Molecular Dynamics simulations to understand the mechanism of biased agonism at a G protein coupled receptor

G蛋白偶联受体（GPCR）是高度动态的蛋白质，其在信号传导中显示复杂的行为模式，例如，相同的GPCR可以偶联到细胞中的多个信号传导途径，而作用于相同GPCR的不同配体可以导致不同的信号传导输出（配体偏好）。这对制药工业特别有意义，因为它可以导致开发具有增强的治疗功效和较少的不良反应的新药。也许令人惊讶的是，计算建模的基本概念，如配体偏见在GPCR是不先进的。Eamonn Kelly教授详细研究了阿片受体（MOPr）与配体的相互作用以及MOPr的分子信号传导，MOPr是一种非常重要的GPCR，对哺乳动物的疼痛和奖赏通路至关重要。Eamonn Kelly教授在该受体的配体偏好方面也有丰富的经验。Richard Sessions博士是一位经验丰富的蛋白质建模师，包括使用MD来建模膜蛋白。他们一起希望了解μ阿片受体的配体偏倚的分子基础，使用计算机建模和受体细胞信号传导的测量相结合。基于已发表的μ阿片受体和相关GPCR的晶体结构，学生将构建MD的μ阿片受体模型，使用这些模拟来：确定偏向/非偏向配体与MOPr结合口袋的相互作用的性质，以及由偏向和非偏向配体诱导/稳定的受体构象变化，以产生活性，可能不同的受体构象使用MD模型筛选其他配体来预测偏倚/此外，学生将通过在哺乳动物中表达μ阿片受体和相关突变体来测试和确认这些建模结果。细胞系，并确定在该受体上的偏向配体的结合和信号传导。

G protein-coupled receptors (GPCRs) are highly dynamic proteins that display complex patterns of behaviour in signalling, for example the same GPCR can couple to multiple signalling pathways in a cell, whilst different ligands acting at the same GPCR can lead to distinct signalling outputs (ligand bias). This is of particular interest to the pharmaceutical industry as it can lead to the development of novel drugs with enhanced therapeutic efficacy and fewer adverse effects. Perhaps surprisingly, the computational modelling of fundamental concepts such as ligand bias at GPCRs is not well advanced. The aim of this project therefore is to use Molecular dynamics simulations (MDs) as a tool to understand ligand bias at a biologically important GPCR.Prof Eamonn Kelly has made detailed studies of ligand interaction with, and molecular signalling of, the opioid receptor (MOPr), an extremely important GPCR which is crucial for pain and reward pathways in mammals. Prof Eamonn Kelly also has wide experience of ligand bias at this receptor. Dr Richard Sessions is a highly experienced protein modeller, including the use of MDs to model membrane proteins. Together they wish to understand the molecular basis of ligand bias at the mu opioid receptor, using a combination of computer modelling and measures of receptor cell signalling. Based upon the published crystal structure of the mu opioid receptor and related GPCRs, the student would build a model of the mu opioid receptor for MDs, using these simulations to:Determine the nature of the interaction of biased/unbiased ligands with the MOPr binding pocket, as well as receptor conformational changes induced/stabilised by biased and unbiased ligands to produce active, presumably distinct receptor conformationsUse the MD models to screen other ligands to predict biased/unbiased ligand phenotype and predict the effect of mutationsFurthermore the student will test and confirm these modelling outcomes by expressing mu opioid receptor and relevant mutants in mammalian cell lines and determining the binding and signalling of biased ligands at this receptor.