Structural dynamics and thermostabilization of neurotensin receptor 1

Revealing the graded activation mechanism of neurotensin receptor 1

Graded activation contributes to the precise regulation of GPCR activity, presenting new opportunities for drug design. In this work, a total of 10 μs enhanced-sampling simulations are performed to provide molecular insights into the binding dynamics differences of the neurotensin receptor 1 (NTSR1) to the full agonist SRI-9829, partial agonist RTI-3a and inverse agonist SR48692. The possible graded activation mechanism of NTSR1 is revealed by an integrated analysis utilizing the reweighted potential of mean force (PMF), deep learning (DL) and transfer entropy (TE). Specifically, the orthosteric pocket is observed to undergo expansion and contraction, with the G-protein-binding site experiencing interconversions among the inactive, intermediate and active-like states. Detailed structural comparisons capture subtle conformational differences arising from ligand binding in allosteric signaling, which can well explain the graded activation. Critical microswitches that contribute to graded activation are efficiently identified with the DL model. TE calculations enable the visualization of allosteric communication networks within the receptor, elucidating the driver-responder relationships associated with signal transduction. Fortunately, the dissociation of the full agonist from the orthosteric pocket is observed. The current findings systematically reveal the mechanism of NTSR1 graded activation, and also provide implications for structure-based drug design.

Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling

Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces, it is challenging to determine which amino acid pair interactions are cooperative. In this work, we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with Gα subunits. Our results reveal six GPCR:Gα contacts that are common to the different Gα subtypes and show strong cooperativity in the formation of interface. Both the C terminus helix5 and the core of the G protein are codependent entities and play an important role in GPCR coupling. We show that a promiscuous GPCR coupling to different Gα subtypes, makes all the GPCR:Gα contacts that are specific to each Gα subtype (Gαs, Gαi, and Gαq). This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.

Bayesian network models identify co-operative GPCR:G protein interactions that contribute to G protein coupling

Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior of interface interactions and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces it is challenging to determine which amino acid pair interactions are cooperative. In this work we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with G proteins. Our results reveal a strong co-dependency in the formation of interface GPCR:G protein contacts. This observation indicates that cooperativity of GPCR:G protein interactions is necessary for the coupling and selectivity of G proteins and is thus critical for receptor function. We have identified subnetworks containing polar and hydrophobic interactions that are common among multiple GPCRs coupling to different G protein subtypes (Gs, Gi and Gq). These common subnetworks along with G protein-specific subnetworks together confer selectivity to the G protein coupling. This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.

Understanding the Stabilization Mechanism of a Thermostable Mutant of Hygromycin B Phosphotransferase by Protein Sector-Guided Dynamic Analysis

Point mutations can exert beneficial effects on proteins, including stabilization. The stabilizing effects of mutations are typically attributed to changes in free energy and residue interactions. However, these explanations lack detail and physical insights, which hinder the mechanistic study of protein stabilization and prevent accurate computational prediction of stabilizing mutations. Here, we investigate the physical mechanism underlying the enhanced thermostability of a Hygromycin B phosphotransferase mutant, Hph5. We find that the unpredictable mutation A118V induces rotation of F199, allowing it to establish an aromatic-aromatic interaction with W235. In contrast, the predictable mutation T246A acts through static hydrophobic interactions within the protein core. These discoveries were accelerated by a residue-coevolution-based theory, which links mutational effects to stability-associated local structures, providing valuable guidance for mechanistic exploration. The established workflow will benefit the development of accurate stability prediction programs and can be used to mine a protein stability database for undiscovered physical mechanisms.

Autoregulation of GPCR signalling through the third intracellular loop

The third intracellular loop (ICL3) of the G protein-coupled receptor (GPCR) fold is important for the signal transduction process downstream of receptor activation1-3. Despite this, the lack of a defined structure of ICL3, combined with its high sequence divergence among GPCRs, complicates characterization of its involvement in receptor signalling4. Previous studies focusing on the β2 adrenergic receptor (β2AR) suggest that ICL3 is involved in the structural process of receptor activation and signalling5-7. Here we derive mechanistic insights into the role of ICL3 in β2AR signalling, observing that ICL3 autoregulates receptor activity through a dynamic conformational equilibrium between states that block or expose the receptor's G protein-binding site. We demonstrate the importance of this equilibrium for receptor pharmacology, showing that G protein-mimetic effectors bias the exposed states of ICL3 to allosterically activate the receptor. Our findings additionally reveal that ICL3 tunes signalling specificity by inhibiting receptor coupling to G protein subtypes that weakly couple to the receptor. Despite the sequence diversity of ICL3, we demonstrate that this negative G protein-selection mechanism through ICL3 extends to GPCRs across the superfamily, expanding the range of known mechanisms by which receptors mediate G protein subtype selective signalling. Furthermore, our collective findings suggest ICL3 as an allosteric site for receptor- and signalling pathway-specific ligands.

Yeast-based directed-evolution for high-throughput structural stabilization of G protein-coupled receptors (GPCRs)

The immense potential of G protein-coupled receptors (GPCRs) as targets for drug discovery is not fully realized due to the enormous difficulties associated with structure elucidation of these profoundly unstable membrane proteins. The existing methods of GPCR stability-engineering are cumbersome and low-throughput; in addition, the scope of GPCRs that could benefit from these techniques is limited. Here, we present a yeast-based screening platform for a single-step isolation of GRCR variants stable in the presence of short-chain detergents, a feature essential for their successful crystallization using vapor diffusion method. The yeast detergent-resistant cell wall presents a unique opportunity for compartmentalization, to physically link the receptor's phenotype to its encoding DNA, and thus enable discovery of stable GPCR variants with unprecedent efficiency. The scope of mutations identified by the method reveals a surprising amenability of the GPCR scaffold to stabilization, and suggests an intriguing possibility of amending the stability properties of GPCR by varying the structural status of the C-terminus.

Sequence coevolution and structure stabilization modulate olfactory receptor expression

Olfactory receptors (ORs) belong to class A G-protein coupled receptors (GPCRs) and are activated by a variety of odorants. To date, there is no three-dimensional structure of an OR available. One of the major bottlenecks in obtaining purified protein for structural studies of ORs is their poor expression in heterologous cells. To design mutants that enhance expression and thereby enable protein purification, we first identified computable physical properties that recapitulate OR and class A GPCR expression and further conducted an iterative computational prediction-experimental test cycle and generated human OR mutants that express as high as biogenic amine receptors for which structures have been solved. In the process of developing the computational method to recapitulate the expression of ORs in membranes, we identified properties, such as amino acid sequence coevolution, and the strength of the interactions between intracellular loop 1 (ICL1) and the helix 8 region of ORs, to enhance their heterologous expression. We identified mutations that are directly located in these regions as well as other mutations not located in these regions but allosterically strengthen the ICL1-helix 8 enhance expression. These mutants also showed functional responses to known odorants. This method to enhance heterologous expression of mammalian ORs will facilitate high-throughput "deorphanization" of ORs, and enable OR purification for biochemical and structural studies to understand odorant-OR interactions.

Development of thermostable sucrose phosphorylase by semi-rational design for efficient biosynthesis of alpha-D-glucosylglycerol

Abstract

Sucrose phosphorylase (SPase) can specifically catalyze transglycosylation reactions and can be used to enzymatically synthesize α-D-glycosides. However, the low thermostability of SPase has been a bottleneck for its industrial application. In this study, a SPase gene from Leuconostoc mesenteroides ATCC 12,291 (LmSPase) was synthesized with optimized codons and overexpressed successfully in Escherichia coli. A semi-rational design strategy that combined the FireProt (a web server designing thermostable proteins), structure–function analysis, and molecular dynamic simulations was used to improve the thermostability of LmSPase. Finally, one single-point mutation T219L and a combination mutation I31F/T219L/T263L/S360A (Mut4) with improved thermostability were obtained. The half-lives at 50 °C of T219L and Mut4 both increased approximately two-fold compared to that of wild-type LmSPase (WT). Furthermore, the two variants T219L and Mut4 were used to produce α-D-glucosylglycerol (αGG) from sucrose and glycerol by incubating with 40 U/mL crude extracts at 37 °C for 60 h and achieved the product concentration of 193.2 ± 12.9 g/L and 195.8 ± 13.1 g/L, respectively, which were approximately 1.3-fold higher than that of WT (150.4 ± 10.0 g/L). This study provides an effective strategy for improving the thermostability of an industrial enzyme.

Key points

• Predicted potential hotspot residues directing the thermostability of LmSPase by semi-rational design

• Screened two positive variants with higher thermostability and higher activity

• Synthesized α-D-glucosylglycerol to a high level by two screened positive variants

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-021-11551-0.

Molecular Dynamics Simulations for the Determination of the Characteristic Structural Differences between Inactive and Active States of Wild Type and Mutants of the Orexin2 Receptor

The orexin2 receptor (OX2R), which is classified as a class A G protein-coupled receptor (GPCR), is the target of our study. We performed over 20 several-microsecond-scale molecular dynamics simulations of the wild type and mutants of OX2R to extract the characteristics of the structural changes taking place in the active state. We introduced mutations that exhibited the stable inactive state and the constitutively active state in class A GPCRs. In these simulations, significant characteristic structural changes were observed in the V309^6.40Y mutant, which corresponded to a constitutively active mutant. These conformational changes include the outward movement of the transmembrane helix 6 (TM6) and the inward movement of TM7, which are common structural changes in the activation of GPCRs. In addition, we extracted a suitable index for the quantitative evaluation of the active and inactive states of GPCRs, namely, the inter-atomic distance of Cα atoms between x(3.46) and Y(7.53). The structures of the inactive and active states solved by X-ray crystallography and cryo-electron microscopy can be classified using the inter-atomic distance. Furthermore, we clarified that the inward movement of TM7 requires the swapping of M305^6.36 on TM6 and L367^7.56 on TM7. Finally, we discussed the structural advantages of TM7 inward movement for GPCR activation.

Allosteric communication regulates ligand-specific GPCR activity

G protein-coupled receptors (GPCRs) are membrane-bound proteins that are ubiquitously expressed in many cell types and take part in mediating multiple signaling pathways. GPCRs are dynamic proteins and exist in an equilibrium between an ensemble of conformational states such as inactive and fully active states. This dynamic nature of GPCRs is one of the factors that confers their basal activity even in the absence of any ligand-mediated activation. Ligands selectively bind and stabilize a subset of the conformations from the ensemble leading to a shift in the equilibrium toward the inactive or the active state depending on the nature of the ligand. This ligand-selective effect is achieved through allosteric communication between the ligand binding site and G protein or β-arrestin coupling site. Similarly, the G protein coupling to the receptor exerts the allosteric effect on the ligand binding region leading to increased binding affinity for agonists and decreased affinity for antagonists or inverse agonists. In this review, we enumerate the current state of our understanding of the mechanism of allosteric communication in GPCRs with a specific focus on the critical role of computational methods in delineating the residues involved in allosteric communication. Analyzing allosteric communication mechanism using molecular dynamics simulations has revealed (a) a structurally conserved mechanism of allosteric communication that regulates the G protein coupling, (b) a rational structure-based approach to designing selective ligands, and (c) an approach to designing allosteric GPCR mutants that are either ligand and G protein or β-arrestin selective.

The Dynamics of the Neuropeptide Y Receptor Type 1 Investigated by Solid-State NMR and Molecular Dynamics Simulation

We report data on the structural dynamics of the neuropeptide Y (NPY) G-protein-coupled receptor (GPCR) type 1 (Y1R), a typical representative of class A peptide ligand GPCRs, using a combination of solid-state NMR and molecular dynamics (MD) simulation. First, the equilibrium dynamics of Y1R were studied using 15N-NMR and quantitative determination of 1H-13C order parameters through the measurement of dipolar couplings in separated-local-field NMR experiments. Order parameters reporting the amplitudes of the molecular motions of the C-H bond vectors of Y1R in DMPC membranes are 0.57 for the Cα sites and lower in the side chains (0.37 for the CH2 and 0.18 for the CH3 groups). Different NMR excitation schemes identify relatively rigid and also dynamic segments of the molecule. In monounsaturated membranes composed of longer lipid chains, Y1R is more rigid, attributed to a higher hydrophobic thickness of the lipid membrane. The presence of an antagonist or NPY has little influence on the amplitude of motions, whereas the addition of agonist and arrestin led to a pronounced rigidization. To investigate Y1R dynamics with site resolution, we conducted extensive all-atom MD simulations of the apo and antagonist-bound state. In each state, three replicas with a length of 20 μs (with one exception, where the trajectory length was 10 μs) were conducted. In these simulations, order parameters of each residue were determined and showed high values in the transmembrane helices, whereas the loops and termini exhibit much lower order. The extracellular helix segments undergo larger amplitude motions than their intracellular counterparts, whereas the opposite is observed for the loops, Helix 8, and termini. Only minor differences in order were observed between the apo and antagonist-bound state, whereas the time scale of the motions is shorter for the apo state. Although these relatively fast motions occurring with correlation times of ns up to a few µs have no direct relevance for receptor activation, it is believed that they represent the prerequisite for larger conformational transitions in proteins.

Activation Microswitches in Adenosine Receptor A2A Function as Rheostats in the Cell Membrane

Although multiple components of the cell membrane modulate the stability and activation of G protein-coupled receptors (GPCRs), insights into the dynamics of GPCR structures come from biophysical studies conducted in detergents. This is because of the challenges of studying activation in a multicomponent lipid bilayer. To understand the role of cellular membrane lipids and cations in GPCR activation, we performed multiscale molecular dynamics simulations (56 μs) on three different conformational states of adenosine receptor A2AR, in both the cell membrane-like lipid bilayer and in detergent micelles. Molecular dynamics (MD) simulations show that the phosphatidylinositol bisphosphate (PIP2) interacts with the basic residues in the intracellular regions of A2AR, thereby reducing the flexibility of the receptor in the inactive state and limiting the transition to the active-intermediate state. In the G protein-coupled fully active state, PIP2 stabilizes the GPCR:G protein complex. Such stiffening effects are absent in non-ionic detergent micelles, and therefore, more transitions have been observed in detergents. The inter-residue distances that change significantly upon GPCR activation are known as activation microswitches. The activation microswitches show different levels of activation in the cell membrane, in the pure POPC bilayer, and in detergents. Thus, the temporal heat map of different activation microswitches calculated from the MD simulations suggests a rheostat model of GPCR activation microswitches rather than the binary switch model. These simulation results connect the chemistry of cell membrane lipids to receptor activity, which is useful for the design of detergents mimicking the cell membrane.

Conformational dynamics of a G protein-coupled receptor helix 8 in lipid membranes

G protein-coupled receptors (GPCRs) are the largest and pharmaceutically most important class of membrane proteins encoded in the human genome, characterized by a seven-transmembrane helix architecture and a C-terminal amphipathic helix 8 (H8). In a minority of GPCR structures solved to date, H8 either is absent or adopts an unusual conformation. The controversial existence of H8 of the class A GPCR neurotensin receptor 1 (NTS1) has been examined here for the nonthermostabilized receptor in a functionally supporting membrane environment using electron paramagnetic resonance, molecular dynamics simulations, and circular dichroism. Lipid-protein interactions with phosphatidylserine and phosphatidylethanolamine lipids, in particular, stabilize the residues 374 to 390 of NTS1 into forming a helix. Furthermore, introduction of a helix-breaking proline residue in H8 elicited an increase in ß-arrestin-NTS1 interactions observed in pull-down assays, suggesting that the structure and/or dynamics of H8 might play an important role in GPCR signaling.

Machine Learning for Prioritization of Thermostabilizing Mutations for G-Protein Coupled Receptors

Although the three-dimensional structures of G-protein coupled receptors (GPCRs), the largest superfamily of drug targets, have enabled structure-based drug design, there are no structures available for 87% of GPCRs. This is due to the stiff challenge in purifying the inherently flexible GPCRs. Identifying thermostabilized mutant GPCRs via systematic alanine scanning mutations has been a successful strategy in stabilizing GPCRs, but it remains a daunting task for each GPCR. We developed a computational method that combines sequence-, structure-, and dynamics-based molecular properties of GPCRs that recapitulate GPCR stability, with four different machine learning methods to predict thermostable mutations ahead of experiments. This method has been trained on thermostability data for 1231 mutants, the largest publicly available data set. A blind prediction for thermostable mutations of the complement factor C5a receptor 1 retrieved 36% of the thermostable mutants in the top 50 prioritized mutants compared to 3% in the first 50 attempts using systematic alanine scanning.

Prediction of Conformation Specific Thermostabilizing Mutations for Class A G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are highly flexible and prone to denaturation during protein extraction in detergents and purification. This poses a huge challenge to purify a conformationally homogeneous solution of GPCRs. Thermostabilizing mutations have been used widely to purify and obtain crystal structures of several GPCRs. However, identifying thermostabilizing mutations for GPCRs remains a tedious and expensive task as they are not transferable even among closely related GPCRs. Additionally, the mutations stabilizing one conformational state of a GPCR do not always stabilize other conformational state(s) of the same GPCR. Previously we developed a computational method, LiticonDesign, for rapid prediction of thermostabilizing mutations for a specific GPCR conformation. In this study, we have used LiticonDesign to predict thermostabilizing mutations for the agonist bound active-intermediate state of the human adenosine receptor (A2AR) using the structure of the inactive state of the same GPCR and vice versa. Our study shows that the thermostable mutation predictions using LiticonDesign, for an active-intermediate state of a GPCR (A2AR in our case), requires a homology model that is derived from an active/active-intermediate state GPCR structure as a template. Similarly, the homology models derived from inactive state GPCR conformations are better in predicting the thermostable mutations for the inactive state of A2AR. Overall, LiticonDesign method is not only efficient in predicting thermostabilizing mutations for a given GPCR sequence but also can recover conformation specific mutations for a state of interest, if a suitable starting structure of desired conformation is chosen.

Engineering Salt Bridge Networks between Transmembrane Helices Confers Thermostability in G-Protein-Coupled Receptors

Introduction of specific point mutations has been an effective strategy in enhancing the thermostability of G-protein-coupled receptors (GPCRs). Our previous work showed that a specific residue position on transmembrane helix 6 (TM6) in class A GPCRs consistently yields thermostable mutants. The crystal structure of human chemokine receptor CCR5 also showed increased thermostability upon mutation of two positions, A233D^6.33 and K303E^7.59. With the goal of testing the transferability of these two thermostabilizing mutations in other chemokine receptors, we tested the mutations A237D^6.33 and R307E^7.59 in human CCR3 for thermostability and aggregation properties in detergent solution. Interestingly, the double mutant exhibited a 6-10-fold decrease in the aggregation propensity of the wild-type protein. This is in stark contrast to the two single mutants whose aggregation properties resemble the wild type (WT). Moreover, unlike in CCR5, the two single mutants separately showed no increase in thermostability compared to the wild-type CCR3, while the double-mutant A237D^6.33/R307E^7.59 confers an increase of 2.6 °C in the melting temperature compared to the WT. Extensive all-atom molecular dynamics (MD) simulations in detergent micelles show that a salt bridge network between transmembrane helices TM3, TM6, and TM7 that is absent in the two single mutants confers stability in the double mutant. The free energy surface of the double mutant shows conformational homogeneity compared to the single mutants. An annular n-dodecyl maltoside detergent layer packs tighter to the hydrophobic surface of the double-mutant CCR3 compared to the single mutants providing additional stability. The purification of other C-C chemokine receptors lacking such stabilizing residues may benefit from the incorporation of these two point mutations.

Optimization and 13CH3 methionine labeling of a signaling competent neurotensin receptor 1 variant for NMR studies

Neurotensin is a 13-residue peptide that acts as a neuromodulator of classical neurotransmitters such as dopamine and glutamate in the mammalian central nervous system, mainly by activating the G protein-coupled receptor (GPCR), neurotensin receptor 1 (NTS₁). Agonist binding to GPCRs shifts the conformational equilibrium of the transmembrane helices towards distinct, thermodynamically favorable conformations that favor effector protein interactions and promotes cell signaling. The introduction of site specific labels for NMR spectroscopy has proven useful for investigating this dynamic process, but the low expression levels and poor stability of GPCRs is a hindrance to solution NMR experiments. Several thermostabilized mutants of NTS₁ have been engineered to circumvent this, with the crystal structures of four of these published. The conformational dynamics of NTS₁ however, has not been thoroughly investigated with NMR. It is generally accepted that stabilized GPCRs exhibit attenuated signaling, thus we thoroughly characterized the signaling characteristics of several thermostabilized NTS₁ variants to identify an optimal variant for protein NMR studies. A variant termed enNTS₁ exhibited the best combination of signaling capability and stability upon solubilization with detergents. enNTS₁ was subsequently labeled with ¹³CH₃-methionine in E. coli and purified to homogeneity in the absence of bound ligands. Using solution NMR spectroscopy we observed several well dispersed ¹³CH₃-methionine resonances, many of which exhibited chemical shift changes upon the addition of the high affinity agonist peptide, NT8-13. Thus, enNTS₁ represents a novel tool for investigating ligand induced conformational changes in NTS₁ to gain insights into the molecular mechanisms underlying neurotensin signaling.

Expression, Functional Characterization, and Solid-State NMR Investigation of the G Protein-Coupled GHS Receptor in Bilayer Membranes

The expression, functional reconstitution and first NMR characterization of the human growth hormone secretagogue (GHS) receptor reconstituted into either DMPC or POPC membranes is described. The receptor was expressed in E. coli. refolded, and reconstituted into bilayer membranes. The molecule was characterized by ¹⁵N and ¹³C solid-state NMR spectroscopy in the absence and in the presence of its natural agonist ghrelin or an inverse agonist. Static ¹⁵N NMR spectra of the uniformly labeled receptor are indicative of axially symmetric rotational diffusion of the G protein-coupled receptor in the membrane. In addition, about 25% of the ¹⁵N sites undergo large amplitude motions giving rise to very narrow spectral components. For an initial quantitative assessment of the receptor mobility, ¹H-¹³C dipolar coupling values, which are scaled by molecular motions, were determined quantitatively. From these values, average order parameters, reporting the motional amplitudes of the individual receptor segments can be derived. Average backbone order parameters were determined with values between 0.56 and 0.69, corresponding to average motional amplitudes of 40–50° of these segments. Differences between the receptor dynamics in DMPC or POPC membranes were within experimental error. Furthermore, agonist or inverse agonist binding only insignificantly influenced the average molecular dynamics of the receptor.

Transporter occluded-state conformation-induced endocytosis: Amino acid transporter ATB0,+-mediated tumor targeting of liposomes for docetaxel delivery for hepatocarcinoma therapy

Rapidly proliferating tumor cells upregulate specific amino acid transporters, which hold great potential for tumor-selective drug delivery. Published reports have focused primarily on blocking these transporters as a means of starving the tumor cells of amino acids, but their potential in drug delivery remains understudied. In the present study, we developed liposomes functionalized with lysine and polyoxyethylene stearate conjugate (LPS) to interact with ATB^0,+, an amino acid transporter overexpressed in hepatocarcinoma and the liver cancer cell line HepG2. The LPS modified liposomes (LPS-Lips) were ~100nm in size and exhibited high drug encapsulation efficiency as 94.7%. The uptake of LPS-Lips in HepG2 cells was dependent on Na⁺ and Cl^-. Molecular dynamic simulation showed that a sustained occluded state of the transporter upon binding to co-transported ions was formed and LPS-Lips triggered the cellular internalization of liposomes. We loaded these LPS-Lips with docetaxel and evaluated the potential of ATB^0,+-mediated endocytosis of the drug-loaded LPS-Lips in HepG2 cells in vitro and in syngeneic mouse transplants in vivo. Compared with unmodified liposomes, which did not interact with ATB^0,+, LPS-Lips exhibited the ability to deliver docetaxel more efficiently into tumor cells with consequent greater antitumor efficacy and less systemic toxicity. These studies provide first evidences that ATB^0,+ can be used as a novel and effective target for drug delivery system in tumor cells using chemically modified liposomes for loading with chemotherapeutics and targeting them for the transporter-mediated endocytosis. As ATB^0,+ is highly upregulated in several cancers, this approach holds potential for tumor-selective delivery of drugs to treat these cancer types.

Rapid Bioinformatic Identification of Thermostabilizing Mutations

Ex vivo stability is a valuable protein characteristic but is laborious to improve experimentally. In addition to biopharmaceutical and industrial applications, stable protein is important for biochemical and structural studies. Taking advantage of the large number of available genomic sequences and growth temperature data, we present two bioinformatic methods to identify a limited set of amino acids or positions that likely underlie thermostability. Because these methods allow thousands of homologs to be examined in silico, they have the advantage of providing both speed and statistical power. Using these methods, we introduced, via mutation, amino acids from thermoadapted homologs into an exemplar mesophilic membrane protein, and demonstrated significantly increased thermostability while preserving protein activity.

Stabilization of a prokaryotic LAT transporter by random mutagenesis

The knowledge of three-dimensional structures at atomic resolution of membrane transport proteins has improved considerably our understanding of their physiological roles and pathological implications. However, most structural biology techniques require an optimal candidate within a protein family for structural determination with (a) reasonable production in heterologous hosts and (b) good stability in detergent micelles. SteT, the Bacillus subtilis L-serine/L-threonine exchanger is the best-known prokaryotic paradigm of the mammalian L-amino acid transporter (LAT) family. Unfortunately, SteT's lousy stability after extracting from the membrane prevents its structural characterization. Here, we have used an approach based on random mutagenesis to engineer stability in SteT. Using a split GFP complementation assay as reporter of protein expression and membrane insertion, we created a library of 70 SteT mutants each containing random replacements of one or two residues situated in the transmembrane domains. Analysis of expression and monodispersity in detergent of this library permitted the identification of evolved versions of SteT with a significant increase in both expression yield and stability in detergent with respect to wild type. In addition, these experiments revealed a correlation between the yield of expression and the stability in detergent micelles. Finally, and based on protein delipidation and relipidation assays together with transport experiments, possible mechanisms of SteT stabilization are discussed. Besides optimizing a member of the LAT family for structural determination, our work proposes a new approach that can be used to optimize any membrane protein of interest.

How Can Mutations Thermostabilize G-Protein-Coupled Receptors?

Structures of over 30 different G-protein-coupled receptors (GPCRs) have advanced our understanding of cell signaling and have provided a foundation for structure-guided drug design. This exciting progress has required the development of three complementary methods to facilitate GPCR crystallization, one of which is the thermostabilization of receptors by systematic mutagenesis. However, the reason why a particular mutation, or combination of mutations, stabilizes the receptor is not always evident from a static crystal structure. Molecular dynamics (MD) simulations have been used to identify and estimate the energetic factors that affect thermostability through comparing the dynamics of the thermostabilized receptors with structure-based models of the wild-type receptor. The data indicate that receptors are stabilized through a combination of factors, including an increase in receptor rigidity, a decrease in collective motion, reduced stress at specific residues, and the presence of ordered water molecules. Predicting thermostabilizing mutations computationally represents a major challenge for the field.

Structural prerequisites for G-protein activation by the neurotensin receptor

We previously determined the structure of neurotensin receptor NTSR1 in an active-like conformation with six thermostabilizing mutations bound to the peptide agonist neurotensin. This receptor was unable to activate G proteins, indicating that the mutations restricted NTSR1 to relate agonist binding to G-protein activation. Here we analyse the effect of three of those mutations (E166A^3.49, L310A^6.37, F358A^7.42) and present two structures of NTSR1 able to catalyse nucleotide exchange at Gα. The presence of F358^7.42 causes the conserved W321^6.48 to adopt a side chain orientation parallel to the lipid bilayer sealing the collapsed Na⁺ ion pocket and linking the agonist with residues in the lower receptor part implicated in GPCR activation. In the intracellular receptor half, the bulkier L310^6.37 side chain dictates the position of R167^3.50 of the highly conserved D/ERY motif. These residues, together with the presence of E166^3.49 provide determinants for G-protein activation by NTSR1.

The structural basis of how G-protein coupled receptors respond to unique stimuli remains poorly understood. Here, Krumm et al. present new structures of the neurotensin receptor and reveal insights into how ligand binding is linked to structural rearrangements associated with receptor activation.