Flat-Bottom Strategy for Improved Accuracy in Protein Side-Chain Placements

Methotrexate Inhibits the Binding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Receptor Binding Domain to the Host-Cell Angiotensin-Converting Enzyme-2 (ACE-2) Receptor

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus mutates, finding effective drugs becomes more challenging. In this study, we use ultrasensitive frequency locked microtoroid optical resonators in combination with in silico screening to search for COVID-19 drugs that can stop the virus from attaching to the human angiotensin-converting enzyme 2 (hACE2) receptor in the lungs. We found 29 promising candidates that could block the binding site and selected four of them that were likely to bind very strongly. We tested three of these candidates using frequency locked optical whispering evanescent resonator (FLOWER), a label-free sensing method based on microtoroid resonators. FLOWER has previously been used for sensing single macromolecules. Here we show, for the first time, that FLOWER can provide accurate binding affinities and sense the inhibition effect of small molecule drug candidates without labels, which can be prohibitive in drug discovery. One of the candidates, methotrexate, showed binding to the spike protein 1.8 million times greater than that to the receptor binding domain (RBD) binding to hACE2, making it difficult for the virus to enter cells. We tested methotrexate against different variants of the SARS-CoV-2 virus and found that it is effective against all four of the tested variants. People taking methotrexate for other conditions have also shown protection against the original SARS-CoV-2 virus. Normally, it is assumed that methotrexate inhibits the replication and release of the virus. However, our findings suggest that it may also block the virus from entering cells. These studies additionally demonstrate the possibility of extracting candidate ligands from large databases, followed by direct receptor-ligand binding experiments on the best candidates using microtoroid resonators, thus creating a workflow that enables the rapid discovery of new drug candidates for a variety of applications.

Fully activated structure of the sterol-bound Smoothened GPCR-Gi protein complex

Smoothened (SMO) is an oncoprotein and signal transducer in the Hedgehog signaling pathway that regulates cellular differentiation and embryogenesis. As a member of the Frizzled (Class F) family of G protein-coupled receptors (GPCRs), SMO biochemically and functionally interacts with Gi family proteins. However, key molecular features of fully activated, G protein-coupled SMO remain elusive. We present the atomistic structure of activated human SMO complexed with the heterotrimeric Gi protein and two sterol ligands, equilibrated at 310 K in a full lipid bilayer at physiological salt concentration and pH. In contrast to previous experimental structures, our equilibrated SMO complex exhibits complete breaking of the pi-cation interaction between R4516.32 and W5357.55, a hallmark of Class F receptor activation. The Gi protein couples to SMO at seven strong anchor points similar to those in Class A GPCRs: intracellular loop 1, intracellular loop 2, transmembrane helix 6, and helix 8. On the path to full activation, we find that the extracellular cysteine-rich domain (CRD) undergoes a dramatic tilt, following a trajectory suggested by positions of the CRD in active and inactive experimental SMO structures. Strikingly, a sterol ligand bound to a shallow transmembrane domain (TMD) site in the initial structure migrates to a deep TMD pocket found exclusively in activator-bound SMO complexes. Thus, our results indicate that SMO interacts with Gi prior to full activation to break the molecular lock, form anchors with Gi subunits, tilt the CRD, and facilitate migration of a sterol ligand in the TMD to an activated position.

Structure and Molecular Mechanism of Signaling for the Glucagon-like Peptide-1 Receptor Bound to Gs Protein and Exendin-P5 Biased Agonist

The glucagon-like peptide-1 receptor (GLP-1R) is a key regulator of blood glucose and a prime target for the treatment of type II diabetes and obesity with multiple public drugs. Here we present a comprehensive computational analysis of the interactions of the activated GLP-1R-Gs signaling complex with a G protein biased agonist, Exendin P5 (ExP5), which possesses a unique N-terminal sequence responsible for the signal bias. Using a refined all-atom model of the ExP5-GLP-1R-Gs complex in molecular dynamics (MD) simulations, we propose a novel mechanism of conformation transduction in which the unique interaction network of ExP5 N-terminus propagates the binding signal across an array of conserved residues at the transmembrane domain to enhance Gs protein coupling at the cytoplasmic end of the receptor. Our simulations reveal previously unobserved interactions important for activation by ExP5 toward GDP-GTP signaling, providing new insights into the mechanism of class B G protein-coupled receptor (GPCR) signaling. These findings offer a framework for the structure-based design of more effective therapeutics.

The dynamics of agonist-β2-adrenergic receptor activation induced by binding of GDP-bound Gs protein

There is considerable uncertainty about the mechanism by which the β₂-adrenergic receptor (β₂AR) is activated. Here we use molecular metadynamics computations to predict the mechanism by which an agonist induces the activation of the β₂AR and its cognate Gs protein. We found that binding agonist alone to the inactive β₂AR does not break the ionic lock and hence does not drive the β₂AR towards the activated conformation. However, we found that attaching the inactive Gs protein to the agonist-bound inactive β₂AR (containing the ionic lock) leads to partial insertion of Gαs-α5 into the core of β₂AR, which breaks the ionic lock, leading to activation of the Gs protein coupled to β₂AR. Upon activation, the Gαs protein undergoes a remarkable opening of the GDP binding pocket, making the GDP available for exchange or release. Concomitantly, Gαs-α5 undergoes a remarkable expansion in the β₂AR cytoplasmic region after the ionic lock is broken, inducing TM6 to displace outward by ~5 Å from TM3.

Predicted structure and cell signaling of TAS2R14 reveal receptor hyper-flexibility for detecting diverse bitter tastes

The 25 human bitter taste receptors (TAS2Rs) are expressed on taste and extra-oral cells representing an integrated chemosensory system. The archetypal TAS2R14 is activated by > 150 topographically diverse agonists, raising the question of how this uncharacteristic accommodation is achieved for these GPCRs. We report the computationally derived structure of TAS2R14 with binding sites and energies for five highly diverse agonists. Remarkably, the binding pocket is the same for all five agonists. The energies derived from molecular dynamics are consistent with experiments determining signal transduction coefficients in live cells. TAS2R14 accommodates agonists through the breaking of a TMD3 H-bond instead of the prototypic strong salt bridge, a TMD1,2,7 interaction different from Class A GPCRs, and agonist-promoted TMD3 salt bridges for high affinity (which we confirmed by receptor mutagenesis). Thus, the broadly tuned TAS2Rs accommodate diverse agonists via a single (vs multiple) binding pocket through unique TM interactions for sensing disparate micro-environments.

Predicted Three-Dimensional Structure of the GCR1 Putative GPCR in Arabidopsis thaliana and Its Binding to Abscisic Acid and Gibberellin A1

GCR1 has been proposed as a plant analogue to animal G-protein-coupled receptors that can promote or regulate several physiological processes by binding different phytohormones. For instance, abscisic acid (ABA) and gibberellin A1 (GA1) have been shown to promote or regulate germination and flowering, root elongation, dormancy, and biotic and abiotic stresses, among others. They may act through binding to GCR1, which would put GCR1 at the heart of key signaling processes of agronomic importance. Unfortunately, this GPCR function has yet to be fully validated due to the lack of an X-ray or cryo-EM 3D atomistic structure for GCR1. Here, we used the primary sequence data from Arabidopsis thaliana and the GEnSeMBLE complete sampling method to examine 13 trillion possible packings of the 7 transmembrane helical domains corresponding to GCR1 to downselect an ensemble of 25 configurations likely to be accessible to the binding of ABA or GA1. We then predicted the best binding sites and energies for both phytohormones to the best GCR1 configurations. To provide the basis for the experimental validation of our predicted ligand-GCR1 structures, we identify several mutations that should improve or weaken the interactions. Such validations could help establish the physiological role of GCR1 in plants.

Intermediate-state-trapped mutants pinpoint G protein-coupled receptor conformational allostery

Understanding the roles of intermediate states in signaling is pivotal to unraveling the activation processes of G protein-coupled receptors (GPCRs). However, the field is still struggling to define these conformational states with sufficient resolution to study their individual functions. Here, we demonstrate the feasibility of enriching the populations of discrete states via conformation-biased mutants. These mutants adopt distinct distributions among five states that lie along the activation pathway of adenosine A2A receptor (A2AR), a class A GPCR. Our study reveals a structurally conserved cation-π lock between transmembrane helix VI (TM6) and Helix8 that regulates cytoplasmic cavity opening as a "gatekeeper" for G protein penetration. A GPCR activation process based on the well-discerned conformational states is thus proposed, allosterically micro-modulated by the cation-π lock and a previously well-defined ionic interaction between TM3 and TM6. Intermediate-state-trapped mutants will also provide useful information in relation to receptor-G protein signal transduction.

Synergic Effects in the Activation of the Sweet Receptor GPCR Heterodimer for Various Sweeteners Predicted Using Molecular Metadynamics Simulations

The sweet taste is elicited by activation of the TAS1R2/1R3 heterodimer G protein-coupled receptor. This is a therapeutic target for treatment of obesity and metabolic dysfunctions. Sweetener blends provide attractive strategies to lower the sugar level while preserving the attractive taste of food. To understand the synergic effect of various sweetener blend combinations of artificial and natural sweeteners, we carried out our molecular dynamics studies using predicted structures of the TAS1R2/1R3 heterodimer and predicted structures for the sweeteners. We used as a measure of activation the intracellular ionic lock distance between transmembrane helices 3 and 6 of TAS1R3. We find that full synergic combinations [rebaudioside A (Reb-A)/acesulfame K and Reb-A/sucralose] and partial synergic combinations (sucralose/acesulfame K) show significantly more negative changes in the free energy compared to single-ligand cases, while a pair known to be suppressive (saccharin and acesulfame K) shows significantly less changes than for the single-ligand case. This study provides an atomistic understanding of the mechanism for synergy and identifies new combinations of sweeteners to reduce the caloric content for treating diseases.

The atomistic level structure for the activated human κ-opioid receptor bound to the full Gi protein and the MP1104 agonist

The kappa opioid receptor (κOR) is an important target for pain therapeutics to reduce depression and other harmful side effects of existing medications. The analgesic activity is mediated by κOR signaling through the adenylyl cyclase-inhibitory family of Gi protein. Here, we report the three-dimensional (3D) structure for the active state of human κOR complexed with both heterotrimeric Gi protein and MP1104 agonist. This structure resulted from long molecular dynamics (MD) and metadynamics (metaMD) simulations starting from the 3.1-Å X-ray structure of κOR-MP1104 after replacing the nanobody with the activated Gi protein and from the 3.5-Å cryo-EM structure of μOR-Gi complex after replacing the 168 missing residues. Using MD and metaMD we discovered interactions to the Gi protein with strong anchors to two intracellular loops and transmembrane helix 6 of the κOR. These anchors strengthen the binding, contributing to a contraction in the binding pocket but an expansion in the cytoplasmic region of κOR to accommodate G protein. These remarkable changes in κOR structure reveal that the anchors are essential for activation.

Discovery of Novel Biased Opioid Receptor Ligands through Structure-Based Pharmacophore Virtual Screening and Experiment

G_i -protein-biased agonists with minimal β-arrestin recruitment represent opportunities to overcome the serious adverse effects of human mu opioid receptor (μ-OR) agonists and developing alternative and safe treatments for pain. In order to discover novel non-morphinan opioid receptor agonists, we applied hierarchical virtual screening of our in-house database against a pharmacophore based on modeling the active conformations of opioid receptors. We discovered an initial hit compound, a novel μ-OR agonist with a pyrazoloisoquinoline scaffold. We applied computational R-group screening to this compound and synthesized 14 derivatives predicted to be the best. Of these, a new G_i -protein-biased compound, 1-{5-(3-chlorophenyl)-7,8-dimethoxy-3-[4-(methylsulfonyl)benzyl]-3H-pyrazolo[3,4-c]isoquinolin-1-yl}-N,N-dimethylmethanamine, showed an EC₅₀ value of 179 nm against the μ-OR. This resulted in significant pain relief for mice in the phase II period of formalin response tests. This study provides a new strategy to identify diverse sets of promising compounds that might prove useful for the development of drugs that target other G-protein-coupled receptors.

A Human Ribonuclease Variant and ERK-Pathway Inhibitors Exhibit Highly Synergistic Toxicity for Cancer Cells

Pancreatic-type ribonucleases (ptRNases) are prevalent secretory enzymes that catalyze the cleavage of RNA. Ribonuclease inhibitor (RI) is a cytosolic protein that has femtomolar affinity for ptRNases, affording protection from the toxic catalytic activity of ptRNases, which can invade human cells. A human ptRNase variant that is resistant to inhibition by RI is a cytotoxin that is undergoing a clinical trial as a cancer chemotherapeutic agent. We find that the ptRNase and protein kinases in the ERK pathway exhibit strongly synergistic toxicity toward lung cancer cells (including a KRAS^G12C variant) and melanoma cells (including BRAF^V600E variants). The synergism arises from inhibiting the phosphorylation of RI and thereby diminishing its affinity for the ptRNase. These findings link seemingly unrelated cellular processes, and suggest that the use of a kinase inhibitor to unleash a cytotoxic enzyme could lead to beneficial manifestations in the clinic.

The 3D Structure of Human DP Prostaglandin G-Protein-Coupled Receptor Bound to Cyclopentanoindole Antagonist, Predicted Using the DuplexBiHelix Modification of the GEnSeMBLE Method

Prostaglandins play a critical physiological role in both cardiovascular and immune systems, acting through their interactions with 9 prostanoid G protein-coupled receptors (GPCRs). These receptors are important therapeutic targets for a variety of diseases including arthritis, allergies, type 2 diabetes, and cancer. The DP prostaglandin receptor is of interest because it has unique structural and physiological properties. Most notably, DP does not have the 3-6 ionic lock common to Class A GPCRs. However, the lack of X-ray structures for any of the 9 prostaglandin GPCRs hampers the application of structure-based drug design methods to develop more selective and active medications to specific receptors. We predict here 3D structures for the DP prostaglandin GPCR, based on the GEnSeMBLE complete sampling with hierarchical scoring (CS-HS) methodology. This involves evaluating the energy of 13 trillion packings to finally select the best 20 that are stable enough to be relevant for binding to antagonists, agonists, and modulators. To validate the predicted structures, we predict the binding site for the Merck cyclopentanoindole (CPI) selective antagonist docked to DP. We find that the CPI binds vertically in the 1-2-7 binding pocket, interacting favorably with residues R310^7.40 and K76^2.54 with additional interactions with S313^7.43, S316^7.46, S19^1.35, etc. This binding site differs significantly from that of antagonists to known Class A GPCRs where the ligand binds in the 3-4-5-6 region. We find that the predicted binding site leads to reasonable agreement with experimental Structure-Activity Relationship (SAR). We suggest additional mutation experiments including K76^2.54, E129^3.49, L123^3.43, M270^6.40, F274^6.44 to further validate the structure, function, and activation mechanism of receptors in the prostaglandin family. Our structures and binding sites are largely consistent and improve upon the predictions by Li et al. ( J. Am. Chem. Soc. 2007 , 129 ( 35 ), 10720 ) that used our earlier MembStruk prediction methodology.

Predicting glycosaminoglycan surface protein interactions and implications for studying axonal growth

Cell-surface carbohydrates play important roles in numerous biological processes through their interactions with various protein-binding partners. These interactions are made possible by the vast structural diversity of carbohydrates and the diverse array of carbohydrate presentations on the cell surface. Among the most complex and important carbohydrates are glycosaminoglycans (GAGs), which display varied stereochemistry, chain lengths, and patterns of sulfation. GAG-protein interactions participate in neuronal development, angiogenesis, spinal cord injury, viral invasion, and immune response. Unfortunately, little structural information is available for these complexes; indeed, for the highly sulfated chondroitin sulfate motifs, CS-E and CS-D, there are no structural data. We describe here the development and validation of the GAG-Dock computational method to predict accurately the binding poses of protein-bound GAGs. We validate that GAG-Dock reproduces accurately (<1-Å rmsd) the crystal structure poses for four known heparin-protein structures. Further, we predict the pose of heparin and chondroitin sulfate derivatives bound to the axon guidance proteins, protein tyrosine phosphatase σ (RPTPσ), and Nogo receptors 1-3 (NgR1-3). Such predictions should be useful in understanding and interpreting the role of GAGs in neural development and axonal regeneration after CNS injury.

Molecular-Docking-Based Drug Design and Discovery

Currently 30-50% of drug targets are G Protein-Coupled Receptors (GPCRs). However, the clinical useful drugs for targeting GPCR have been limited by the lack of subtype selectivity or efficacy, leading to undesirable side effects. To develop subtype-selective GPCR ligands with desired molecular properties, better understanding is needed of the pharmacophore elements and of the binding mechanism required for subtype selectivity. To illustrate these issues, we describe here three successful applications to understand the binding mechanism associated with subtype selectivity: 5-HT2B (5-Hydroxytryptamine, 5-HT) serotonin receptor (HT2BR), H3 histamine receptor (H3HR) and A3 adenosine receptor (A3AR). The understanding of structure-function relationships among individual types and subtypes of GPCRs gained from such computational predictions combined with experimental validation and testing is expected the development of new highly selective and effective ligands to address such diseases while minimizing side-effects.

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.

Computational Prediction and Biochemical Analyses of New Inverse Agonists for the CB1 Receptor

Human cannabinoid type 1 (CB1) G-protein coupled receptor is a potential therapeutic target for obesity. The previously predicted and experimentally validated ensemble of ligand-free conformations of CB1 [Scott, C. E. et al. Protein Sci. 2013 , 22 , 101 - 113 ; Ahn, K. H. et al. Proteins 2013 , 81 , 1304 - 1317] are used here to predict the binding sites for known CB1-selective inverse agonists including rimonabant and its seven known derivatives. This binding pocket, which differs significantly from previously published models, is used to identify 16 novel compounds expected to be CB1 inverse agonists by exploiting potential new interactions. We show experimentally that two of these compounds exhibit inverse agonist properties including inhibition of basal and agonist-induced G-protein coupling activity, as well as an enhanced level of CB1 cell surface localization. This demonstrates the utility of using the predicted binding sites for an ensemble of CB1 receptor structures for designing new CB1 inverse agonists.

The predicted ensemble of low-energy conformations of human somatostatin receptor subtype 5 and the binding of antagonists

Human somatostatin receptor subtype 5 (hSSTR5) regulates cell proliferation and hormone secretion. However, the identification of effective therapeutic small-molecule ligands is impeded because experimental structures are not available for any SSTR subtypes. Here, we predict the ensemble of low-energy 3D structures of hSSTR5 using a modified GPCR Ensemble of Structures in Membrane BiLayer Environment (GEnSeMBLE) complete sampling computational method. We find that this conformational ensemble displays most interhelical interactions conserved in class A G protein-coupled receptors (GPCRs) plus seven additional interactions (e.g., Y2.43-D3.49, T3.38-S4.53, K5.64-Y3.51) likely conserved among SSTRs. We then predicted the binding sites for a series of five known antagonists, leading to predicted binding energies consistent with experimental results reported in the literature. Molecular dynamics (MD) simulation of 50 ns in explicit water and lipid retained the predicted ligand-bound structure and formed new interaction patterns (e.g. R3.50-T6.34) consistent with the inactive μ-opioid receptor X-ray structure. We suggest more than six mutations for experimental validation of our prediction. The final predicted receptor conformations and antagonist binding sites provide valuable insights for designing new small-molecule drugs targeting SSTRs.

Predicted structures for kappa opioid G-protein coupled receptor bound to selective agonists

Human kappa opioid receptor (κ-OR), a G protein-coupled receptor (GPCR), has been identified as a drug target for treatment of such human disorders as pain perception, neuroendocrine physiology, affective behavior, and cognition. In order to find more selective and active agonists, one would like to do structure based drug design. Indeed, there is an X-ray structure for an antagonist bound to κ-OR, but structures for activated GPCRs are quite different from those for the inactive GPCRs. Here we predict the ensemble of 24 low-energy structures of human kappa opioid receptor (κ-OR), obtained by application of the GEnSeMBLE (GPCR Ensemble of Structures in Membrane Bilayer Environment) complete sampling method, which evaluates 13 trillion combinations of tilt and rotation angles for κ-OR to select the best 24. To validate these structures, we used the DarwinDock complete sampling method to predict the binding sites for five known agonists (ethylketocyclazocine, bremazocine, pentazocine, nalorphine, and morphine) bound to all 24 κ-OR conformations. We find that some agonists bind selectively to receptor conformations that lack the salt bridge between transmembrane domains 3 and 6 as expected for active conformations. These 3D structures for κ-OR provide a structural basis for understanding ligand binding and activation of κ-OR, which should be useful for guiding subtype specific drug design.

Predicted 3D structures of olfactory receptors with details of odorant binding to OR1G1

Olfactory receptors (ORs) are responsible for mediating the sense of smell; they allow humans to recognize an enormous number of odors but the connection between binding and perception is not known. We predict the ensemble of low energy structures for the human OR1G1 (hOR1G1) and also for six other diverse ORs, using the G protein-coupled receptor Ensemble of Structures in Membrane BiLayer Environment complete sampling method that samples 13 trillion different rotations and tilts using four different templates to predict the 24 structures likely to be important in binding and activation. Our predicted most stable structures of hOR1G1 have a salt-bridge between the conserved D3.49 and K6.30 in the D(E)RY region, that we expect to be associated with an inactive form. The hOR1G1 structure also has specific interaction in transmembrane domains (TMD) 3-6 (E3.39 and H6.40), which is likely an important conformational feature for all hORs because of the ~94 to 98 % conservation among all hOR sequences. Of the five ligands studied (nonanal, 9-decen-1-ol, 1-nonanol, camphor, and n-butanal), we find that the 4 expected to bind lead to similar binding energies with nonanol the strongest.

Molecular basis for dramatic changes in cannabinoid CB1 G protein-coupled receptor activation upon single and double point mutations

There is considerable interest in determining the activation mechanism of G protein-coupled receptors (GPCRs), one of the most important types of proteins for intercellular signaling. Recently, it was demonstrated for the cannabinoid CB1 GPCR, that a single mutation T210A could make CB1 completely inactive whereas T210I makes it essentially constitutively active. To obtain an understanding of this dramatic dependence of activity on mutation, we used first-principles-based methods to predict the ensemble of low-energy seven-helix conformations for the wild-type (WT) and mutants (T210A and T210I). We find that the transmembrane (TM) helix packings depend markedly on these mutations, leading for T210A to both TM3+TM6 and TM2+TM6 salt-bridge couplings in the cytoplasmic face that explains the inactivity of this mutant. In contrast T210I has no such couplings across the receptor explaining the ease in activating this mutant. WT has just the TM3+TM6 coupling, known to be broken upon GPCR activation. To test this hypothesis on activity, we predicted double mutants that would convert the inactive mutant to normal activity and then confirmed this experimentally. This CB1 activation mechanism, or one similar to it, is expected to play a role in other constitutively active GPCRs as well.

Ligand- and mutation-induced conformational selection in the CCR5 chemokine G protein-coupled receptor

We predicted the structural basis for pleiotropic signaling of the C-C chemokine type 5 (CCR5) G protein-coupled receptor (GPCR) by predicting the binding of several ligands to the lower-energy conformations of the CCR5 receptor and 11 mutants. For each case, we predicted the ∼ 20 most stable conformations for the receptor along with the binding sites for four anti-HIV ligands. We found that none of the ligands bind to the lowest-energy apo-receptor conformation. The three ligands with a similar pharmacophore (Maraviroc, PF-232798, and Aplaviroc) bind to a specific higher-energy receptor conformation whereas TAK-779 (with a different pharmacophore) binds to a different high-energy conformation. This result is in agreement with the very different binding-site profiles for these ligands obtained by us and others. The predicted Maraviroc binding site agrees with the recent structure of CCR5 receptor cocrystallized with Maraviroc. We performed 11 site-directed mutagenesis experiments to validate the predicted binding sites. Here, we independently predicted the lowest 10 mutant protein conformations for each of the 11 mutants and then docked the ligands to these lowest conformations. We found the predicted binding energies to be in excellent agreement with our mutagenesis experiments. These results show that, for GPCRs, each ligand can stabilize a different protein conformation, complicating the use of cocrystallized structures for ligand screening. Moreover, these results show that a single-point mutation in a GPCR can dramatically alter the available low-energy conformations, which in turn alters the binding site, potentially altering downstream signaling events. These studies validate the conformational selection paradigm for the pleiotropic function and structural plasticity of GPCRs.

Predicted ligands for the human urotensin-II G protein-coupled receptor with some experimental validation

Human Urotensin-II (U-II) is the most potent mammalian vasoconstrictor known.1 Thus, a U-II antagonist would be of therapeutic value in a number of cardiovascular disorders.2 Here, we describe our work on the prediction of the structure of the human U-II receptor (hUT2 R) using GEnSeMBLE (GPCR Ensemble of Structures in Membrane BiLayer Environment) complete sampling Monte Carlo method. With the validation of our predicted structures, we designed a series of new potential antagonists predicted to bind more strongly than known ligands. Next, we carried out R-group screening to suggest a new ligand predicted to bind with 7 kcal mol(-1) better energy than 1-{2-[4-(2-bromobenzyl)-4-hydroxypiperidin-1-yl]ethyl}-3-(thieno[3,2-b]pyridin-7-yl)urea, the designed antagonist predicted to have the highest affinity for the receptor. Some of these predictions were tested experimentally, validating the computational results. Using the pharmacophore generated from the predicted structure for hUT2 R bound to ACT-058362, we carried out virtual screening based on this binding site. The most potent hit compounds identified contained 2-(phenoxymethyl)-1,3,4-thiadiazole core, with the best derivative exhibiting an IC50 value of 0.581 μM against hUT2 R when tested in vitro. Our efforts identified a new scaffold as a potential new lead structure for the development of novel hUT2 R antagonists, and the computational methods used could find more general applicability to other GPCRs.

SuperBiHelix method for predicting the pleiotropic ensemble of G-protein-coupled receptor conformations

There is overwhelming evidence that G-protein-coupled receptors (GPCRs) exhibit several distinct low-energy conformations, each of which might favor binding to different ligands and/or lead to different downstream functions. Understanding the function of such proteins requires knowledge of the ensemble of low-energy configurations that might play a role in this pleiotropic functionality. We earlier reported the BiHelix method for efficiently sampling the (12)(7) = 35 million conformations resulting from 30° rotations about the axis (η) of all seven transmembrane helices (TMHs), showing that the experimental structure is reliably selected as the best conformation from this ensemble. However, various GPCRs differ sufficiently in the tilts of the TMHs that this method need not predict the optimum conformation starting from any other template. In this paper, we introduce the SuperBiHelix method in which the tilt angles (θ, ϕ) are optimized simultaneously with rotations (η) efficiently enough that it is practical and sufficient to sample (5 × 3 × 5)(7) = 13 trillion configurations. This method can correctly identify the optimum structure of a GPCR starting with the template from a different GPCR. We have validated this method by predicting known crystal structure conformations starting from the template of a different protein structure. We find that the SuperBiHelix conformational ensemble includes the higher energy conformations associated with the active protein in addition to those associated with the more stable inactive protein. This methodology was then applied to design and experimentally confirm structures of three mutants of the CB1 cannabinoid receptor associated with different functions.

Computationally-predicted CB1 cannabinoid receptor mutants show distinct patterns of salt-bridges that correlate with their level of constitutive activity reflected in G protein coupling levels, thermal stability, and ligand binding

The cannabinoid receptor 1 (CB1), a member of the class A G-protein-coupled receptor (GPCR) family, possesses an observable level of constitutive activity. Its activation mechanism, however, has yet to be elucidated. Previously we discovered dramatic changes in CB1 activity due to single mutations; T3.46A, which made the receptor inactive, and T3.46I and L3.43A, which made it essentially fully constitutively active. Our subsequent prediction of the structures of these mutant receptors indicated that these changes in activity are explained in terms of the pattern of salt-bridges in the receptor region involving transmembrane domains 2, 3, 5, and 6. Here we identified key salt-bridges, R2.37 + D6.30 and D2.63 + K3.28, critical for CB1 inactive and active states, respectively, and generated new mutant receptors that we predicted would change CB1 activity by either precluding or promoting these interactions. We find that breaking the R2.37 + D6.30 salt-bridge resulted in substantial increase in G-protein coupling activity and reduced thermal stability relative to the wild-type reflecting the changes in constitutive activity from inactive to active. In contrast, breaking the D2.63 + K3.28 salt-bridge produced the opposite profile suggesting this interaction is critical for the receptor activation. Thus, we demonstrate an excellent correlation with the predicted pattern of key salt-bridges and experimental levels of activity and conformational flexibility. These results are also consistent with the extended ternary complex model with respect to shifts in agonist and inverse agonist affinity and provide a powerful framework for understanding the molecular basis for the multiple stages of CB1 activation and that of other GPCRs in general.

Predicted structure of agonist-bound glucagon-like peptide 1 receptor, a class B G protein-coupled receptor

The glucagon-like peptide 1 receptor (GLP1R) is a G protein-coupled receptor (GPCR) involved in insulin synthesis and regulation; therefore, it is an important drug target for treatment of diabetes. However, GLP1R is a member of the class B1 family of GPCRs for which there are no experimental structures. To provide a structural basis for drug design and to probe class B GPCR activation, we predicted the transmembrane (TM) bundle structure of GLP1R bound to the peptide Exendin-4 (Exe4; a GLP1R agonist on the market for treating diabetes) using the MembStruk method for scanning TM bundle conformations. We used protein-protein docking methods to combine the TM bundle with the X-ray crystal structure of the 143-aa N terminus coupled to the Exe4 peptide. This complex was subjected to 28 ns of full-solvent, full-lipid molecular dynamics. We find 14 strong polar interactions of Exe4 with GLP1R, of which 8 interactions are in the TM bundle (2 interactions confirmed by mutation studies) and 6 interactions involve the N terminus (3 interactions found in the crystal structure). We also find 10 important hydrophobic interactions, of which 4 interactions are in the TM bundle (2 interactions confirmed by mutation studies) and 6 interactions are in the N terminus (6 interactions present in the crystal structure). Thus, our predicted structure agrees with available mutagenesis studies. We suggest a number of mutation experiments to further validate our predicted structure. The structure should be useful for guiding drug design and can provide a structural basis for understanding ligand binding and receptor activation of GLP1R and other class B1 GPCRs.

Phosphofructokinase 1 glycosylation regulates cell growth and metabolism

Cancer cells must satisfy the metabolic demands of rapid cell growth within a continually changing microenvironment. We demonstrated that the dynamic posttranslational modification of proteins by O-linked β-N-acetylglucosamine (O-GlcNAcylation) is a key metabolic regulator of glucose metabolism. O-GlcNAcylation was induced at serine 529 of phosphofructokinase 1 (PFK1) in response to hypoxia. Glycosylation inhibited PFK1 activity and redirected glucose flux through the pentose phosphate pathway, thereby conferring a selective growth advantage on cancer cells. Blocking glycosylation of PFK1 at serine 529 reduced cancer cell proliferation in vitro and impaired tumor formation in vivo. These studies reveal a previously uncharacterized mechanism for the regulation of metabolic pathways in cancer and a possible target for therapeutic intervention.

3D structure prediction of TAS2R38 bitter receptors bound to agonists phenylthiocarbamide (PTC) and 6-n-propylthiouracil (PROP)

The G protein-coupled receptor (GPCR) TAS2R38 is a bitter taste receptor that can respond to bitter compounds such as phenylthiocarbamide (PTC) and 6-n-propylthiouracil (PROP). This receptor was chosen because its four haplotypes (based on three residue site polymorphism) hTAS2R38PAV, hTAS2R38AVI, hTAS2R38AAI, and hTAS2R38PVV are known to have dramatically different responses to PTC and PROP. We aimed to identify the protein-ligand interaction features that determine whether the bitter taste signal from this receptor is sent to the cortex. To do this we predicted the 3D structures of the TAS2R38 bitter taste receptor using our new BiHelix and SuperBiHelix Monte Carlo methods (No experimental determinations of the 3D structure have been reported for any taste receptors.). We find that residue 262 (2nd position in the polymorphism) is involved in the interhelical hydrogen bond network stabilizing the GPCR structure in tasters (hTAS2R38PAV, hTAS2R38AAI, and hTAS2R38PVV), while it is not in the nontaster (hTAS2R38AVI). This suggests that the hydrogen bond interactions between TM3 and TM6 or between TM5 and TM6 may play a role in activating this GPCR. To further validate these structures, we used the DarwinDock method to predict the binding sites and 3D structures for PTC and PROP bound to hTAS2R38PAV, hTAS2R38AVI, hTAS2R38AAI, and hTAS2R38PVV, respectively. Our results show that PTC and PROP can form H-bonds with the backbone of residue 262 in the tasters (hTAS2R38PAV, hTAS2R38AAI, and hTAS2R38PVV) but not in the nontaster (hTAS2R38AVI). Thus it appears that the hydrogen bond interaction between TM3 and TM6 may activate the receptor to pass the ligand binding signal to intracellular processes and that the H-bond between agonists and residue 262 in tasters is involved in the bitter tasting. This is in agreement with experimental observations, providing validation of the predicted ligand-protein complexes and also a potential activation mechanism for the TAS2R38 receptor.

Molecular basis for the interplay of apoptosis and proliferation mediated by Bcl-xL:Bim interactions in pancreatic cancer cells

A major mechanism through which cancer cells avoid apoptosis is by promoting the association of anti-apoptotic members of the pro-survival Bcl-2 protein family (like Bcl-2 and Bcl-xL) with BH(3) domain-only proteins (like Bim and Bid). Apoptosis and cell proliferation have been shown to be linked for many cancers but the molecular basis for this link is far from understood. We have identified the Bcl-xL:Bim protein-protein interface as a direct regulator of proliferation and apoptosis in pancreatic cancer cells. We were able to predict and subsequently verify experimentally the effect of various Bcl-xL single-point mutants (at the position A142) on binding to Bim by structural analysis and computational modeling of the inter-residue interactions at the Bcl-xL:Bim protein-protein interface. The mutants A142N, A142Q, and A142Y decreased binding of Bim to Bcl-xL and A142S increased this binding. The Bcl-xL mutants, with decreased affinity for Bim, caused an increase in apoptosis and a corresponding decrease in cell proliferation. However, we could prevent these effects by introducing a small interfering RNA (siRNA) targeted at Bim. These results show a novel role played by the Bcl-xL:Bim interaction in regulating proliferation of pancreatic cancer cells at the expense of apoptosis. This study presents a physiologically relevant model of the Bcl-xL:Bim interface that can be used for rational therapeutic design for the inhibition of proliferation and cancer cell resistance to apoptosis.

Structure prediction of G protein-coupled receptors and their ensemble of functionally important conformations

G protein-coupled receptors (GPCRs) are integral membrane proteins whose "pleiotropic" nature enables transmembrane (TM) signal transduction, amplification, and diversification via G protein-coupled and β arrestin-coupled pathways. GPCRs appear to enable this by being structurally flexible and by existing in different conformational states with potentially different signaling and functional consequences. We describe a method for the prediction of the three-dimensional structures of these different conformations of GPCRs starting from their amino acid sequence. It combines a unique protocol of computational methods that first predict the TM regions of these receptors and TM helix shapes based on those regions, which is followed by a locally complete sampling of TM helix packings and their scoring that results in a few (~10-20) lowest energy conformations likely to play a role in binding to different ligands and signaling events. Prediction of the structures for multiple conformations of a GPCR is starting to enable the testing of multiple hypotheses related to GPCR activation and binding to ligands with different signaling profiles.

Bihelix: Towards de novo structure prediction of an ensemble of G-protein coupled receptor conformations

G-Protein Coupled Receptors (GPCRs) play a critical role in cellular signal transduction pathways and are prominent therapeutic targets. Recently there has been major progress in obtaining experimental structures for a few GPCRs. Each GPCR, however, exhibits multiple conformations that play a role in their function and we have been developing methods aimed at predicting structures for all these conformations. Analysis of available structures shows that these conformations differ in relative helix tilts and rotations. The essential issue is, determining how to orient each of the seven helices about its axis since this determines how it interacts with the other six helices. Considering all possible helix rotations to ensure that no important packings are overlooked, and using rotation angle increments of 30° about the helical axis would still lead to 12(7) or 35 million possible conformations each with optimal residue positions. We show in this paper how to accomplish this. The fundamental idea is to optimize the interactions between each pair of contacting helices while ignoring the other 5 and then to estimate the energies of all 35 million combinations using these pair-wise interactions. This BiHelix approach dramatically reduces the effort to examine the complete set of conformations and correctly identifies the crystal packing for the experimental structures plus other near-native packings we believe may play an important role in activation. This approach also enables a detailed structural analysis of functionally distinct conformations using helix-helix interaction energy landscapes and should be useful for other helical transmembrane proteins as well.

Structure-based prediction of subtype selectivity of histamine H3 receptor selective antagonists in clinical trials

Histamine receptors (HRs) are excellent drug targets for the treatment of diseases, such as schizophrenia, psychosis, depression, migraine, allergies, asthma, ulcers, and hypertension. Among them, the human H(3) histamine receptor (hH(3)HR) antagonists have been proposed for specific therapeutic applications, including treatment of Alzheimer's disease, attention deficit hyperactivity disorder (ADHD), epilepsy, and obesity. However, many of these drug candidates cause undesired side effects through the cross-reactivity with other histamine receptor subtypes. In order to develop improved selectivity and activity for such treatments, it would be useful to have the three-dimensional structures for all four HRs. We report here the predicted structures of four HR subtypes (H(1), H(2), H(3), and H(4)) using the GEnSeMBLE (GPCR ensemble of structures in membrane bilayer environment) Monte Carlo protocol, sampling ∼35 million combinations of helix packings to predict the 10 most stable packings for each of the four subtypes. Then we used these 10 best protein structures with the DarwinDock Monte Carlo protocol to sample ∼50 000 × 10(20) poses to predict the optimum ligand-protein structures for various agonists and antagonists. We find that E206(5.46) contributes most in binding H(3) selective agonists (5, 6, 7) in agreement with experimental mutation studies. We also find that conserved E5.46/S5.43 in both of hH(3)HR and hH(4)HR are involved in H(3)/ H(4) subtype selectivity. In addition, we find that M378(6.55) in hH(3)HR provides additional hydrophobic interactions different from hH(4)HR (the corresponding amino acid of T323(6.55) in hH(4)HR) to provide additional subtype bias. From these studies, we developed a pharmacophore model based on our predictions for known hH(3)HR selective antagonists in clinical study [ABT-239 1, GSK-189,254 2, PF-3654746 3, and BF2.649 (tiprolisant) 4] that suggests critical selectivity directing elements are: the basic proton interacting with D114(3.32), the spacer, the aromatic ring substituted with the hydrophilic or lipophilic groups interacting with lipophilic pockets in transmembranes (TMs) 3-5-6 and the aliphatic ring located in TMs 2-3-7. These 3D structures for all four HRs should help guide the rational design of novel drugs for the subtype selective antagonists and agonists with reduced side effects.

Elucidating glycosaminoglycan-protein-protein interactions using carbohydrate microarray and computational approaches

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan-protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan-protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan-protein-protein interactions, as well as a molecular-level understanding of those complexes.

Predicted structures of agonist and antagonist bound complexes of adenosine A3 receptor

We used the GEnSeMBLE Monte Carlo method to predict ensemble of the 20 best packings (helix rotations and tilts) based on the neutral total energy (E) from a vast number (10 trillion) of potential packings for each of the four subtypes of the adenosine G protein-coupled receptors (GPCRs), which are involved in many cytoprotective functions. We then used the DarwinDock Monte Carlo methods to predict the binding pose for the human A(3) adenosine receptor (hAA(3)R) for subtype selective agonists and antagonists. We found that all four A(3) agonists stabilize the 15th lowest conformation of apo-hAA(3)R while also binding strongly to the 1st and 3rd. In contrast the four A(3) antagonists stabilize the 2nd or 3rd lowest conformation. These results show that different ligands can stabilize different GPCR conformations, which will likely affect function, complicating the design of functionally unique ligands. Interestingly all agonists lead to a trans χ1 angle for W6.48 that experiments on other GPCRs associate with G-protein activation while all 20 apo-AA(3)R conformations have a W6.48 gauche+ χ1 angle associated experimentally with inactive GPCRs for other systems. Thus docking calculations have identified critical ligand-GPCR structures involved with activation. We found that the predicted binding site for selective agonist Cl-IB-MECA to the predicted structure of hAA(3)R shows favorable interactions to three subtype variable residues, I253(6.58), V169(EL2), and Q167(EL2), while the predicted structure for hAA(2A)R shows weakened to the corresponding amino acids: T256(6.58), E169(EL2), and L167(EL2), explaining the observed subtype selectivity.

Predicted structures and dynamics for agonists and antagonists bound to serotonin 5-HT2B and 5-HT2C receptors

Subtype 2 serotonin (5-hydroxytryptamine, 5-HT) receptors are major drug targets for schizophrenia, feeding disorders, perception, depression, migraines, hypertension, anxiety, hallucinogens, and gastrointestinal dysfunctions. (1) We report here the predicted structure of 5-HT2B and 5-HT2C receptors bound to highly potent and selective 5-HT2B antagonist PRX-08066 3, (pKi: 30 nM), including the key binding residues [V103 (2.53), L132 (3.29), V190 (4.60), and L347 (6.58)] determining the selectivity of binding to 5-HT2B over 5-HT2A. We also report structures of the endogenous agonist (5-HT) and a HT2B selective antagonist 2 (1-methyl-1-1,6,7,8-tetrahydro-pyrrolo[2,3-g]quinoline-5-carboxylic acid pyridine-3-ylamide). We examine the dynamics for the agonist- and antagonist-bound HT2B receptors in explicit membrane and water finding dramatically different patterns of water migration into the NPxxY motif and the binding site that correlates with the stability of ionic locks in the D(E)RY region.

Importance of receptor flexibility in binding of cyclam compounds to the chemokine receptor CXCR4

We have elucidated the binding sites of four moncyclam and one bicyclam antagonist AMD3100, in the human chemokine receptor CXCR4. Using the predicted structural models of CXCR4, we have further predicted the binding sites of these cyclam compounds. We used the computational method LITiCon to map the differences in receptor structure stabilized by the mono and bicyclam compounds. Accounting for the receptor flexibility lead to a single binding mode for the cyclam compounds, that has not been possible previously using a single receptor structural model and fixed receptor docking algorithms. There are several notable differences in the receptor conformations stabilized by monocyclam antagonist compared to a bicylam antagonist. The loading of the Cu(2+) ions in the cyclam compounds, shrinks the size of the cyclam rings and the residue D262(6.58) plays an important role in bonding to the copper ion in the monocylam compounds while residue E288(7.39) is important for the bicyclam compound.

Structural insights into conformational stability of wild-type and mutant beta1-adrenergic receptor

Recent experiments to derive a thermally stable mutant of turkey beta-1-adrenergic receptor (beta1AR) have shown that a combination of six single point mutations resulted in a 20 degrees C increase in thermal stability in mutant beta1AR. Here we have used the all-atom force-field energy function to calculate a stability score to detect stabilizing point mutations in G-protein coupled receptors. The calculated stability score shows good correlation with the measured thermal stability for 76 single point mutations and 22 multiple mutants in beta1AR. We have demonstrated that conformational sampling of the receptor for various mutants improve the prediction of thermal stability by 50%. Point mutations Y227A5.58, V230A5.61, and F338M7.48 in the thermally stable mutant m23-beta1AR stabilizes key microdomains of the receptor in the inactive conformation. The Y227A5.58 and V230A5.61 mutations stabilize the ionic lock between R139(3.50) on transmembrane helix3 and E285(6.30) on transmembrane helix6. The mutation F338M7.48 on TM7 alters the interaction of the conserved motif NPxxY(x)5,6F with helix8 and hence modulates the interaction of TM2-TM7-helix8 microdomain. The D186-R317 salt bridge (in extracellular loops 2 and 3) is stabilized in the cyanopindolol-bound wild-type beta1AR, whereas the salt bridge between D184-R317 is preferred in the mutant m23. We propose that this could be the surrogate to a similar salt bridge found between the extracellular loop 2 and TM7 in beta2AR reported recently. We show that the binding energy difference between the inactive and active states is less in m23 compared to the wild-type, which explains the activation of m23 at higher norepinephrine concentration compared to the wild-type. Results from this work throw light into the mechanism behind stabilizing mutations. The computational scheme proposed in this work could be used to design stabilizing mutations for other G-protein coupled receptors.

Experimental validation of the predicted binding site of Escherichia coli K1 outer membrane protein A to human brain microvascular endothelial cells: identification of critical mutations that prevent E. coli meningitis

Escherichia coli K1, the most common cause of meningitis in neonates, has been shown to interact with GlcNAc1-4GlcNAc epitopes of Ecgp96 on human brain microvascular endothelial cells (HBMECs) via OmpA (outer membrane protein A). However, the precise domains of extracellular loops of OmpA interacting with the chitobiose epitopes have not been elucidated. We report the loop-barrel model of these OmpA interactions with the carbohydrate moieties of Ecgp96 predicted from molecular modeling. To test this model experimentally, we generated E. coli K1 strains expressing OmpA with mutations of residues predicted to be critical for interaction with the HBMEC and tested E. coli invasion efficiency. For these same mutations, we predicted the interaction free energies (including explicit calculation of the entropy) from molecular dynamics (MD), finding excellent correlation (R(2) = 90%) with experimental invasion efficiency. Particularly important is that mutating specific residues in loops 1, 2, and 4 to alanines resulted in significant inhibition of E. coli K1 invasion in HBMECs, which is consistent with the complete lack of binding found in the MD simulations for these two cases. These studies suggest that inhibition of the interactions of these residues of Loop 1, 2, and 4 with Ecgp96 could provide a therapeutic strategy to prevent neonatal meningitis due to E. coli K1.

Prediction of the three-dimensional structure for the rat urotensin II receptor, and comparison of the antagonist binding sites and binding selectivity between human and rat receptors from atomistic simulations

Urotensin-II (U-II) has been shown to be the most potent mammalian vasoconstrictor known. Thus, a U-II antagonist might be of therapeutic value in a number of cardiovascular disorders. However, interspecies variability of several nonpeptidic ligands complicates the interpretation of in vivo studies of such antagonists in preclinical animal disease models. ACT058362 is a selective antagonist for the human U-II receptor (hUT2R) with a reported K(d) value of approximately 4 nM in a molecular binding assay, but it is reported to bind weakly to rat UT2R (rUT2R), with a K(d) value of approximately 1 500 nM. In contrast, the arylsulphonamide SB706375 is a selective antagonist against both hUT2R (K(d)= approximately 9 nM) and rUT2R (K(d)= approximately 21 nM). To understand the species selectivity of the UT2R, we investigated the binding site of ACT058362 and SB706375 in both hUT2R and rUT2R to explain the dramatically lower (approximately 400-fold) affinity of ACT058362 for rUT2R and the similar affinity (approximately 10 nM) of SB706375 for both UT2Rs. These studies used MembStruk and MSCDock to predict the UT2R structure and the binding site of ACT058362 and SB706375. Based on binding energies, we found two binding modes each with D130(3.32) as the crucial anchoring point (Ballesteros-Weinstein numbering given in superscript). We predict that ACT058362 (an aryl-amine-aryl or ANA ligand) binds in the transmembrane (TM) 3456 region, while SB706375 (an aryl-aryl-amine or AAN ligand) binds in the TM 1237 region. These predicted sites explain the known differences in binding of the ANA ligand to rat and human receptors, while explaining the similar binding of the AAN compound to rat and human receptors. Moreover the predictions explain currently available structure-activity relationship (SAR) data. To further validate the predicted binding sites of these ligands in hUT2R and rUT2R, we propose several mutations that would help define the structural origins of differential responses between UT2R of different species, potentially indicating novel UT2R antagonists with cross-species high affinity.

Computational mapping of the conformational transitions in agonist selective pathways of a G-protein coupled receptor

The active state conformation of a G-protein coupled receptor (GPCR) is influenced by the chemical structure and the efficacy of the bound ligand. Insight into the active state conformation as well as the activation pathway for ligands with different efficacies is critical in designing functionally specific drugs for GPCRs. Starting from the crystal structure of the beta2-adrenergic receptor, we have used coarse grain computational methods to understand the modulation of the potential energy landscape of the receptor by two full agonists, two partial agonists, and an inverse agonist. Our coarse grain method involves a systematic conformational spanning of the receptor transmembrane helices followed by an energy minimization and ligand redocking in each sampled conformation. We have derived the activation pathways for several agonists and partial agonists, using a Monte Carlo algorithm, and these are in agreement with fluorescence spectroscopy measurements. The calculated pathways for the full agonists start with an energy downhill step leading to a stable intermediate followed by a barrier crossing leading to the active state. We find that the barrier crossing involves breaking of an interhelical hydrogen bond between helix5 and helix6, and polarization of the binding site residues by water facilitates the barrier crossing. The uphill step in the partial agonist salbutamol induced activation is distinct from full agonist norepinephrine, and originates from steric hindrance with the aromatic residues on helix6. Virtual ligand screening with the salbutamol-stabilized conformation shows enrichment of noncatechol agonists over the norepinephrine-stabilized conformation. Our computational method provides an unprecedented opportunity to derive hypotheses for experiments and also understand activation mechanisms in GPCRs.

Predicted 3D structures for adenosine receptors bound to ligands: comparison to the crystal structure

G protein-coupled receptors (GPCRs) are therapeutic targets for many diseases, but progress in developing active and selective therapeutics has been severely hampered by the difficulty in obtaining accurate structures. We have been developing methods for predicting the structures for GPCR ligand complexes, but validation has been hampered by a lack of experimental structures with which to compare our predictions. We report here the predicted structures of the human adenosine GPCR subtypes (A(1), A(2A), A(2B), and A(3)) and the binding sites for adenosine agonist and eight antagonists to this predicted structure, making no use of structural data, and compare with recent experimental crystal structure for ZM241385 bound human A(2A) receptor. The predicted structure correctly identifies 9 of the 12 crystal binding site residues. Moreover, the predicted binding energies of eight antagonists to the predicted structure of A(2A) correlate quite well with experiment. These excellent predictions resulted when we used Monte Carlo techniques to optimize the loop structures, particularly the cysteine linkages. Ignoring these linkages led to a much worse predicted binding site (identifying only 3 of the 12 important residues). These results indicate that computational methods can predict the three-dimensional structure of GPCR membrane proteins sufficiently accurately for use in designing subtype selective ligands for important GPCR therapeutics targets.