QSAR-Based Computational Approaches to Accelerate the Discovery of Sigma-2 Receptor (S2R) Ligands as Therapeutic Drugs.

Yangxi Yu,Hiep Dong,William J Welsh,Youyi Peng

doi:10.3390/molecules26175270

Yangxi Yu, Hiep Dong + Show 2 more

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https://doi.org/10.3390/molecules26175270

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Abstract

S2R overexpression is associated with various forms of cancer as well as both neuropsychiatric disorders (e.g., schizophrenia) and neurodegenerative diseases (Alzheimer’s disease: AD). In the present study, three ligand-based methods (QSAR modeling, pharmacophore mapping, and shape-based screening) were implemented to select putative S2R ligands from the DrugBank library comprising 2000+ entries. Four separate optimization algorithms (i.e., stepwise regression, Lasso, genetic algorithm (GA), and a customized extension of GA called GreedGene) were adapted to select descriptors for the QSAR models. The subsequent biological evaluation of selected compounds revealed that three FDA-approved drugs for unrelated therapeutic indications exhibited sub-1 uM binding affinity for S2R. In particular, the antidepressant drug nefazodone elicited a S2R binding affinity Ki = 140 nM. A total of 159 unique S2R ligands were retrieved from 16 publications for model building, validation, and testing. To our best knowledge, the present report represents the first case to develop comprehensive QSAR models sourced by pooling and curating a large assemblage of structurally diverse S2R ligands, which should prove useful for identifying new drug leads and predicting their S2R binding affinity prior to the resource-demanding tasks of chemical synthesis and biological evaluation.

Highlights

The Sigma receptors (SRs), originally considered as members of the opioid receptor family [1], were recognized as a separate group in 1982 [2]
The analgesic effects associated with modulation of Sigma-1 receptor (S1R) have been recognized [4], and more recent in vivo studies in rat models have demonstrated that S1R antagonists can potentiate opioid analgesia with fewer and less severe adverse effects such as drug tolerance [5]
The 2D-QSAR and ligand-based pharmacophore models were constructed with different Ki datasets with overlap of some structures

Summary

Introduction

The Sigma receptors (SRs), originally considered as members of the opioid receptor family [1], were recognized as a separate group in 1982 [2]. In 2017, S2R was first reported as the translation of the transmembrane protein 97 gene (TMEM97) [8]. This conjecture was refuted in 2019, as knockout studies on TMEM97 and/or PGRMC1 demonstrated no effect on the EC50 of S2R ligands, suggesting that the cytotoxic effects of S2R ligands are not mediated by TMEM97 or PGRMC1 [9]. Unlike S1R, for which the human X-ray crystal structure is available (PDB ID: 5HK1), the crystal structure of S2R for any species remains unavailable

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