Sangbae Lee

Dynamic behavior of the active and inactive states of the adenosine A(2A) receptor.

The adenosine A2A receptor (A2AR) belongs to the superfamily of membrane proteins called the G-protein-coupled receptors (GPCRs) that form one of the largest superfamilies of drug targets. Deriving thermostable mutants has been one of the strategies used for crystallization of A2AR in both the agonist and antagonist bound conformational states. The crystal structures do not reveal differences in the activation mechanism of the mutant receptors compared to the wild type receptor, that have been observed experimentally. These differences stem from the dynamic behavior of the mutant receptors. Furthermore, it is not understood how the mutations confer thermostability. Since these details are difficult to obtain from experiments, we have used atomic level simulations to elucidate the dynamic behavior of the agonist and antagonist bound mutants as well the wild type A2AR. We found that significant enthalpic contribution leads to stabilization of both the inactive state (StaR2) and active-like state (GL31) thermostable mutants of A2AR. Stabilization resulting from mutations of bulky residues to alanine is due to the formation of interhelical hydrogen bonds and van der Waals packing that improves the transmembrane domain packing. The thermostable mutant GL31 shows less movement of the transmembrane helix TM6 with respect to TM3 than the wild type receptor. While restricted dynamics of GL31 is advantageous in its purification and crystallization, it could also be the reason why these mutants are not efficient in activating the G proteins. We observed that the calculated stress on each residue is higher in the wild type receptor compared to the thermostable mutants, and this stress is required for activation to occur. Thus, reduced dynamic behavior of the thermostable mutants leading to lowered activation of these receptors originates from reduced stress on each residue. Finally, accurate calculation of the change in free energy for single mutations shows good correlation with the change in the measured thermostability. These results provide insights into the effect of mutations that can be incorporated in deriving thermostable mutants for other GPCRs.

Rapid Computational Prediction of Thermostabilizing Mutations for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are highly dynamic and often denature when extracted in detergents. Deriving thermostable mutants has been a successful strategy to stabilize GPCRs in detergents, but this process is experimentally tedious. We have developed a computational method to predict the position of the thermostabilizing mutations for a given GPCR sequence. We have validated the method against experimentally measured thermostability data for single mutants of the β1-adrenergic receptor (β1AR), adenosine A2A receptor (A2AR) and neurotensin receptor 1 (NTSR1). To make these predictions we started from homology models of these receptors of varying accuracies and generated an ensemble of conformations by sampling the rigid body degrees of freedom of transmembrane helices. Then, an all-atom force field function was used to calculate the enthalpy gain, known as the “stability score” upon mutation of every residue, in these receptor structures, to alanine. For all three receptors, β1AR, A2AR, and NTSR1, we observed that mutations of hydrophobic residues in the transmembrane domain to alanine that have high stability scores correlate with high experimental thermostability. The prediction using the stability score improves when using an ensemble of receptor conformations compared to a single structure, showing that receptor flexibility is important. We also find that our previously developed LITiCon method for generating conformation ensembles is similar in performance to predictions using ensembles obtained from microseconds of molecular dynamics simulations (which is computationally hundred times slower than LITiCon). We improved the thermostability prediction by including other properties such as residue-based stress and the extent of allosteric communication by each residue in the stability score. Our method is the first step toward a computational method for rapid prediction of thermostable mutants of GPCRs.

Structure and dynamics of a constitutively active neurotensin receptor.

Many G protein-coupled receptors show constitutive activity, resulting in the production of a second messenger in the absence of an agonist; and naturally occurring constitutively active mutations in receptors have been implicated in diseases. To gain insight into mechanistic aspects of constitutive activity, we report here the 3.3 Å crystal structure of a constitutively active, agonist-bound neurotensin receptor (NTSR1) and molecular dynamics simulations of agonist-occupied and ligand-free receptor. Comparison with the structure of a NTSR1 variant that has little constitutive activity reveals uncoupling of the ligand-binding domain from conserved connector residues, that effect conformational changes during GPCR activation. Furthermore, molecular dynamics simulations show strong contacts between connector residue side chains and increased flexibility at the intracellular receptor face as features that coincide with robust signalling in cells. The loss of correlation between the binding pocket and conserved connector residues, combined with altered receptor dynamics, possibly explains the reduced neurotensin efficacy in the constitutively active NTSR1 and a facilitated initial engagement with G protein in the absence of agonist.

Structural Dynamics and Thermostabilization of Neurotensin Receptor 1

The neurotensin receptor NTSR1 binds the peptide agonist neurotensin (NTS) and signals preferentially via the Gq protein. Recently, Grisshammer and co-workers reported the crystal structure of a thermostable mutant NTSR1-GW5 with NTS bound. Understanding how the mutations thermostabilize the structure would allow efficient design of thermostable mutant GPCRs for protein purification, and subsequent biophysical studies. Using microsecond scale molecular dynamics simulations (4 μs) of the thermostable mutant NTSR1-GW5 and wild type NTSR1, we have elucidated the structural and energetic factors that affect the thermostability and dynamics of NTSR1. The thermostable mutant NTSR1-GW5 is found to be less flexible and less dynamic than the wild type NTSR1. The point mutations confer thermostability by improving the interhelical hydrogen bonds, hydrophobic packing, and receptor interactions with the lipid bilayer, especially in the intracellular regions. During MD, NTSR1-GW5 becomes more hydrated compared to wild type NTSR1, with tight hydrogen bonded water clusters within the transmembrane core of the receptor, thus providing evidence that water plays an important role in improving helical packing in the thermostable mutant. Our studies provide valuable insights into the stability and functioning of NTSR1 that will be useful in future design of thermostable mutants of other peptide GPCRs.

Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) mediate multiple signaling pathways in the cell, depending on the agonist that activates the receptor and multiple cellular factors. Agonists that show higher potency to specific signaling pathways over others are known as “biased agonists” and have been shown to have better therapeutic index. Although biased agonists are desirable, their design poses several challenges to date. The number of assays to identify biased agonists seems expensive and tedious. Therefore, computational methods that can reliably calculate the possible bias of various ligands ahead of experiments and provide guidance, will be both cost and time effective. In this work, using the mechanism of allosteric communication from the extracellular region to the intracellular transducer protein coupling region in GPCRs, we have developed a computational method to calculate ligand bias ahead of experiments. We have validated the method for several β-arrestin–biased agonists in β2-adrenergic receptor (β2AR), serotonin receptors 5-HT1B and 5-HT2B and for G-protein–biased agonists in the κ-opioid receptor. Using this computational method, we also performed a blind prediction followed by experimental testing and showed that the agonist carmoterol is β-arrestin–biased in β2AR. Additionally, we have identified amino acid residues in the biased agonist binding site in both β2AR and κ-opioid receptors that are involved in potentiating the ligand bias. We call these residues functional hotspots, and they can be used to derive pharmacophores to design biased agonists in GPCRs.

Distinct structural mechanisms determine substrate affinity and kinase activity of Protein Kinase Cα

Protein kinase Cα (PKCα) belongs to the family of AGC kinases that phosphorylate multiple peptide substrates. Although the consensus sequence motif has been identified and used to explain substrate specificity for PKCα, it does not inform the structural basis of substrate-binding and kinase activity for diverse substrates phosphorylated by this kinase. The transient, dynamic, and unstructured nature of this protein–protein interaction has limited structural mapping of kinase–substrate interfaces. Here, using multiscale MD simulation-based predictions and FRET sensor-based experiments, we investigated the conformational dynamics of the kinase–substrate interface. We found that the binding strength of the kinase–substrate interaction is primarily determined by long-range columbic interactions between basic (Arg/Lys) residues located N-terminally to the phosphorylated Ser/Thr residues in the substrate and by an acidic patch in the kinase catalytic domain. Kinase activity stemmed from conformational flexibility in the region C-terminal to the phosphorylated Ser/Thr residues. Flexibility of the substrate–kinase interaction enabled an Arg/Lys two to three amino acids C-terminal to the phosphorylated Ser/Thr to prime a catalytically active conformation, facilitating phosphoryl transfer to the substrate. The structural mechanisms determining substrate binding and catalytic activity formed the basis of diverse binding affinities and kinase activities of PKCα for 14 substrates with varying degrees of sequence conservation. Our findings provide insight into the dynamic properties of the kinase–substrate interaction that govern substrate binding and turnover. Moreover, this study establishes a modeling and experimental method to elucidate the structural dynamics underlying substrate selectivity among eukaryotic kinases.

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, A233D6.33 and K303E7.59. With the goal of testing the transferability of these two thermostabilizing mutations in other chemokine receptors, we tested the mutations A237D6.33 and R307E7.59 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 A237D6.33/R307E7.59 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.

Bitopic inhibition of ATP and substrate binding in Ser/Thr kinases through a conserved allosteric mechanism

Protein kinases achieve substrate selective phosphorylation through their conformational flexibility and dynamic interaction with the substrate. Designing substrate selective or kinase selective small molecule inhibitors remains a challenge because of a lack of understanding of the dynamic mechanism by which substrates are selected by the kinase. Using a combination of all-atom molecular dynamics simulations and FRET sensors, we have delineated an allosteric mechanism that results in interaction among the DFG motif, G-loop, and activation loop and structurally links the nucleotide and substrate binding interfaces in protein kinase Cα and three other Ser/Thr kinases. ATP-competitive staurosporine analogues engage this allosteric switch region located just outside the ATP binding site to displace substrate binding to varying degrees. These inhibitors function as bitopic ligands by occupying the ATP binding site and interacting with the allosteric switch region. The conserved mechanism identified in this study can be exploited to select and design bitopic inhibitors for kinases.