Molecular modeling of the second extracellular loop of G-protein coupled receptors and its implication on structure-based virtual screening

The current study describes the validation of high-throughput modeling procedures for the construction of the second extracellular loop (ecl2) of all nonolfactory human G Protein-coupled receptors. Our modeling flowchart is based on the alignment of essential residues determining the particular ecl2 fold observed in the bovine rhodopsin (bRho) crystal structure. For a set of GPCR targets, the dopamine D2 receptor (DRD2), adenosine A3 receptor (AA3R), and the thromboxane A2 receptor (TA2R), the implications of including ecl2 atomic coordinates is evaluated in terms of structure-based virtual screening accuracy: the suitability of the 3D models to distinguish between known antagonists and randomly chosen decoys using automated docking approaches. The virtual screening results of different models describing increasingly exhaustive receptor representations (seven helices only, seven helices and ecl2 loop, full model) have been compared. Explicit modeling of the ecl2 loop was found to be important in only one of three test cases whereas a loopless model was shown to be accurate enough in the two other receptors. An exhaustive comparison of ecl2 loops of 365 receptors to that of bRho suggests that explicit ecl2 loop modeling should be reserved to receptors where loop building can be guided by experimental restraints.     

Incorporation of evolutionary information into Rosetta comparative modeling

Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosetta's comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.     

PERMOL: restraint-based protein homology modeling using DYANA or CNS

SUMMARY: PERMOL is a new restraint-based program for homology modeling of proteins. Restraints are generated from the information contained in structures of homologous template proteins. Employing the restraints generated by PERMOL, three-dimensional structures are obtained using MD programs such as DYANA or CNS. In contrast to other programs PERMOL is mainly based on the use of dihedral angle information which is optimally suited to preserve the local secondary structure. The global arrangement of these elements is then facilitated by a small number of distance restraints. Using PERMOL homology, models of high quality are obtained. A key advantage of the proposed method is its flexibility, which allows the inclusion of data from other sources, such as experimental restraints and the use of modern molecular dynamics programs to calculate structures. AVAILABILITY: The software and a detailed manual are available free of charge (http://www.biologie.uni-regensburg.de/Biophysik/Kalbitzer/permol/permol.html)     

Crystal structure of squid rhodopsin with intracellularly extended cytoplasmic region

G-protein-coupled receptors play a key step in cellular signal transduction cascades by transducing various extracellular signals via G-proteins. Rhodopsin is a prototypical G-protein-coupled receptor involved in the retinal visual signaling cascade. We determined the structure of squid rhodopsin at 3.7A resolution, which transduces signals through the G(q) protein to the phosphoinositol cascade. The structure showed seven transmembrane helices and an amphipathic helix H8 has similar geometry to structures from bovine rhodopsin, coupling to G(t), and human beta(2)-adrenergic receptor, coupling to G(s). Notably, squid rhodopsin contains a well structured cytoplasmic region involved in the interaction with G-proteins, and this region is flexible or disordered in bovine rhodopsin and human beta(2)-adrenergic receptor. The transmembrane helices 5 and 6 are longer and extrude into the cytoplasm. The distal C-terminal tail contains a short hydrophilic alpha-helix CH after the palmitoylated cysteine residues. The residues in the distal C-terminal tail interact with the neighboring residues in the second cytoplasmic loop, the extruded transmembrane helices 5 and 6, and the short helix H8. Additionally, the Tyr-111, Asn-87, and Asn-185 residues are located within hydrogen-bonding distances from the nitrogen atom of the Schiff base.     

The predictive accuracy of secondary chemical shifts is more affected by protein secondary structure than solvent environment

Biomolecular NMR spectroscopy frequently employs estimates of protein secondary structure using secondary chemical shift (Δδ) values, measured as the difference between experimental and random coil chemical shifts (RCCS). Most published random coil data have been determined in aqueous conditions, reasonable for non-membrane proteins, but potentially less relevant for membrane proteins. Two new RCCS sets are presented here, determined in dimethyl sulfoxide (DMSO) and chloroform:methanol:water (4:4:1 by volume) at 298 K. A web-based program, CS-CHEMeleon, has been implemented to determine the accuracy of secondary structure assessment by calculating and comparing Δδ values for various RCCS datasets. Using CS-CHEMeleon, Δδ predicted versus experimentally determined secondary structures were compared for large datasets of membrane and non-membrane proteins as a function of RCCS dataset, Δδ threshold, nucleus, localized parameter averaging and secondary structure type. Optimized Δδ thresholds are presented both for published and for the DMSO and chloroform:methanol:water derived RCCS tables. Despite obvious RCCS variations between datasets, prediction of secondary structure was consistently similar. Strikingly, predictive accuracy seems to be most dependent upon the type of secondary structure, with helices being the most accurately predicted by Δδ values using five different RCCS tables. We suggest caution when using Δδ-based restraints in structure calculations as the underlying dataset may be biased. Comparative assessment of multiple RCCS datasets should be performed, and resulting Δδ-based restraints weighted appropriately relative to other experimental restraints.     

Determining the 3D structure of human ASC2 protein involved in apoptosis and inflammation

ASC2 structure has been well defined by 1141 NOE experimental restraints. The model consists of five alpha helices. alpha-Helices are connected by short random structure loops. The sole exception is the loop connecting helices 2 and 3, which has a 20-residue length. Folding generally agrees with the folding of recently published death domain structures in which alpha-helix structures have been reported. In spite of structural similarity, amino acid sequence homology with the most similar protein (ASC1) is just 64%. DD, DED, and CASP protein structures present six helices along their sequences; ASC2 presents 5 well-defined helices due to long distance restraints. However, a helical fragment was observed between amino acids 38 and 42 (representing helix 3) in the death domains when constructing the model.     

Crystal structure of rhodopsin: implications for vision and beyond

A heptahelical transmembrane bundle is a common structural feature of G-protein-coupled receptors (GPCRs) and bacterial retinal-binding proteins, two functionally distinct groups of membrane proteins. Rhodopsin, a photoreceptor protein involved in photopic (rod) vision, is a prototypical GPCR that contains 11-cis-retinal as its intrinsic chromophore ligand. Therefore, uniquely, rhodopsin is a GPCR and also a retinal-binding protein, but is not found in bacteria. Rhodopsin functions as a typical GPCR in processes that are triggered by light and photoisomerization of its ligand. Bacteriorhodopsin is a light-driven proton pump with an all-trans-retinal chromophore that photoisomerizes to 13-cis-retinal. The recent crystal structure determination of bovine rhodopsin revealed a structure that is not similar to previously established bacteriorhodopsin structures. Both groups of proteins have a heptahelical transmembrane bundle structure, but the helices are arranged differently. The activation of rhodopsin involves rapid cis-trans photoisomerization of the chromophore, followed by slower and incompletely defined structural rearrangements. For rhodopsin and related receptors, a common mechanism is predicted for the formation of an active state intermediate that is capable of interacting with G proteins.     

TOUCHSTONEX: protein structure prediction with sparse NMR data

TOUCHSTONEX, a new method for folding proteins that uses a small number of long-range contact restraints derived from NMR experimental NOE (nuclear Overhauser enhancement) data, is described. The method employs a new lattice-based, reduced model of proteins that explicitly represents C(alpha), C(beta), and the sidechain centers of mass. The force field consists of knowledge-based terms to produce protein-like behavior, including various short-range interactions, hydrogen bonding, and one-body, pairwise, and multibody long-range interactions. Contact restraints were incorporated into the force field as an NOE-specific pairwise potential. We evaluated the algorithm using a set of 125 proteins of various secondary structure types and lengths up to 174 residues. Using N/8 simulated, long-range sidechain contact restraints, where N is the number of residues, 108 proteins were folded to a C(alpha)-root-mean-square deviation (RMSD) from native below 6.5 A. The average RMSD of the lowest RMSD structures for all 125 proteins (folded and unfolded) was 4.4 A. The algorithm was also applied to limited experimental NOE data generated for three proteins. Using very few experimental sidechain contact restraints, and a small number of sidechain-main chain and main chain-main chain contact restraints, we folded all three proteins to low-to-medium resolution structures. The algorithm can be applied to the NMR structure determination process or other experimental methods that can provide tertiary restraint information, especially in the early stage of structure determination, when only limited data are available.     

Comparison of the transmembrane helices of bovine rhodopsin in the crystal structure and the C α template based on cryo-electron microscopy maps and sequence analysis of the G protein-coupled receptors

G protein-coupled receptors (GPCR) are activated by a diverse array of extracellular signals, ranging from light to polypeptide molecules. The receptors propagate these signals intracellularly using G protein secondary messenger pathways. A common feature in the architecture of these receptors is their seven transmembrane domains. The first crystal structure of a GPCR, bovine rhodopsin, has recently been solved at 2.8 Å. We compared the seven membrane-spanning helices (TMH) from the crystal structure of bovine rhodopsin with those from the low-resolution model of bovine rhodopsin based on the cryo-electron microscopy structure of frog rhodopsin developed by Dr Joyce Baldwin. The model developed by Baldwin used a consensus sequence approach to predict the rotational position of each helix with respect to the other six helices. Superposition of the entire helix bundle of the Baldwin model with the crystal structure gave a RMS difference (RMSD) of 3.2 Å for the 198 C f atoms which suggests a high level of similarity in the arrangement of the helices. Except for TMH IV (RMSD of 4.0 Å), the position of corresponding helices within the helix bundle overlapped well. The superposition of individual helices showed that the RMSD values over 3 Å in the global superposition were largely due to one or more of the following: (i) differences in the unraveling and kinks for these helices, (ii) translation of TMH perpendicular to the membrane and (iii) rotation of helices up to 31°, except for TMH IV in which an additional contribution to the RMSD came from the aforementioned observation. As other crystal structures of GPCRs become available, a comparison with the Baldwin consensus model may reveal larger differences than those observed here.     

The three-dimensional structure of bovine rhodopsin determined by electron cryomicroscopy

G-protein-coupled receptors are integral membrane proteins that respond to environmental signals and initiate signal transduction pathways, which activate cellular processes. Rhodopsin, a well known member of the G-protein-coupled receptor family, is located in the disk membranes of the rod outer segment, where it is responsible for the visualization of dim light. Rhodopsin is the most extensively studied G-protein-coupled receptor, and knowledge about its structure serves as a template for other related receptors. We have gained detailed structural knowledge from the crystal structure (1), which was solved by x-ray crystallography in 2000 using three-dimensional crystals. Here we report a three-dimensional density map of bovine rhodopsin determined by electron cryomicroscopy of two-dimensional crystals with p22(1)2(1) symmetry. The usage of relatively small and disordered crystals made the process of structure determination challenging. Special attention was paid to the extraction of amplitudes and phases, since usable raw data were limited to a maximum tilt of 45 degrees. In the refinement process, an improved unbending procedure was applied. This led to a final resolution of 5.5 A in the membrane plane and approximately 13 A perpendicular to it, making our electron density map the most accurate map of a G-protein-coupled receptor currently available by electron microscopy. Most important is the information we gain about the center of the membrane plane and the orientation of the molecule relative to the bilayer. This information cannot be retrieved from the three-dimensional crystals. In our electron density map, all seven transmembrane helices were identified, and their arrangement is in agreement with the arrangement known from the crystal structure (1). In the retinal binding pocket, a density peak adjacent to helix 3 suggests the position of the beta-ionine ring of the chromophore, and in its vicinity several of the bigger amino acids can be identified.     

GENFOLD: a genetic algorithm for folding protein structures using NMR restraints.

We report the development and validation of the program GENFOLD, a genetic algorithm that calculates protein structures using restraints obtained from NMR, such as distances derived from nuclear Overhauser effects, and dihedral angles derived from coupling constants. The program has been tested on three proteins: the POU domain (a small three-helix DNA-binding protein), bovine pancreatic trypsin inhibitor (BPTI), and the starch-binding domain from Aspergillus niger glucoamylase I, a 108-residue beta-sheet protein. Structures were calculated for each protein using published NMR restraints. In addition, structures were calculated for BPTI using artificial restraints generated from a high-resolution crystal structure. In all cases the fittest calculated structures were close to the target structure, and could be refined to structures indistinguishable from the target structures by means of a low-temperature simulated annealing refinement. The effectiveness of the program is similar to that of distance geometry and simulated annealing methods, and it is capable of using a very wide range of restraints as input. It can thus be readily extended to the calculation of structures of large proteins, for which few NOE restraints may be available.     

Ensemble modeling of protein disordered states: Experimental restraint contributions and validation

Disordered states of proteins include the biologically functional intrinsically disordered proteins and the unfolded states of normally folded proteins. In recent years, ensemble‐modeling strategies using various experimental measurements as restraints have emerged as powerful means for structurally characterizing disordered states. However, these methods are still in their infancy compared with the structural determination of folded proteins. Here, we have addressed several issues important to ensemble modeling using our ENSEMBLE methodology. First, we assessed how calculating ensembles containing different numbers of conformers affects their structural properties. We find that larger ensembles have very similar properties to smaller ensembles fit to the same experimental restraints, thus allowing a considerable speed improvement in our calculations. In addition, we analyzed the contributions of different experimental restraints to the structural properties of calculated ensembles, enabling us to make recommendations about the experimental measurements that should be made for optimal ensemble modeling. The effects of different restraints, most significantly from chemical shifts, paramagnetic relaxation enhancements and small‐angle X‐ray scattering, but also from other data, underscore the importance of utilizing multiple sources of experimental data. Finally, we validate our ENSEMBLE methodology using both cross‐validation and synthetic experimental restraints calculated from simulated ensembles. Our results suggest that secondary structure and molecular size distribution can generally be modeled very accurately, whereas the accuracy of calculated tertiary structure is dependent on the number of distance restraints used. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Iterative assembly of helical proteins by optimal hydrophobic packing

We present a method for the computer-based iterative assembly of native-like tertiary structures of helical proteins from alpha-helical fragments. For any pair of helices, our method, called MATCHSTIX, first generates an ensemble of possible relative orientations of the helices with various ways to form hydrophobic contacts between them. Those conformations having steric clashes, or a large radius of gyration of hydrophobic residues, or with helices too far separated to be connected by the intervening linking region, are discarded. Then, we attempt to connect the two helical fragments by using a robotics-based loop-closure algorithm. When loop closure is feasible, the algorithm generates an ensemble of viable interconnecting loops. After energy minimization and clustering, we use a representative set of conformations for further assembly with the remaining helices, adding one helix at a time. To efficiently sample the conformational space, the order of assembly generally proceeds from the pair of helices connected by the shortest loop, followed by joining one of its adjacent helices, always proceeding with the shorter connecting loop. We tested MATCHSTIX on 28 helical proteins each containing up to 5 helices and found it to heavily sample native-like conformations. The average rmsd of the best conformations for the 17 helix-bundle proteins that have 2 or 3 helices is less than 2 A; errors increase somewhat for proteins containing more helices. Native-like states are even more densely sampled when disulfide bonds are known and imposed as restraints. We conclude that, at least for helical proteins, if the secondary structures are known, this rapid rigid-body maximization of hydrophobic interactions can lead to small ensembles of highly native-like structures. It may be useful for protein structure prediction.     

Computer modelling of kappa carrageenam-mannan interactions

Molecular modelling has been used as a theoretical approach to investigate the kappa carrageenan structure and its interaction with mannan chains. Calculations revealed the existence of six minima for the kappa carrageenan structure in solution. Two of them were very close to the structure found in the solid state. The methodology allowed the calculation of the theoretical counterpart of the structures based on x-ray fibre diffractions studies. In the second step of this study, we have shown that there is the possibility of interactions between kappa carrageenan double helices and mannan chains. This interacting process is allowed by the flexibility of the mannan chains and structural changes of the kappa carrageenan double helices. The calculations suggest that the disaccaride mannan fragment might be required for recognition. The result of our investigation are in good agreement with a model of gel structure based on experimental data. This approach could be applied to simulate and predict other associations in molecular assemblies.     

Modeling of the structure of bacteriorhodopsin. A molecular dynamics study.

Secondary structure predictions for membrane proteins are relatively reliable and permit the construction of model structures that may serve as initial conformations for molecular dynamics simulations. This might provide a scheme to predict the three-dimensional structures of membrane proteins. The feasibility of such an approach is tested for bacteriorhodopsin. We were not able to fully predict the kidney-shaped structure of bacteriorhodopsin. However, features compatible with this structure developed in a simulation starting from a circular arrangement of the seven predicted helices. When instead we started from the kidney shape, assigning the seven predicted helices in different ways to those on the structure, we could distinguish between the different assignments on the basis of energy and tilt of the helices. In this way we could select the correct assignment from a few others. For the correct assignment, the helices spontaneously adopted a tilt that agrees remarkably well with the experimental model structure derived by others. The root-mean-square deviation between our best molecular dynamics structure and the experimental model structure is 3.8 A, caused mainly by deviations in the internal degrees of freedom of the helices.     

Solution structure of alpha t alpha, a helical hairpin peptide of de novo design.

alpha t alpha is a 38-residue peptide designed to adopt a helical hairpin conformation in solution (Fezoui Y, Weaver DL Osterhout JJ, 1995, Protein Sci 4:286-295). A previous study of the carboxylate form of alpha t alpha by CD and two-dimensional NMR indicated that the peptide was highly helical and that the helices associated in approximately the intended orientation (Fezoui Y, Weaver DL, Osterhout JJ, 1994, Proc Natl Acad Sci USA 91:3675-3679). Here, the solution structure of alpha t alpha as determined by two-dimensional NMR is reported. A total of 266 experimentally derived distance restraints and 20 dihedral angle restraints derived from J-couplings were used. One-hundred initial structures were generated by distance geometry and refined by dynamical simulated annealing. Twenty-three of the lowest-energy structures consistent with the experimental restraints were analyzed. The results presented here show that alpha t alpha is comprised of two associating helices connected by a turn region.     

Comparative Sequence and Structural Analyses of G-Protein-Coupled Receptor Crystal Structures and Implications for Molecular Models

Background

Up until recently the only available experimental (high resolution) structure of a G-protein-coupled receptor (GPCR) was that of bovine rhodopsin. In the past few years the determination of GPCR structures has accelerated with three new receptors, as well as squid rhodopsin, being successfully crystallized. All share a common molecular architecture of seven transmembrane helices and can therefore serve as templates for building molecular models of homologous GPCRs. However, despite the common general architecture of these structures key differences do exist between them. The choice of which experimental GPCR structure(s) to use for building a comparative model of a particular GPCR is unclear and without detailed structural and sequence analyses, could be arbitrary. The aim of this study is therefore to perform a systematic and detailed analysis of sequence-structure relationships of known GPCR structures.

Methodology

We analyzed in detail conserved and unique sequence motifs and structural features in experimentally-determined GPCR structures. Deeper insight into specific and important structural features of GPCRs as well as valuable information for template selection has been gained. Using key features a workflow has been formulated for identifying the most appropriate template(s) for building homology models of GPCRs of unknown structure. This workflow was applied to a set of 14 human family A GPCRs suggesting for each the most appropriate template(s) for building a comparative molecular model.

Conclusions

The available crystal structures represent only a subset of all possible structural variation in family A GPCRs. Some GPCRs have structural features that are distributed over different crystal structures or which are not present in the templates suggesting that homology models should be built using multiple templates. This study provides a systematic analysis of GPCR crystal structures and a consistent method for identifying suitable templates for GPCR homology modelling that will help to produce more reliable three-dimensional models.     

Assembly of protein structure from sparse experimental data: An efficient Monte Carlo model

A new, efficient method for the assembly of protein tertiary structure from known, loosely encoded secondary structure restraints and sparse information about exact side chain contacts is proposed and evaluated. The method is based on a new, very simple method for the reduced modeling of protein structure and dynamics, where the protein is described as a lattice chain connecting side chain centers of mass rather than Cαs. The model has implicit built-in multibody correlations that simulate short- and long-range packing preferences, hydrogen bonding cooperativity and a mean force potential describing hydrophobic interactions. Due to the simplicity of the protein representation and definition of the model force field, the Monte Carlo algorithm is at least an order of magnitude faster than previously published Monte Carlo algorithms for structure assembly. In contrast to existing algorithms, the new method requires a smaller number of tertiary restraints for successful fold assembly; on average, one for every seven residues as compared to one for every four residues. For example, for smaller proteins such as the B domain of protein G, the resulting structures have a coordinate root mean square deviation (cRMSD), which is about 3 Å from the experimental structure; for myoglobin, structures whose backbone cRMSD is 4.3 Å are produced, and for a 247-residue TIM barrel, the cRMSD of the resulting folds is about 6 Å. As would be expected, increasing the number of tertiary restraints improves the accuracy of the assembled structures. The reliability and robustness of the new method should enable its routine application in model building protocols based on various (very sparse) experimentally derived structural restraints. Proteins 32:475–494, 1998. © 1998 Wiley-Liss, Inc.     

Modeling of the three-dimensional structure of polypeptides in solution using potential-scaled/hot-solute molecular dynamics.

We present here an efficient and accurate procedure for modeling of the three-dimensional structures of polypeptides in the explicit solvent water based on molecular dynamics calculations. Using the toxic domain analog of heat-stable enterotoxin as a model peptide, we examined the utilities of two molecular dynamics techniques with the system containing the explicit solvent. One is the potential-scaled molecular dynamics that had been designed for effective conformational analyses of biomolecules with the explicit solvent water by partially scaling down the potential energies involved in the solute molecules. The other is the variation of Berendsen's weak coupling method (referred to as "hot-solute" method), in which only the solute of the system is heated to a high temperature while the solvent is kept at a normal temperature. Each method successfully increased the rate of folding of the peptides, and the most effective was a combination of the two methods. Moreover, the final structure obtained via cooling process successfully reproduced the experimentally known structure from the extended amino acid sequence using only the distance restraints representing three disulfide bonds in the peptide. Additional distance restraints derived from some of the NOE cross peaks accelerated the folding of the peptide, but gave almost the same structure as in the case without these additional restraints. Because a similar calculation without the explicit solvent could not reproduce the known structure, it is suggested that the explicit solvent water could play an important role in the modeling. The methods presented here have the potential for accurate modeling even when less experimental information was available.     

Using experimental information to produce a model of the transmembrane domain of the ion channel phospholamban.

Molecular models of the transmembrane domain of the phospholamban pentamer have been generated by a computational method that uses the experimentally measured effects of systematic single-site mutations as a guiding force in the modeling procedure. This method makes the assumptions that 1) the phospholamban transmembrane domain is a parallel five-helix bundle, and 2) nondisruptive mutation positions are lipid exposed, whereas 3) disruptive or partially disruptive mutations are not. Our procedure requires substantially less computer time than systematic search methods, allowing rapid assessment of the effects of different experimental results on the helix arrangement. The effectiveness of the approach is investigated in test calculations on two helix-dimer systems of known structure. Two independently derived sets of mutagenesis data were used to define the restraints for generating models of phospholamban. Both resulting models are left-handed, highly symmetrical pentamers. Although the overall bundle geometry is very similar in the two models, the orientation of individual helices differs by approximately 50 degrees, resulting in different sets of residues facing the pore. This demonstrates how differences in restraints can have an effect on the model structures generated, and how the violation of these restraints can identify inconsistent experimental data.