Malaria remains a critical global health issue, worsen by the rise of parasite resistance to antimalarial
drugs, necessitating new therapeutic agents. This study investigated thiosemicarbazone as a promising
scaffold for antimalarial activity through the inhibition of cysteine proteases, particularly falcipain-2,
with the Quantitative Structure-Activity Relationship (QSAR) approach. Thiosemicarbazone derivative
structures were optimized by the Density Functional Theory (DFT) method with the B3LYP equation
and 6-31G as the basis set using Gaussian09 software, with descriptors computed using Gaussian09
and PaDEL-Descriptor 2.21. Multilinear regression analysis using SPSS Statistics 27.0 identified the
optimal QSAR model, validated using the Leave-One-Out technique. The QSAR equation obtained was
Log (1/EC50) = 51.459 –0.001 x (TotalE) + 20.369 x (HLGap) + 0.115 x (Polarizability) + 0.030 x (MR) –
0.543 x (LogP) –3.243 x (Density) –0.465 x (Hacc) + 13.892 x (qN3) + 70.657 x (qN6) + 2.884 x (qS5) –
0.050 x (EVDW) –0.187 x (LipoIndex) + 0.001 x (WeinerN) + 0.729 x (IC1). Compound 6 was chosen as the
lead compound in the design of the novel derivatives. As a result of the modification based on the QSAR
equation, compounds 51 and 53 were predicted to have a lower EC50 value, indicating a higher
antimalarial activity compared to the compounds in the training set.