Jabeen Amara, Vijayram Ramya, Ranganathan Shoba
Department of Molecular Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamilnadu, India.
Curr Res Struct Biol. 2020 Oct 9;2:213-221. doi: 10.1016/j.crstbi.2020.10.001. eCollection 2020.
Olfactory receptor (OR) 1A2 is the member of largest superfamily of G protein-coupled receptors (GPCRs). OR1A2 is an ectopically expressed receptor with only 13 known ligands, implicated in reducing hepatocellular carcinoma progression, with enormous therapeutic potential. We have developed a two-stage screening approach to identify novel putative ligands of OR1A2. We first used a pharmacophore model based on atomic property field (APF) to virtually screen a library of 5942 human metabolites. We then carried out structure-based virtual screening (SBVS) for predicting the potential agonists, based on a 3D homology model of OR1A2. This model was developed using a biophysical approach for template selection, based on multiple parameters including hydrophobicity correspondence, applied to the complete set of available GPCR structures to pick the most appropriate template. Finally, the membrane-embedded 3D model was refined by molecular dynamics (MD) simulations in both the and forms. The refined model in the form was selected for SBVS. Four novel small molecules were identified as strong binders to this olfactory receptor on the basis of computed binding energies.
嗅觉受体（OR）1A2是G蛋白偶联受体（GPCR）最大超家族的成员。OR1A2是一种异位表达的受体，仅有13种已知配体，与降低肝细胞癌进展有关，具有巨大的治疗潜力。我们开发了一种两阶段筛选方法来鉴定OR1A2的新型假定配体。我们首先使用基于原子性质场（APF）的药效团模型对5942种人类代谢物库进行虚拟筛选。然后，基于OR1A2的三维同源模型进行基于结构的虚拟筛选（SBVS）以预测潜在激动剂。该模型是使用生物物理方法进行模板选择开发的，基于包括疏水性对应在内的多个参数，应用于整套可用的GPCR结构以选择最合适的模板。最后，通过分子动力学（MD）模拟在α和β形式下对膜嵌入的三维模型进行优化。选择α形式的优化模型进行SBVS。基于计算出的结合能，鉴定出四种新型小分子为该嗅觉受体的强结合剂。
