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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.