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Abstract
Sigma receptors are a fascinating receptor protein class whose ligands are actually under clinical evaluation for the modulation of opioid analgesia and their use as positron emission tomography radiotracers. In particular, peculiar biological and therapeutic functions are associated with the sigma-2 (σ2) receptor. The σ2 receptor ligands determine tumor cell death through apoptotic and non-apoptotic pathways, and the overexpression of σ2 receptors in several tumor cell lines has been well documented, with significantly higher levels in proliferating tumor cells compared to quiescent ones. This acknowledged feature has found practical application in the development of cancer cell tracers and for ligand-targeting therapy. In this context, the development of new ligands that target the σ2 receptors is beneficial for those diseases in which this protein is involved. In this paper, we conducted a search of new potential σ2 receptor ligands among a database of 1517 “small” marine natural products constructed by the union of the Seaweed Metabolite and the Chemical Entities of Biological Interest (ChEBI) Databases. The structures were passed through two filters that were constituted by our developed two-dimensional (2D) and three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) statistical models, and successively docked upon a σ2 receptor homology model that we built according to the FASTA sequence of the σ2/TMEM97 (SGMR2_HUMAN) receptor.
Highlights
Sigma (σ) receptors include a particular pharmacologically defined family of membrane-bound receptors that bind compounds belonging to a variety of structural classes
CORAL allows for a hybrid representation of molecular structures that includes a simplified molecular input line entry system (SMILES) and a molecular graph
The aromatic rings were converted into the kekulé forms. These conversions have been performed in order to generate SMILES with the same depiction as those used for building the hybrid σ2 receptor affinity filter, since this model works by chopping the SMILES or the molecular graphs into small fragments, and iteratively overmatching them with the SMILES and molecular graphs fragments that compose the training set [30,31]
Summary
Sigma (σ) receptors include a particular pharmacologically defined family of membrane-bound receptors that bind compounds belonging to a variety of structural classes. Discovered in 1976 and recognized in two distinct subtypes in the early 1990s, they represent a potential target for the diagnosis and therapy of cancer and central nervous system (CNS) diseases [1,2]. Both σ receptor subtypes are highly expressed in several tissues and distinguished from each other through their affinity for different ligands and biological profiles.
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