GPR17, a previously orphan receptor responding to both uracil nucleotides and cysteinyl-leukotrienes, has been proposed as a novel promising target for human neurodegenerative diseases. Here, in order to specifically identify novel potent ligands of GPR17, we first modeled in silico the receptor by using a multiple template approach, in which extracellular loops of the receptor, quite complex to treat, were modeled making reference to the most similar parts of all the class-A GPCRs crystallized so far. A high-throughput virtual screening exploration of GPR17 binding site with more than 130,000 lead-like compounds was then applied, followed by the wet functional and pharmacological validation of the top-scoring chemical structures. This approach revealed successful for the proposed aim, and allowed us to identify five agonists or partial agonists with very diverse chemical structure. None of these compounds could have been expected 'a priori' to act on a GPCR, and all of them behaved as much more potent ligands than GPR17 endogenous activators.

In silico identification of new ligands for GPR17 : a promising therapeutic target for neurodegenerative diseases / I. Eberini, S. Daniele, C. Parravicini, C. Sensi, M.L. Trincavelli, C. Martini, M.P. Abbracchio. - In: JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN. - ISSN 0920-654X. - 25:8(2011 Aug), pp. 743-752. [10.1007/s10822-011-9455-8]

In silico identification of new ligands for GPR17 : a promising therapeutic target for neurodegenerative diseases

I. Eberini
Primo
;
C. Parravicini;C. Sensi;M.P. Abbracchio
Ultimo
2011

Abstract

GPR17, a previously orphan receptor responding to both uracil nucleotides and cysteinyl-leukotrienes, has been proposed as a novel promising target for human neurodegenerative diseases. Here, in order to specifically identify novel potent ligands of GPR17, we first modeled in silico the receptor by using a multiple template approach, in which extracellular loops of the receptor, quite complex to treat, were modeled making reference to the most similar parts of all the class-A GPCRs crystallized so far. A high-throughput virtual screening exploration of GPR17 binding site with more than 130,000 lead-like compounds was then applied, followed by the wet functional and pharmacological validation of the top-scoring chemical structures. This approach revealed successful for the proposed aim, and allowed us to identify five agonists or partial agonists with very diverse chemical structure. None of these compounds could have been expected 'a priori' to act on a GPCR, and all of them behaved as much more potent ligands than GPR17 endogenous activators.
Computational biology; Drug discovery; High throughput screening; Molecular modeling; Pharmacology
Settore BIO/14 - Farmacologia
ago-2011
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/166296
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