STRUCTURAL DETERMINATION OF PLASMA KALLIKREIN PROTEIN AND IDENTIFICATION OF ITS INHIBITORS IN CANCER: AN IN-SILICO STUDY
Main Article Content
Keywords
Serine proteases, Cancer, Docking, Virtual screening, Kallikreins, Homology modelling, In-Silico studies.
Abstract
Background: The serine protease known as KLK B1 is essential to the kallikrein-kinin system and has been linked to the development of cancer. Tumor growth, metastasis, and alterations in immunological responses may be caused by dysregulation of KLK B1 and its endogenous inhibitors.
Objective: Determine the expression levels of KLK B1 and its inhibitors in various cancer types, evaluate their function in tumor progression, and assess putative inhibitory mechanisms that contribute to the formation of cancer.
Method: Using homology modelling protocols, the theoretical structure of KLK B1 will be predicted and the resulting model will be validated by several server tools. To identify new scaffold compounds that are effective against KLK B1, the active site will be examined and the ligand database is used for virtual screening.
Result: Compared to normal tissues, KLK B1 was markedly elevated in pancreatic, prostate, and breast malignancies. HIS44, ASP93, and SER188 residues in the active site triad and protein residues from GLN25 to GLY211 will be chosen as a pocket for ligand molecule binding. With the results of virtual screening and ADME characteristics, the scaffolds containing the amide pharmacophore were recognized as potential hits against the plasma kallikrein protein. KLK B1 inhibitors decreased the migration and proliferation of cancer cells while encouraging apoptosis, indicating that they may have therapeutic value.
Conclusion: The development of cancer is significantly influenced by KLK B1. The research results determined that the chosen ligand molecules with ADME parameter values are more acceptable scaffolds, highlighting the ligand molecules' drug-like activity through inhibition of KLK B1 protein. Identification of novel therapeutic scaffolds for cancer is aided by structural data, active site details, and specific ligand molecules.
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Vani Kondaparthi
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Madhavi Latha Bingi
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Thirupathi Damera
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Priyadarshini Gangidi
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Mounika Badineni
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Kiran Kumar Mustyala
Department of Chemistry, Nizam College, Osmania University, Hyderabad, Telangana, India – 500001.
Vasavi Malkhed
Molecular Modelling Research Laboratory, Department of Chemistry, Osmania University, Hyderabad, Telangana, India – 500007;
Department of Chemistry, University College of Science, Saifabad, Osmania University, Hyderabad, Telangana, India – 500004;