Exploration and identification of novel inhibitors against Knowpain-4 of P. knowlesi using a combinatorial 3D pharmacophore modeling approach

Abstract

Papain-like cysteine protease of P. knowlesi is a significant target for the treatment of malaria infection. P. knowlesi poses a new threat to malaria eradication programs as it starts infecting humans. We have targeted P. knowlesi Knowpain-4 protein for inhibitor designing based on the molecular modeling simulations and structure-based pharmacophore modeling. In-depth sequence analysis reveals its crucial role in host hemoglobin degradation. Dihedral angles and QMEAN score analysis successfully validate the modeled structure of Knowpain4. The docking simulation leads to the prediction of E64 poses at the binding site of Knowpain4 protein. The ligand–receptor interaction information is used for generating five different pharmacophore models taking a diverse set of parameters. A combined 3D features-based, a pharmacophore model is assembled to screen in-house database. The presence of E64, along with 2,128 compounds in the output cross-confirms our screening model. Later on, top 22 screened compounds with higher relative pharmacophore score to E64 is selected for interaction study. The docking simulation experiments result in the identification of 6 compounds that occupies the functional, active site of Knowpain4 protein with high binding affinity. Further, pharmacokinetic studies showed that the identified compounds are potential bioactive molecules with unique scaffolds, and may have the potential to block the expression of Knowpain4 protease.