There is considerable interest in determining the activation mechanism of G proteincoupled 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-principlesbased 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 TM31TM6 and TM21TM6 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 TM31TM6 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.Keywords: protein structure prediction; G protein binding; computational methods; conformational ensemble Abbreviations: actHA 2A AR, active human A 2A adenosine receptor; actHb 2 AR, active human b 2 adrenergic receptor; actTb 1 AR, active turkey (Meleagris gallopavo) b 1 adrenergic receptor; bOps, bovine opsin; bRho, bovine rhodopsin; CB1, human cannabinoid 1 receptor; CB2, human cannabinoid 2 receptor; EC2, extracellular loop 2; GEnSeMBLE, GPCR Ensemble of Structures in Membrane Bilayer Environment; GPCR, G-protein coupled receptor; GTPcS, guanosine 5 0 -O-(3-thiotriphosophate); hCXCR4, human chemokine CXCR4 receptor; HEK, human embryonic kidney; hDD3R, human dopamine D3 receptor; hH1HR, human H1 Histamine receptor; hOPRK, human j-opioid receptor; hOPRX, human NOP opioid receptor; hS1P1R, human sphingosine 1-phosphate 1 receptor; IC2, intracellular loop 2; IC3, intracellular loop 3; inactHA 2A AR, inactive human A 2A adenosine receptor; inactHb 2 AR, inactive human b 2 adrenergic receptor; inactTb 1 AR, inactive turkey b 1 adrenergic receptor; meta II, bovine metarhodopsin II; mOPRD, mouse (Mus musculus) d-opioid receptor; mOPRM, mouse (Mus musculus) l-opioid receptor; PDB ID, protein data bank identification number; SCREAM, Side Chain Rotamer Excitation Analysis Method; sRho, squid (Todarodes pacificus) rhodopsin; T m , temperature midpoint of denaturation curve; TM, transmembrane.

Parvalbumin (PV) is a globular calcium (Ca(2+))-selective protein expressed in a variety of biological tissues. Our computational studies of the rat β-parvalbumin (β-PV) isoform seek to elucidate the molecular thermodynamics of Ca(2+) versus magnesium (Mg(2+)) binding at the protein's two EF-hand motifs. Specifically, we have utilized molecular dynamics (MD) simulations and a mean-field electrolyte model (mean spherical approximation (MSA) theory) to delineate how the EF-hand scaffold controls the "local" thermodynamics of Ca(2+) binding selectivity over Mg(2+). Our MD simulations provide the probability density of metal-chelating oxygens within the EF-hand scaffolds for both Ca(2+) and Mg(2+), as well the conformational strain induced by Mg(2+) relative to Ca(2+) binding. MSA theory utilizes the binding domain oxygen and charge distributions to predict the chemical potential of ion binding, as well as their corresponding concentrations within the binding domain. We find that the electrostatic and steric contributions toward ion binding were similar for Mg(2+) and Ca(2+), yet the latter was 5.5 kcal/mol lower in enthalpy when internal strain within the EF hand was considered. We therefore speculate that beyond differences in dehydration energies for the Ca(2+) versus Mg(2+), strain induced in the β-PV EF hand by cation binding significantly contributes to the nearly 10,000-fold difference in binding affinity reported in the literature. We further complemented our analyses of local factors governing cation binding selectivity with whole-protein (global) contributions, such as interhelical residue-residue contacts and solvent exposure of hydrophobic surface. These contributions were found to be comparable for both Ca(2+)- and Mg(2+)-bound β-PV, which may implicate local factors, EF-hand strain, and dehydration, in providing the primary means of selectivity. We anticipate these methods could be used to estimate metal binding thermodynamics across a broad range of PV sequence homologues and EF-hand-containing, Ca(2+) binding proteins.

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.protein structure prediction | A 2A adenosine receptor | β 2 -adrenergic receptor | constitutive activity | functional selectivity

Cytosolic crowding can influence the thermodynamics and kinetics of in vivo chemical reactions. Most significantly, proteins and nucleic acid crowders reduce the accessible volume fraction, ϕ, available to a diffusing substrate, thereby reducing its effective diffusion rate, Deff, relative to its rate in bulk solution. However, Deff can be further hindered or even enhanced, when long-range crowder/diffuser interactions are significant. To probe these effects, we numerically estimated Deff values for small, charged molecules in representative, cytosolic protein lattices up to 0.1 × 0.1 × 0.1 μm(3) in volume via the homogenized Smoluchowski electro-diffusion equation. We further validated our predictions against Deff estimates from ϕ-dependent analytical relationships, such as the Maxwell-Garnett (MG) bound, as well as explicit solutions of the time-dependent electro-diffusion equation. We find that in typical, moderately crowded cell cytoplasm (ϕ ≈ 0.8), Deff is primarily determined by ϕ; in other words, diverse protein shapes and heterogeneous distributions only modestly impact Deff. However, electrostatic interactions between diffusers and crowders, particularly at low electrolyte ionic strengths, can substantially modulate Deff. These findings help delineate the extent that cytoplasmic crowders influence small molecule diffusion, which ultimately may shape the efficiency and timing of intracellular signaling pathways. More generally, the quantitative agreement between computationally expensive solutions of the time-dependent electro-diffusion equation and its comparatively cheaper homogenized form suggest that the latter is a broadly effective model for diffusion in wide-ranging, crowded biological media.

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.