Cell-Free Co-Translational Approaches for Producing Mammalian Receptors: Expanding the Cell-Free Expression Toolbox Using Nanolipoproteins - Shelby, Megan L.; He, Wei; Dang, Amanda T.; Kuhl, Tonya L.; Coleman, Matthew A. (Frontiers in Pharmacology, 2019)
Membranes proteins make up more than 60% of current drug targets and account for approximately 30% or more of the cellular proteome. Access to this important class of proteins has been difficult due to their insolubility and tendency to aggregate in aqueous solutions. Understanding membrane protein structure and function demands novel means of membrane protein production that preserve their native conformational state. Over the last decade cell-free expression systems have emerged as an important complement to cell-based expression of membrane proteins due to their simple and customizable experimental parameters. One approach to overcome the solubility and stability limitations of purified membrane proteins is to support them in stable, native like states within nanolipoprotein particles (NLPs), aka nanodiscs. This has become common practice to facilitate biochemical and biophysical characterization of proteins of interest. NLP technology can be easily coupled with cell-free systems to achieve functional membrane protein production for this purpose. Our approach involves utilizing cell-free expression systems in the presence of NLPs or using co-translation techniques to perform one-pot expression and self-assembly of membrane protein/NLP complexes. We describe how cell-free reactions can be modified to render control over nanoparticle size and monodispersity in support of membrane protein production. These modifications have been exploited to facilitate co-expression of full-length functional membrane proteins such as G-protein coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs). In particular, we summarize the state of the art in NLP assisted cell-free co-expression of these important classes of membrane proteins as well as evaluate the advances in and prospects for this technology that will drive drug discovery against these targets.