Nashrieh Shimi va Mohandesi Shimi Iran

Nashrieh Shimi va Mohandesi Shimi Iran

Design and Evaluation of Novel Potent G-protein Coupled Receptor Kinase Inhibitors Using Virtual Screening Methods

Document Type : Research Article

Authors
Saeid Azimi
Leila Heydari
Department of Chemistry, Payame Noor University. Tehran, Iran.
Abstract
The G-protein receptor kinases are members of the most effective enzymes in the incidence of some important disease such as cardiovascular diseases, hypertension and Alzheimer’s disease. One of these enzymes is a protein with PDB code: 3v5w in the protein data bank. The in-silico study on the interaction of variety of inhibitor ligands with this enzyme was performed. The results of the interaction between selected ligands and target protein were investigated and analyzed using molecular screening by molecular docking simulation methods. The calculations of some factors such as binding energy between ligands and target protein, non-bonding interactions of ligands in the active site of enzyme and analysis of the result of molecular docking scoring were performed. The results were compared with a standard inhibitor (Paroxetine). Furthermore, to better evaluate and correct the selection of the lead compound, the related properties of absorption, distribution, metabolism, excretion and toxicity (ADMET) of high-scored ligands were compared with pharmacokinetic factors of Paroxetine using ADMETLab 2.0 data server platform. As the result, the compound L10, (4R,5S)-5-(1,3-benzodioxol-5-yloxymethyl)-4-(4-fluorophenyl)piperidin-2-one was introduced as a novel potent inhibitor ligand which has the better potency, more binding energy and more  appropriate pharmacokinetic properties.
Keywords
Molecular Docking Simulation
Novel Inhibitor of Protein Kinase
Molecular Screening
Paroxetine
Pharmacokinetic Properties

Subjects

[1] Yan Y., Zhou X.E., Novick S.J., Shaw S.J., Li Y., Brunzelle J.S., Melcher K., Structures of AMP-Activated Protein Kinase Bound to Novel Pharmacological Activators in Phosphorylated, Non-Phosphorylated, and Nucleotide-Free States. Journal of Biological Chemistry, 294(3): 953-967 (2019).
[2]  Rozpędek W., Pytel D., Nowak-Zduńczyk A., Lewko D., Wojtczak R., Diehl J.A., Majsterek, I., Breaking the DNA Damage Response Via Serine/Threonine Kinase Inhibitors to Improve Cancer Treatment. Current medicinal chemistry, 26(8): 1425-1445 (2019).
[3] Uitdehaag J.C., de Man J., Willemsen-Seegers N., Prinsen M.B., Libouban M.A., Sterrenburg J.G., Zaman G.J., Target Residence Time-Guided Optimization on TTK Kinase Results in Inhibitors with Potent Anti-Proliferative Activity. Journal of Molecular Biology, 429(14): 2211-2230 (2017).
[4] Guccione M., Ettari R., Taliani S., Da Settimo F., Zappalà M., Grasso S., G-Protein-Coupled Receptor Kinase 2 (GRK2) Inhibitors: Current Trends and Future Perspectives. Journal of medicinal chemistry, 59(20): 9277-9294 (2016).
[5] Thal D.M., Homan K.T., Chen J., Wu E.K., Hinkle P.M., Huang Z.M., Tesmer J.J., Paroxetine is a Direct Inhibitor of G Protein-Coupled Receptor Kinase 2 and Increases Myocardial Contractility. ACS chemical biology, 7(11): 1830-1839 (2012).
[6] Yao H., Uras G., Zhang P., Xu S., Yin Y., Liu J., Xu J., Discovery of Novel Tacrine–Pyrimidone Hybrids as Potent Dual AChE/GSK-3 Inhibitors for the Treatment of Alzheimer’s Disease. Journal of Medicinal Chemistry, 64(11): 7483-7506 (2021).
[7] Lian X., Xia Z., Li X., Karpov P., Jin H., Tetko I.V., Wu S., Anti-MRSA Drug Discovery by Ligand-Based Virtual Screening and Biological Evaluation. Bioorganic Chemistry, 114: 105042 (2021).
[8] Mahdian S., Zarrabi M., Moini A., Shahhoseini M., Movahedi M., In Silico Evidence for Prednisone and Progesterone Efficacy in Recurrent Implantation Failure Treatment. Journal of Molecular Modeling, 28(4): 105 (2022).
[9] Glaab E., Building a Virtual Ligand Screening Pipeline Using Free Software: A Survey. Briefings in Bioinformatics, 17(2): 352-366 (2016).
[10] Azeez S., Babu R.O., Aykkal R., Narayanan, R., Virtual Screening and in Vitro Assay of Potential Drug Like Inhibitors from Spices Against Glutathione-S-Transferase of Filarial Nematodes. Journal of molecular modeling, 18: 151-163 (2012).
[11] Mahdian S., Zarrabi M., Panahi Y., Dabbagh, S., Repurposing FDA-Approved Drugs to Fight COVID-19 Using in Silico Methods: Targeting SARS-CoV-2 RdRp Enzyme and Host Cell Receptors (ACE2, CD147) Through Virtual Screening and Molecular Dynamic Simulations. Informatics in medicine unlocked, 23: 100541 (2021).
[12] Azmian Moghadam F., Kefayati H., Evazalipour M., Ghasemi S., Design, Synthesis, Biological Evaluation, and Docking Study of Novel 4-Anilinoquinazolines Derivatives as Anticancer Agents, Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 41: 353-367 (2022).
[13] Ibeji C.U., Oguejiofo U., Chukwuma Chime C., Akpomie K.G., Anarado C.J.O., Odewole O.A., Grishina M., Potemkin V., Dehydroacetic Acid-Phenylhydrazone as a Potential Inhibitor for Wild-Type HIV-1 Protease: Structural, DFT, Molecular Dynamics, 3D QSAR and ADMET Characteristics, Iranian Journal of Chemistry and Chemical Engineering, 40: 215-230 (2021).
[14] Zuo K., Qian J., Gong J., Zhang J., Li H., Zhou G., Synthesis, Characterization, Molecular Docking and Cytotoxicity Studies of Bagasse Xylem Ferulate-Acrylamide/Methyl Methacrylate Composite, Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 38: 107-116. (2019).
[15] Liu Z., Liu Q., Zhang B., Liu Q., Fang L., Gou S., Blood–Brain Barrier Permeable and No-Releasing Multifunctional Nanoparticles for Alzheimer’s Disease Treatment: Targeting NO/cGMP/CREB Signaling Pathways. Journal of Medicinal Chemistry, 64(18): 13853-13872 (2021).
[16] Roskoski Jr R., Properties of FDA-Approved Small Molecule Protein Kinase Inhibitors: A 2021 Update. Pharmacological research, 165: 105463 (2021).
[17] Setyawan J., Koide K., Diller T.C., Bunnage M.E., Taylor S.S., Nicolaou K.C., Brunton L.L., Inhibition of Protein Kinases by Balanol: Specificity Within the Serine/Threonine Protein Kinase Subfamily. Molecular pharmacology, 56(2): 370-376 (1999).
[18] Thal D.M., Yeow R.Y., Schoenau C., Huber J., Tesmer J.J.G., Molecular Mechanism of Selectivity among G Protein-Coupled Receptor Kinase 2 Inhibitors, Molecular Pharmacology, 80: 294-303 (2011).
[19] Homan K.T., Larimore K.M., Elkins J.M., Szklarz M., Knapp S., Tesmer J.J., Identification and Structure–Function Analysis of Subfamily Selective G Protein-Coupled Receptor Kinase Inhibitors. ACS chemical biology, 10(1): 310-319 (2015).
[20] Kim S., Chen J., Cheng T., Gindulyte A., He J., He S., Bolton E.E., PubChem in 2021: New Data Content and Improved Web Interfaces. Nucleic acids research, 49(D1): D1388-D1395 (2021).
[21] O'Boyle N.M., Banck M., James C.A., Morley C., Vandermeersch T., Hutchison G.R., Open Babel: An Open Chemical Toolbox. Journal of cheminformatics, 3(1): 1-14 (2011).
[22] Morris G.M., Huey R., Lindstrom W., Sanner M.F., Belew R.K., Goodsell D.S., Olson A.J., AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility. Journal of computational chemistry, 30(16): 2785-2791 (2009).
[23] Baldi P., Nasr R., When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values. Journal of chemical information and modeling, 50(7): 1205-1222 (2010).
[24] Xiong G., Wu Z., Yi J., Fu L., Yang Z., Hsieh C., Cao D., ADMETlab 2.0: an Integrated Online Platform for Accurate and Comprehensive Predictions of ADMET Properties. Nucleic Acids Research, 49(W1): W5-W14 (2021).
[25] Dong J., Wang N.N., Yao Z.J., Zhang L., Cheng Y., Ouyang D., Cao D.S., ADMETlab: a Platform for Systematic ADMET Evaluation Based on a Comprehensively Collected ADMET Database. Journal of cheminformatics, 10: 1-11 (2018).
[26] Azimi S., Mohammadi B., Babadoust S., Vessally E., In Silico Study and Design of Some New Potent Threonine Tyrosine Kinase Inhibitors Using Molecular Docking Simulation. Molecular Simulation, 49(5): 517-524 (2023).