Abstract
Caspases (cysteine-aspartic proteases) play critical roles in inflammation and the programming of cell death in the form of necroptosis, apoptosis, and pyroptosis. The name of these enzymes has been chosen in accordance with their cysteine protease activity. They act as cysteines in nucleophilically active sites to attack and cleave target proteins in the aspartic acid and amino acid C-terminal. Based on the substrate's structure and the specificity, the physiological activity of caspases is divided. However, in apoptosis, the division of caspases into initiating caspases (caspase 2, 8, 9, and 10) and executive caspases (caspase 3, 6, and 7) is essential. The present study aimed to perform Proteochemometrics Modeling to generalize the data on caspases, which could predict ligand and protein interactions. In this study, we employed protein and ligand descriptors. Moreover, protein descriptors were computed using the Protr R package, while PADEL-Descriptor was employed for the computation of ligand descriptors. In addition, NCA (Neighborhood Component Analyses) was used for descriptor selection, and SVR, decision tree, and ensemble methods were utilized for the proteochemometrics modeling. This study shows that the ensemble model demonstrates superior performance compared with other models in terms of R2, Q2, and RMSE criteria.