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Pharmacophore and docking-based sequential virtual screening for the identification of novel Sigma 1 receptor ligands

Sigma 1 receptor (σ1), a small transmembrane protein expressed in most human cells participates in modulating the function of other membrane proteins such as G protein coupled receptors and ion channels. Several ligands targeting this receptor are currently in clinical trials for the treatment of Al...

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Detalles Bibliográficos
Autores principales: Alamri, Mubarak A, Alamri, Mohammed A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822515/
https://www.ncbi.nlm.nih.gov/pubmed/31719769
http://dx.doi.org/10.6026/97320630015586
Descripción
Sumario:Sigma 1 receptor (σ1), a small transmembrane protein expressed in most human cells participates in modulating the function of other membrane proteins such as G protein coupled receptors and ion channels. Several ligands targeting this receptor are currently in clinical trials for the treatment of Alzheimer's disease, ischemic stroke and neuro-pathic pain. Hence, this receptor has emerged as an attractive target for the treatment of neuro-pathological diseases with unmet medical needs. It is of interest to identify and characterise novelσ1 receptor ligands with different chemical scaffolds using computer-aided drug designing approach. In this work, a GPCR-focused chemical library consisting of 8543 compounds was screened by pharmacophore and docking-based virtual screening methods using LigandScout 4.3 and Autodock Vina 1.1.2 in PyRx 0.8, respectively. The pharmacophore model was constructed based on the interactions of a selective agonist and another antagonist ligand with high binding affinity to the human σ1receptors. Candidate compounds were filtered sequentially by pharmacophore-fit scores, docking energy scores, drug-likeness filters and ADMET properties. The binding mode and pharmacophore mapping of candidate compounds were analysed by Autodock Vina 1.1.2 and LigandScout 4.3 programs, respectively. A pharmacophore model composed of three hydrophobic and positive ionizable features with recognized geometry was built and used as a 3D query for screening a GPCR-focused chemical library by LigandScout 4.3 program. Among the screened 8543 compounds, 159 candidate compounds were obtained from pharmacophore-based screening. 45 compounds among them bound to σ 1receptor with high binding-affinity scores in comparison to the co-crystallized ligand. Amongst these, top five candidate compounds with excellent druglikeness and ADMET properties were selected. These five candidate compounds may act as potential σ1 receptor ligands.