Dataset Information

Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening.

ABSTRACT: Morphine, oxycodone, fentanyl, and other µ-opioid receptors (MOR) agonists have been used for decades in antinociceptive therapies. However, these drugs are associated with numerous side effects, such as euphoria, addiction, respiratory depression, and adverse gastrointestinal reactions, thus, circumventing these drawbacks is of extensive importance. With the aim of identifying novel peptide ligands endowed with MOR inhibitory activity, we developed a virtual screening protocol, including receptor-based pharmacophore screening, docking studies, and molecular dynamics simulations, which was used to filter an in-house built virtual library of tetrapeptide ligands. The three top-scored compounds were synthesized and subjected to biological evaluation, revealing the identity of a hit compound (peptide 1) endowed with appreciable MOR inverse agonist effect and selectivity over ?-opioid receptors. These results confirmed the reliability of our computational approach and provided a promising starting point for the development of new potent MOR modulators.

SUBMITTER: Poli G

PROVIDER: S-EPMC6865014 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening.

Poli Giulio G Dimmito Marilisa Pia MP Mollica Adriano A Zengin Gokhan G Benyhe Sandor S Zador Ferenc F Stefanucci Azzurra A

Molecules (Basel, Switzerland) 20191027 21

Morphine, oxycodone, fentanyl, and other µ-opioid receptors (MOR) agonists have been used for decades in antinociceptive therapies. However, these drugs are associated with numerous side effects, such as euphoria, addiction, respiratory depression, and adverse gastrointestinal reactions, thus, circumventing these drawbacks is of extensive importance. With the aim of identifying novel peptide ligands endowed with MOR inhibitory activity, we developed a virtual screening protocol, including recept ...[more]

PMID: 31717871

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Project description:Transforming growth factor-beta (TGF-β), a member of the TGF-β cytokine superfamily, is known to bind to sulfated glycosaminoglycans (GAGs), but the nature of this interaction remains unclear. In a recent study, we found that preterm human milk TGF-β2 is sequestered by chondroitin sulfate (CS) in its proteoglycan form. To understand the molecular basis of the TGF-β2-CS interaction, we utilized the computational combinatorial virtual library screening (CVLS) approach in tandem with molecular dynamics (MD) simulations. All possible CS oligosaccharides were generated in a combinatorial manner to give 24 di- (CS02), 192 tetra- (CS04), and 1536 hexa- (CS06) saccharides. This library of 1752 CS oligosaccharides was first screened against TGF-β2 using the dual filter CVLS algorithm in which the GOLDScore and root-mean-square-difference (RMSD) between the best bound poses were used as surrogate markers for in silico affinity and in silico specificity. CVLS predicted that both the chain length and level of sulfation are critical for the high affinity and high specificity recognition of TGF-β2. Interestingly, CVLS led to identification of two distinct sites of GAG binding on TGF-β2. CVLS also deduced the preferred composition of the high specificity hexasaccharides, which were further assessed in all-atom explicit solvent MD simulations. The MD results confirmed that both sites of binding form stable GAG-protein complexes. More specifically, the highly selective CS chains were found to engage the TGF-β2 monomer with high affinity. Overall, this work present key principles of recognition with regard to the TGF-β2-CS system. In the process, it led to the generation of the in silico library of all possible CS oligosaccharides, which can be used for advanced studies on other protein-CS systems. Finally, the study led to the identification of unique CS sequences that are predicted to selectively recognize TGF-β2 and may out-compete common natural CS biopolymers.

Project description:Background and purposeMorphine activates the µ-opioid receptor without causing its rapid endocytosis. In contrast, full agonists such as [d-Ala(2) -MePhe(4) -Gly-ol]enkephalin (DAMGO) or etonitazene stimulate a rapid and profound internalization. However, the detailed molecular events underlying the differential regulation of receptor trafficking by distinct opioid agonists remain incompletely understood.Experimental approachHere, we have generated phosphosite-specific antibodies for the carboxyl-terminal residues serine 363 (Ser363), threonine 370 (Thr370) and serine 375 (Ser375), which enabled us to selectively detect either the Ser363-, Thr370- or Ser375-phosphorylated form of the receptor.Key resultsWe showed that agonist-induced phosphorylation occurs at Thr370 and Ser375, whereas Ser363 is constitutively phosphorylated in the absence of agonist. We further demonstated that DAMGO and etonitazene stimulated the phosphorylation of both Thr370 and Ser375. In contrast, morphine promoted the phosphorylation of Ser375, but failed to stimulate Thr370 phosphorylation. In the presence of DAMGO, Ser375 phosphorylation occurred at a faster rate than phosphorylation of Thr370, indicating that Ser375 is the primary site of agonist-dependent phosphorylation. Activation of PKC by phorbol 12-myristate 13-acetate increased receptor phosphorylation only on Thr370, but not on Ser375, indicating that Thr370 can also undergo heterologous PKC-mediated phosphorylation. We also showed that µ receptor dephosphorylation can occur within minutes at or near the plasma membrane, and that agonist removal is a major prerequisite for Thr370 and Ser375 dephosphorylation.Conclusions and implicationsTogether, we showed for the first time that distinct agonists stimulate site-specific patterns of phosphorylation, which are intimately related to their ability to elicit µ-opioid receptor sequestration.Linked articleThis article is commented on by Kelly, pp. 294-297 of this issue. To view this commentary visit http://dx.doi.org/10.1111/j.1476-5381.2011.01387.x.

Dataset Information

Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening.

Publications

Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening.

Similar Datasets

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