N2, N3, and N4 do not violate Lipinski-5 and Veber rules using the ADME and BoiLED-Egg methods. The binding energy, kcal mol(–1), of the novel compounds to the 1ACJ-PDB protein receptor of the AChE enzyme was also obtained by molecular docking and dynamics simulations consistent with those predicted from the QSAR(ANN) and QSAR(SVR) models. New compounds N1, N2, N3, and N4 were synthesized, and the experimental in vitro pIC(50) activity was determined in agreement with those obtained from in silico models. The newly synthesized thiosemicarbazones N1, N2, N3, and N4 can inhibit 1ACJ-PDB, which is predicted to be able to cross the barrier. The DFT B3LYP/def-SV(P)-ECP quantization calculation method was used to calculate E(HOMO) and E(LUMO) to account for the activities of compounds N1, N2, N3, and N4. The quantum calculation results explained are consistent with those obtained in in silico models. The successful results here may contribute to the search for new drugs for the treatment of AD.