Optimization of Membrane Protein TmrA Purification Procedure Guided by Analytical Ultracentrifugation

Membrane proteins are involved in various cellular processes. However, purification of membrane proteins has long been a challenging task, as membrane protein stability in detergent is the bottleneck for purification and subsequent analyses. Therefore, the optimization of detergent conditions is critical for the preparation of membrane proteins. Here, we utilize analytical ultracentrifugation (AUC) to examine the effects of different detergents (OG, Triton X-100, DDM), detergent concentrations, and detergent supplementation on the behavior of membrane protein TmrA. Our results suggest that DDM is more suitable for the purification of TmrA compared with OG and TritonX-100; a high concentration of DDM yields a more homogeneous protein aggregation state; supplementing TmrA purified with a low DDM concentration with DDM maintains the protein homogeneity and aggregation state, and may serve as a practical and cost-effective strategy for membrane protein purification.

Membrane Protein Stabilization Strategies for Structural and Functional Studies

Accounting for nearly two-thirds of known druggable targets, membrane proteins are highly relevant for cell physiology and pharmacology. In this regard, the structural determination of pharmacologically relevant targets would facilitate the intelligent design of new drugs. The structural biology of membrane proteins is a field experiencing significant growth as a result of the development of new strategies for structure determination. However, membrane protein preparation for structural studies continues to be a limiting step in many cases due to the inherent instability of these molecules in non-native membrane environments. This review describes the approaches that have been developed to improve membrane protein stability. Membrane protein mutagenesis, detergent selection, lipid membrane mimics, antibodies, and ligands are described in this review as approaches to facilitate the production of purified and stable membrane proteins of interest for structural and functional studies.

A day in the life of a biopharmaceutical senior scientist

Dr Jana Broecker is a senior scientist in the Biochemistry Department at Sosei Heptares in the UK, where she is part of a team that develops small-molecule therapeutics using protein structural information. Jana graduated as a Diploma Engineer from the Technical University Berlin (Germany) and did her PhD with the University of Kaiserslautern on the biophysical quantification of membrane-protein stability. She also completed post-doctoral research at the University of Toronto (Canada), where she spearheaded the optimization of membrane-protein crystallization using polymer-bound lipid nanodiscs and where she also developed a method that avoids crystal harvesting.

An improved fluorescent tag and its nanobodies for membrane protein expression, stability assay, and purification

Green fluorescent proteins (GFPs) are widely used to monitor membrane protein expression, purification, and stability. An ideal reporter should be stable itself and provide high sensitivity and yield. Here, we demonstrate that a coral (Galaxea fascicularis) thermostable GFP (TGP) is by such reasons an improved tag compared to the conventional jellyfish GFPs. TGP faithfully reports membrane protein stability at temperatures near 90 °C (20-min heating). By contrast, the limit for the two popular GFPs is 64 °C and 74 °C. Replacing GFPs with TGP increases yield for all four test membrane proteins in four expression systems. To establish TGP as an affinity tag for membrane protein purification, several high-affinity synthetic nanobodies (sybodies), including a non-competing pair, are generated, and the crystal structure of one complex is solved. Given these advantages, we anticipate that TGP becomes a widely used tool for membrane protein structural studies.

IMPROvER: the Integral Membrane Protein Stability Selector

Identifying stabilising variants of membrane protein targets is often required for structure determination. Our new computational pipeline, the Integral Membrane Protein Stability Selector (IMPROvER) provides a rational approach to variant selection by employing three independent approaches: deep-sequence, model-based and data-driven. In silico tests using known stability data, and in vitro tests using three membrane protein targets with 7, 11 and 16 transmembrane helices provided measures of success. In vitro, individual approaches alone all identified stabilising variants at a rate better than expected by random selection. Low numbers of overlapping predictions between approaches meant a greater success rate was achieved (fourfold better than random) when approaches were combined and selections restricted to the highest ranked sites. The mix of information IMPROvER uses can be extracted for any helical membrane protein. We have developed the first general-purpose tool for selecting stabilising variants of $$\upalpha$$ α -helical membrane proteins, increasing efficiency and reducing workload. IMPROvER can be accessed at http://improver.ddns.net/IMPROvER/.

mCSM-membrane: predicting the effects of mutations on transmembrane proteins

Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects of mutations in membrane proteins. To fill this gap, here we report, mCSM-membrane, a user-friendly web server that can be used to analyse the impacts of mutations on membrane protein stability and the likelihood of them being disease associated. mCSM-membrane derives from our well-established mutation modelling approach that uses graph-based signatures to model protein geometry and physicochemical properties for supervised learning. Our stability predictor achieved correlations of up to 0.72 and 0.67 (on cross validation and blind tests, respectively), while our pathogenicity predictor achieved a Matthew's Correlation Coefficient (MCC) of up to 0.77 and 0.73, outperforming previously described methods in both predicting changes in stability and in identifying pathogenic variants. mCSM-membrane will be an invaluable and dedicated resource for investigating the effects of single-point mutations on membrane proteins through a freely available, user friendly web server at http://biosig.unimelb.edu.au/mcsm_membrane.