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introductionThe current study aims to determine the structure of the protein Kallikrein 11 and to screen for small natural product ligands to identify inhibitors of Kallikrein 11. Kallikreinrelated peptidase 11 (KLK 11) belongs to the Kallikrein family of Serine proteases. Kallikrein 11 is a multifunctional protease. In addition to causing cancer, this plays a critical role in a variety of physiological functions, including blood pressure regulation, sperm liquefaction, and skin desquamation. This study aims to identify the protein's 3D structure, perform virtual screening with a natural product database, and find ADME characteristics for the most desirable ligand retrieved. Additionally, it aims to evaluate the effectiveness of binding affinity-based scoring systems in differentiating active KLK11 inhibitors from decoy compounds through the use of Receiver Operating Characteristic (ROC) analysis.

methodsUsing homology modelling protocols, the theoretical model of Kallikrein 11 will be predicted, and the resulting structure will be validated by several server tools. To identify new scaffold compounds that are effective against Kallikrein 11, the active site is examined, and the ligand database is used for virtual screening. The ROC-Area Under the Curve (AUC) is used to assess the effectiveness of inhibitors.

resultsThe HIS94, ASP142, and SER235 residues in the KLK 11 protein are essential as the active site triad, and residues from GLY24 to ASN281 were chosen as a pocket for ligand molecule binding, according to the results of the virtual screening. With an AUC of 0.837, the results show a strong predictive ability, indicating that binding affinity is a trustworthy parameter for early virtual screening pipelines that target KLK11. Given its superior ADME qualities, the scaffolds containing the polyphenols and flavone pharmacophores were recognized as a potential lead drug against the KLK 11 protein. DISCUSSION: The findings confirm the reliability of the homology-modelled KLK11 structure and demonstrate that its catalytic triad and binding pocket can effectively distinguish active scaffolds through virtual screening. The strong ROC-AUC value indicates that binding-affinity-based selection is robust for early inhibitor discovery. Notably, the natural-product scaffolds displayed higher binding affinities than approved drugs, highlighting their potential as superior KLK11 inhibitor candidates.

conclusionThe research results demonstrated that the chosen ligand molecules with ADME parameter values are more acceptable medications, highlighting the ligand molecules' drug-like activity through the inhibition of KLK 11 protein. The identification of novel therapeutic scaffolds for cancer is aided by structural data, active site details, specific ligand molecules, and ROC-AUC of inhibitors.