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Bias-force guided simulations combined with experimental validations towards GPR17 modulators identification

Sana KariMolecular Signaling Group, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O.Box 553, 33101 Tampere, FinlandAkshaya MurugesanMolecular Signaling Group, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O.Box 553, 33101 Tampere, FinlandRamesh ThiyagarajanDepartment of Basic Medical Sciences, College of Medicine, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Kingdom of Saudi ArabiaSrivatsan KidambiDepartment of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, 820 N 16th Street, 207 Othmer Hall, NE 68588, USAJamoliddin RazzokovInstitute of Fundamental and Applied Research, National Research University TIIAME, Kori Niyoziy 39, 100000 Tashkent, Uzbekistan; College of Engineering, Akfa University, Milliy Bog Street 264, 111221 Tashkent, Uzbekistan; Institute of Material Sciences, Academy of Sciences, Chingiz Aytmatov 2b, 100084 Tashkent, Uzbekistan; Department of Physics, National University of Uzbekistan, Universitet 4, 100174 Tashkent, Uzbekistan; Laboratory of Experimental Biophysics, Centre for Advanced Technologies, Universitet 7, 100174 Tashkent, UzbekistanChandrabose SelvarajDepartment of Biotechnology, Division of Research and Innovation, Saveetha School of Engineering, SIMATS, Chennai 602105, Tamil Nadu, IndiaMeenakshisundaram KandhaveluMolecular Signaling Group, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O.Box 553, 33101 Tampere, Finland. Electronic address: [email protected]Parthiban MarimuthuPharmaceutical Science Laboratory (PSL - Pharmacy) and Structural Bioinformatics Laboratory (SBL - Biochemistry), Faculty of Science and Engineering, Åbo Akademi University, FI-20520 Turku, Finland. Electronic address: [email protected]
ABI

Аннотация

Glioblastoma Multiforme (GBM) is known to be by far the most aggressive brain tumor to affect adults. The median survival rate of GBM patient’s is < 15 months, while the GBM cells aggressively develop resistance to chemo- and radiotherapy with their self-renewal capacity which suggests the pressing need to develop novel preventative measures. We have recently proved that GPR17 —an orphan G protein-coupled receptor— is highly expressed on the GBM cell surface and it has a vital role to play in the disease progression. Despite the progress made on GBM downregulation, there still remain difficulties in developing a promising modulator for GPR17, till date. Here, we have performed robust virtual screening combined with biased-force pulling molecular dynamic (MD) simulations to predict high-affinity GPR17 modulators followed by experimental validation. Initially, the database containing 1379 FDA-approved drugs were screened against the orthosteric binding pocket of the GPR17. The external bias-potentials were then applied to the screened hits during the MD simulations which enabled to predict a spectrum of rupture peak force values that were used to select four approved drugs –ZINC000003792417 (Sacubitril), ZINC000014210457 (Victrelis), ZINC000001536109 (Pralatrexate) and ZINC000003925861 (Vorapaxar)– as top hits. The hits selected turns out to demonstrate unique dissociation pathways, interaction pattern, and change in polar network over time. Subsequently the selected hits with GPR17 were measured by inhibiting the forskolin-stimulated cAMP accumulation in GBM cell lines, LN229 and SNB19. The ex vivo validations shows that Sacubitril drug can act as a full agonist, while Vorapaxar functions as a partial agonist for GPR17. The pEC50 of Sacubitril was identified as 4.841 and 4.661 for LN229 and SNB19, respectively. Small interference of the RNA (siRNA)– silenced the GPR17 to further validate the targeted binding of Sacubitril with GPR17. In the current investigation, we have identified new repurposable GPR17 specific drugs which are likely to increase the opportunity to treat orphan deadly diseases.

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