Membrane preparation and solubilization

The effect of polymer end-group on the formation of styrene - maleic acid lipid particles (SMALPs)

A series of block copolymers comprising styrene and maleic acid (SMA) has been prepared using RAFT polymerisation. RAFT often results in a large hydrophobic alkylthiocarbonylthio end group and this work examines its effect on the solution behaviour of the copolymers. SMA variants with, and without, this end group were synthesised and their behaviour compared with a commercially-available random copolymer of similar molecular weight. Dynamic light scattering and surface tension measurements found the RAFT-copolymers preferentially self-assembled into higher-order aggregates in aqueous solution. Small angle neutron scattering using deuterated styrene varients add support to the accepted model that these agreggates comprise a solvent-protected styrenic core with an acid-rich shell. Replacing the hydrophobic RAFT end group with a more hydrophilic nitrile caused differences in the resulting surface activity, attributed to the ability of the adjoining styrene homoblock to drive aggregation. Each of the copolymers formed SMALP nanodiscs with DMPC lipids, which were found to encapsulate a model membrane protein, gramicidin. However, end group variation affected solubilisition of DPPC, a lipid with a higher phase transition temperature. When using RAFT-copolymers terminated with a hydrophobic group, swelling of the bilayer and greater penetration of the homoblock into the nanodisc core occurred with increasing homoblock length. Conversely, commercial and nitrile-terminated RAFT-copolymers produced nanodisc sizes that stayed constant, instead indicating interaction at the edge of the lipid patch. The results highlight how even minor changes to the copolymer can modify the amphiphilic balance between regions, knowledge useful towards optimising copolymer structure to enhance and control nanodisc formation.

Analytical Ultracentrifugation as a Matrix-Free Probe for the Study of Kinase Related Cellular and Bacterial Membrane Proteins and Glycans

Analytical ultracentrifugation is a versatile approach for analysing the molecular mass, molecular integrity (degradation/aggregation), oligomeric state and association/dissociation constants for self-association, and assay of ligand binding of kinase related membrane proteins and glycans. It has the great property of being matrix free-providing separation and analysis of macromolecular species without the need of a separation matrix or membrane or immobilisation onto a surface. This short review-designed for the non-hydrodynamic expert-examines the potential of modern sedimentation velocity and sedimentation equilibrium and the challenges posed for these molecules particularly those which have significant cytoplasmic or extracellular domains in addition to the transmembrane region. These different regions can generate different optimal requirements in terms of choice of the appropriate solvent (aqueous/detergent). We compare how analytical ultracentrifugation has contributed to our understanding of two kinase related cellular or bacterial protein/glycan systems (i) the membrane erythrocyte band 3 protein system-studied in aqueous and detergent based solvent systems-and (ii) what it has contributed so far to our understanding of the enterococcal VanS, the glycan ligand vancomycin and interactions of vancomycin with mucins from the gastrointestinal tract.

Effect of Detergents and Osmolytes on Thermal Stability of Native and Mutant Rhodobacter sphaeroides Reaction Centers

Photosynthetic reaction center (RC) of the purple bacterium Rhodobacter sphaeroides is one of the most well-studied transmembrane pigment-protein complexes. It is a relatively stable protein with established conditions for its isolation from membranes, purification, and storage. However, it has been shown that some amino acid substitutions can affect stability of the RC, which results in a decrease of the RCs yield during its isolation and purification, disturbs spectral properties of the RCs during storage, and can lead to sample heterogeneity. To optimize conditions for studying mutant RCs, the effect of various detergents and osmolytes on thermal stability of the complex was examined. It was shown that trehalose and, to a lesser extent, sucrose, maltose, and hydroxyectoin at 1 M concentration slow down thermal denaturation of RCs. Sodium cholate was found to have significant stabilizing effect on the structure of native and genetically modified RCs. The use of sodium cholate as a detergent has several advantages and can be recommended for the storage and investigation of the unstable mutant membrane complexes of purple bacteria in long-term experiments.

TMP- SSurface2: A Novel Deep Learning-Based Surface Accessibility Predictor for Transmembrane Protein Sequence

Transmembrane protein (TMP) is an important type of membrane protein that is involved in various biological membranes related biological processes. As major drug targets, TMPs’ surfaces are highly concerned to form the structural biases of their material-bindings for drugs or other biological molecules. However, the quantity of determinate TMP structures is still far less than the requirements, while artificial intelligence technologies provide a promising approach to accurately identify the TMP surfaces, merely depending on their sequences without any feature-engineering. For this purpose, we present an updated TMP surface residue predictor TMP-SSurface2 which achieved an even higher prediction accuracy compared to our previous version. The method uses an attention-enhanced Bidirectional Long Short Term Memory (BiLSTM) network, benefiting from its efficient learning capability, some useful latent information is abstracted from protein sequences, thus improving the Pearson correlation coefficients (CC) value performance of the old version from 0.58 to 0.66 on an independent test dataset. The results demonstrate that TMP-SSurface2 is efficient in predicting the surface of transmembrane proteins, representing new progress in transmembrane protein structure modeling based on primary sequences. TMP-SSurface2 is freely accessible at https://github.com/NENUBioCompute/TMP-SSurface-2.0.

TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-Helical Transmembrane Proteins

Alpha transmembrane proteins (αTMPs) profoundly affect many critical biological processes and are major drug targets due to their pivotal protein functions. At present, even though the non-transmembrane secondary structures are highly relevant to the biological functions of αTMPs along with their transmembrane structures, they have not been unified to be studied yet. In this study, we present a novel computational method, TMPSS, to predict the secondary structures in non-transmembrane parts and the topology structures in transmembrane parts of αTMPs. TMPSS applied a Convolutional Neural Network (CNN), combined with an attention-enhanced Bidirectional Long Short-Term Memory (BiLSTM) network, to extract the local contexts and long-distance interdependencies from primary sequences. In addition, a multi-task learning strategy was used to predict the secondary structures and the transmembrane helixes. TMPSS was thoroughly trained and tested against a non-redundant independent dataset, where the Q3 secondary structure prediction accuracy achieved 78% in the non-transmembrane region, and the accuracy of the transmembrane region prediction achieved 90%. In sum, our method showcased a unified model for predicting the secondary structure and topology structure of αTMPs by only utilizing features generated from primary sequences and provided a steady and fast prediction, which promisingly improves the structural studies on αTMPs.

Detergent Desorption of Membrane Proteins Exhibits Two Kinetic Phases

Gradual dissociation of detergent molecules from water-insoluble membrane proteins culminates in protein aggregation. However, the time-dependent trajectory of this process remains ambiguous because the signal-to-noise ratio of most spectroscopic and calorimetric techniques is drastically declined by the presence of protein aggregates in solution. We show that by using steady-state fluorescence polarization (FP) spectroscopy the dissociation of the protein-detergent complex (PDC) can be inspected in real time at detergent concentrations below the critical micelle concentration. This article provides experimental evidence of the coexistence of two distinct phases of the dissociations of detergent monomers from membrane proteins. We first noted a slow detergent predesolvation process, which was accompanied by a relatively modest change in the FP anisotropy, suggesting a small number of dissociated detergent monomers from the proteomicelles. This predesolvation phase was followed by a fast detergent desolvation process, which was highlighted by a major alteration in the FP anisotropy. The durations and rates of these phases were dependent on both the detergent concentration and the interfacial PDC interactions. Further development of this approach might lead to the creation of a new semiquantitative method for the assessment of the kinetics of association and dissociation of proteomicelles.

X-Ray Crystallographic Studies for Revealing Binding Sites of General Anesthetics in Pentameric Ligand-Gated Ion Channels

X-ray crystallography is a powerful tool in structural biology and can offer insight into structured-based understanding of general anesthetic action on various relevant molecular targets, including pentameric ligand-gated ion channels (pLGICs). In this chapter, we outline the procedures for expression and purification of pLGICs. Optimization of crystallization conditions, especially to achieve high-resolution structures of pLGICs bound with general anesthetics, is also presented. Case studies of pLGICs bound with the volatile general anesthetic isoflurane, 2-bromoethanol, and the intravenous general anesthetic ketamine are revisited.

Quantification of Membrane Protein-Detergent Complex Interactions

Although fundamentally significant in structural, chemical, and membrane biology, the interfacial protein-detergent complex (PDC) interactions have been modestly examined because of the complicated behavior of both detergents and membrane proteins in aqueous phase. Membrane proteins are prone to unproductive aggregation resulting from poor detergent solvation, but the participating forces in this phenomenon remain ambiguous. Here, we show that using rational membrane protein design, targeted chemical modification, and steady-state fluorescence polarization spectroscopy, the detergent desolvation of membrane proteins can be quantitatively evaluated. We demonstrate that depleting the detergent in the sample well produced a two-state transition of membrane proteins between a fully detergent-solvated state and a detergent-desolvated state, the nature of which depended on the interfacial PDC interactions. Using a panel of six membrane proteins of varying hydrophobic topography, structural fingerprint, and charge distribution on the solvent-accessible surface, we provide direct experimental evidence for the contributions of the electrostatic and hydrophobic interactions to the protein solvation properties. Moreover, all-atom molecular dynamics simulations report the major contribution of the hydrophobic forces exerted at the PDC interface. This semiquantitative approach might be extended in the future to include studies of the interfacial PDC interactions of other challenging membrane protein systems of unknown structure. This would have practical importance in protein extraction, solubilization, stabilization, and crystallization.

Navigating Membrane Protein Structure, Dynamics, and Energy Landscapes Using Spin Labeling and EPR Spectroscopy

A detailed understanding of the functional mechanism of a protein entails the characterization of its energy landscape. Achieving this ambitious goal requires the integration of multiple approaches including determination of high-resolution crystal structures, uncovering conformational sampling under distinct biochemical conditions, characterizing the kinetics and thermodynamics of transitions between functional intermediates using spectroscopic techniques, and interpreting and harmonizing the data into novel computational models. With increasing sophistication in solution-based and ensemble-oriented biophysical approaches such as electron paramagnetic resonance (EPR) spectroscopy, atomic resolution structural information can be directly linked to conformational sampling in solution. Here, we detail how recent methodological and technological advances in EPR spectroscopy have contributed to the elucidation of membrane protein mechanisms. Furthermore, we aim to assist investigators interested in pursuing EPR studies by providing an introduction to the technique, a primer on experimental design, and a description of the practical considerations of the method toward generating high quality data.