Modeling the possible conformations of the extracellular loops in G-protein-coupled receptors

Structure prediction of the second extracellular loop in G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

Insights into the mechanism of C5aR inhibition by PMX53 via implicit solvent molecular dynamics simulations and docking

Background

The complement protein C5a acts by primarily binding and activating the G-protein coupled C5a receptor C5aR (CD88), and is implicated in many inflammatory diseases. The cyclic hexapeptide PMX53 (sequence Ace-Phe-[Orn-Pro-dCha-Trp-Arg]) is a full C5aR antagonist of nanomolar potency, and is widely used to study C5aR function in disease.

Results

We construct for the first time molecular models for the C5aR:PMX53 complex without the a priori use of experimental constraints, via a computational framework of molecular dynamics (MD) simulations, docking, conformational clustering and free energy filtering. The models agree with experimental data, and are used to propose important intermolecular interactions contributing to binding, and to develop a hypothesis for the mechanism of PMX53 antagonism.

Conclusion

This work forms the basis for the design of improved C5aR antagonists, as well as for atomic-detail mechanistic studies of complement activation and function. Our computational framework can be widely used to develop GPCR-ligand structural models in membrane environments, peptidomimetics and other chemical compounds with potential clinical use.

Modelling three-dimensional protein structures for applications in drug design

A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.

Assessment and challenges of ligand docking into comparative models of G-protein coupled receptors

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 10³ fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes.

Prediction of Long Loops with Embedded Secondary Structure using the Protein Local Optimization Program

Robust homology modeling to atomic-level accuracy requires in the general case successful prediction of protein loops containing small segments of secondary structure. Further, as loop prediction advances to success with larger loops, the exclusion of loops containing secondary structure becomes awkward. Here, we extend the applicability of the Protein Local Optimization Program (PLOP) to loops up to 17 residues in length that contain either helical or hairpin segments. In general, PLOP hierarchically samples conformational space and ranks candidate loops with a high-quality molecular mechanics force field. For loops identified to possess α-helical segments, we employ an alternative dihedral library composed of (ϕ,ψ) angles commonly found in helices. The alternative library is searched over a user-specified range of residues that define the helical bounds. The source of these helical bounds can be from popular secondary structure prediction software or from analysis of past loop predictions where a propensity to form a helix is observed. Due to the maturity of our energy model, the lowest energy loop across all experiments can be selected with an accuracy of sub-Ångström RMSD in 80% of cases, 1.0 to 1.5 Å RMSD in 14% of cases, and poorer than 1.5 Å RMSD in 6% of cases. The effectiveness of our current methods in predicting hairpin-containing loops is explored with hairpins up to 13 residues in length and again reaching an accuracy of sub-Ångström RMSD in 83% of cases, 1.0 to 1.5 Å RMSD in 10% of cases, and poorer than 1.5 Å RMSD in 7% of cases. Finally, we explore the effect of an imprecise surrounding environment, in which side chains, but not the backbone, are initially in perturbed geometries. In these cases, loops perturbed to 3Å RMSD from the native environment were restored to their native conformation with sub-Ångström RMSD.

Towards the miniaturization of GPCR-based live-cell screening assays

G protein-coupled receptors (GPCRs) play a key role in many physiological or disease-related processes and for this reason are favorite targets of the pharmaceutical industry. Although ~30% of marketed drugs target GPCRs, their potential remains largely untapped. The discovery of new leads calls for the screening of thousands of compounds with high-throughput cell-based assays. Although microtiter plate-based high-throughput screening platforms are well established, microarray and microfluidic technologies hold potential for miniaturization, automation, and biosensor integration that may well redefine the format of GPCR screening assays. This paper reviews the latest research efforts directed to bringing microarray and microfluidic technologies into the realm of GPCR-based, live-cell screening assays.

FINDSITE(X): a structure-based, small molecule virtual screening approach with application to all identified human GPCRs

We have developed FINDSITE(X), an extension of FINDSITE, a protein threading based algorithm for the inference of protein binding sites, biochemical function and virtual ligand screening, that removes the limitation that holo protein structures (those containing bound ligands) of a sufficiently large set of distant evolutionarily related proteins to the target be solved; rather, predicted protein structures and experimental ligand binding information are employed. To provide the predicted protein structures, a fast and accurate version of our recently developed TASSER(VMT), TASSER(VMT)-lite, for template-based protein structural modeling applicable up to 1000 residues is developed and tested, with comparable performance to the top CASP9 servers. Then, a hybrid approach that combines structure alignments with an evolutionary similarity score for identifying functional relationships between target and proteins with binding data has been developed. By way of illustration, FINDSITE(X) is applied to 998 identified human G-protein coupled receptors (GPCRs). First, TASSER(VMT)-lite provides updates of all human GPCR structures previously modeled in our lab. We then use these structures and the new function similarity detection algorithm to screen all human GPCRs against the ZINC8 nonredundant (TC < 0.7) ligand set combined with ligands from the GLIDA database (a total of 88,949 compounds). Testing (excluding GPCRs whose sequence identity > 30% to the target from the binding data library) on a 168 human GPCR set with known binding data, the average enrichment factor in the top 1% of the compound library (EF(0.01)) is 22.7, whereas EF(0.01) by FINDSITE is 7.1. For virtual screening when just the target and its native ligands are excluded, the average EF(0.01) reaches 41.4. We also analyze off-target interactions for the 168 protein test set. All predicted structures, virtual screening data and off-target interactions for the 998 human GPCRs are available at http://cssb.biology.gatech.edu/skolnick/webservice/gpcr/index.html .

Structural mechanisms of constitutive activation in the C5a receptors with mutations in the extracellular loops: molecular modeling study

Previously we demonstrated by random saturation mutagenesis a set of mutations in the extracellular (EC) loops that constitutively activate the C5a receptor (C5aR) (Klco et al., Nat Struct Mol Biol 2005;12:320-326; Klco et al., J Biol Chem 2006;281:12010-12019). In this study, molecular modeling revealed possible conformations for the extracellular loops of the C5a receptors with mutations in the EC2 loop or in the EC3 loop. Comparison of low-energy conformations of the EC loops defined two distinct clusters of conformations typical either for strongly constitutively active mutants of C5aR (the CAM cluster) or for nonconstitutively active mutants (the non-CAM cluster). In the CAM cluster, the EC3 loop was turned towards the transmembrane (TM) helical bundle and more closely interacted with EC2 than in the non-CAM cluster. This suggested a structural mechanism of constitutive activity where EC3 contacts EC2 leading to EC2 interactions with helix TM3, thus triggering movement of TM7 towards TM2 and TM3. The movement initiates rearrangement of the system of hydrogen bonds between TM2, TM3 and TM7 including formation of the hydrogen bond between the side chains of D82(2.50) in TM2 and N296(7.49) in TM7, which is crucial for formation of the activated states of the C5a receptors (Nikiforovich et al., Proteins: Struct Funct Gene 2011;79:787-802). Since the relative large length of EC3 in C5aR (13 residues) is comparable with those in many other members of rhodopsin family of GPCRs (13-19 residues), our findings might reflect general mechanisms of receptor constitutive activation. The very recent X-ray structure of the agonist-induced constitutively active mutant of rhodopsin (Standfuss et al., Nature 2011;471:656-660) is discussed in view of our modeling results.

In Silico Veritas: The Pitfalls and Challenges of Predicting GPCR-Ligand Interactions

Recently the first community-wide assessments of the prediction of the structures of complexes between proteins and small molecule ligands have been reported in the so called GPCR Dock 2008 and 2010 assessments. In the current review we discuss the different steps along the protein-ligand modeling workflow by critically analyzing the modeling strategies we used to predict the structures of protein-ligand complexes we submitted to the recent GPCR Dock 2010 challenge. These representative test cases, focusing on the pharmaceutically relevant G Protein-Coupled Receptors, are used to demonstrate the strengths and challenges of the different modeling methods. Our analysis indicates that the proper performance of the sequence alignment, introduction of structural adjustments guided by experimental data, and the usage of experimental data to identify protein-ligand interactions are critical steps in the protein-ligand modeling protocol.

Conserved residues in the extracellular loops of short-wavelength cone visual pigments

The role of the extracellular loop region of a short-wavelength sensitive pigment, Xenopus violet cone opsin, is investigated via computational modeling, mutagenesis, and spectroscopy. The computational models predict a complex H-bonding network that stabilizes and connects the EC2-EC3 loop and the N-terminus. Mutations that are predicted to disrupt the H-bonding network are shown to produce visual pigments that do not stably bind chromophore and exhibit properties of a misfolded protein. The potential role of a disulfide bond between two conserved Cys residues, Cys(105) in TM3 and Cys(182) in EC2, is necessary for proper folding and trafficking in VCOP. Lastly, certain residues in the EC2 loop are predicted to stabilize the formation of two antiparallel β-strands joined by a hairpin turn, which interact with the chromophore via H-bonding or van der Waals interactions. Mutations of conserved residues result in a decrease in the level of chromophore binding. These results demonstrate that the extracellular loops are crucial for the formation of this cone visual pigment. Moreover, there are significant differences in the structure and function of this region in VCOP compared to that in rhodopsin.

Theoretical study of 3-D molecular similarity and ligand binding modes of orthologous human and rat D2 dopamine receptors

The D(2) dopamine receptor (D(2)DR) is an important target for the treatment of some central nervous system disorders, such as Parkinson disease, schizophrenia and drug-dependence. In this work, we built 3-D models of the long form of human and rat D(2)DRs by considering data from the crystallized D3 dopamine receptor, β2 adrenoceptor and A2a adenosine receptor as templates. Then, docking was performed with ligand and protein residue flexibility. These results were used to analyze ligand recognition and estimate binding affinity. Our results show that the predicted ligand affinity correlates with experimental data, and binding modes are very similar between the D(2)DRs of these two species.

Successful prediction of the intra- and extracellular loops of four G-protein-coupled receptors

We present results of the restoration of all crystallographically available intra- and extracellular loops of four G-protein-coupled receptors (GPCRs): bovine rhodopsin (bRh), the turkey β-1 adrenergic receptor (β1Ar), and the human β-2 adrenergic (β2Ar) and A2A adenosine (A2Ar) receptors. We use our Protein Local Optimization Program (PLOP), which samples conformational space from first principles to build sets of loop candidates and then discriminates between them using our physics-based, all-atom energy function with implicit solvent. We also discuss a new kind of explicit membrane calculation developed for GPCR loops that interact, either in the native structure or in low-energy false-positive structures, with the membrane, and thus exist in a multiphase environment not previously incorporated in PLOP. Our results demonstrate a significant advance over previous work reported in the literature, and of particular note we are able to accurately restore the extremely long second extracellular loop (ECL2), which is also key for GPCR ligand binding. In the case of β2Ar, accurate ECL2 restoration required seeding a small helix into the loop in the appropriate region, based on alignment with the β1Ar ECL2 loop, and then running loop reconstruction simulations with and without the seeded helix present; simulations containing the helix attain significantly lower total energies than those without the helix, and have rmsds close to the native structure. For β1Ar, the same protocol was used, except the alignment was done to β2Ar. These results represent an encouraging start for the more difficult problem of accurate loop refinement for GPCR homology modeling.

Open conformation of adipokinetic hormone receptor from the malaria mosquito facilitates hormone binding

Insect flight requires rapid mobilization of energy reserves during flight, which is mediated and regulated by hormonal control via adipokinetic hormones. The structure of the G-protein receptors to which these hormones bind, are crucial in understanding many of the physiological processes in which they play a central role. To date no 3D structure of an insect G-protein coupled receptor (GPCR) is available. Here, the first models of the 3D structures of a GPCR from the malaria mosquito are presented. Homology modeling of the receptor identified from the genome of Anopheles gambiae was used to construct two models of the receptor. The 7 transmembrane helical bundles of these two models are based on the crystal structures of beta2-adrenergic receptor and rhodopsin. The flexible loop regions were modeled using high temperature simulated annealing and constrained molecular dynamic simulations. The two receptor models differ in a number of critical features, the most important of which is that the rhodopsin-based model has a 'closed' structure while the beta2-based structure is 'open'. The 'open' conformation provides easy access of the hormone to the binding pocket. Docking calculations with the insect adipokinetic hormones, AKH-1 (pGlu-Leu-Thr-Phe-Thr-Pro-Ala-Trp-NH(2)) from the malaria mosquito and Del-CC (pGlu-Lys-Asn-Phe-Ser-Pro-Asn-Trp-Gly-Asn-NH(2)) from the blister beetle showed that while the binding motif of the two is similar, AKH-1 has more than 30 times higher affinity than Del-CC, which strongly suggests that the binding is specific, and that the correct binding site was identified. Using these models it is possible to design antagonists, which block the binding site and are thus species-specific insecticides.

Loop simulations

Loop modeling is crucial for high-quality homology model construction outside conserved secondary structure elements. Dozens of loop modeling protocols involving a range of database and ab initio search algorithms and a variety of scoring functions have been proposed. Knowledge-based loop modeling methods are very fast and some can successfully and reliably predict loops up to about eight residues long. Several recent ab initio loop simulation methods can be used to construct accurate models of loops up to 12-13 residues long, albeit at a substantial computational cost. Major current challenges are the simulations of loops longer than 12-13 residues, the modeling of multiple interacting flexible loops, and the sensitivity of the loop predictions to the accuracy of the loop environment.

Simplified modeling approach suggests structural mechanisms for constitutive activation of the C5a receptor

Molecular modeling of conformational changes occurring in the transmembrane region of the complement factor 5a receptor (C5aR) during receptor activation was performed by comparing two constitutively active mutants (CAMs) of C5aR, NQ (I124N/L127Q), and F251A, to those of the wild-type C5aR and NQ-N296A (I124N/L127Q/N296A), which have the wild-type phenotype. Modeling involved comprehensive sampling of various rotations of TM helices aligned to the crystal template of the dark-adapted rhodopsin along their long axes. By assuming that the relative energies of the spontaneously activated states of CAMs should be lower or at least comparable to energies characteristic for the ground states, we selected the plausible models for the conformational states associated with constitutive activation in C5aR. The modeling revealed that the hydrogen bonds between the side chains of D82-N119, S85-N119, and S131-C221 characteristic for the ground state were replaced by the hydrogen bonds D82-N296, N296-Y300, and S131-R134, respectively, in the activated states. Also, conformational transitions that occurred upon activation were hindered by contacts between the side chains of L127 and F251. The results rationalize the available data of mutagenesis in C5aR and offer the first specific molecular mechanism for the loss of constitutive activity in NQ-N296A. Our results also contributed to understanding the general structural mechanisms of activation in G-protein-coupled receptors lacking the "ionic lock", R(3.50) and E/D(6.30). Importantly, these results were obtained by modeling approaches that deliberately simplify many elements in order to explore potential conformations of GPCRs involving large-scale molecular movements.

Modeling G Protein-Coupled Receptors: a Concrete Possibility

G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that are involved in the regulation of a wide range of physiological functions and constitute the most common target for therapeutic intervention. Due to the paucity of crystal structures, homology modeling has become a widespread technique for the construction of GPCR models, which have been applied to the study of their structure-function relationships and to the identification of lead ligands through virtual screening. Rhodopsin has been for years the only available template. However, recent breakthroughs in GPCR crystallography have led to the solution of the structures of a few additional receptors. In light of these newly elucidated crystal structures, we have been able to produce a substantial amount of data to demonstrate that accurate models of GPCRs in complex with their ligands can be constructed through homology modeling followed by fully flexible molecular docking. These results have been confirmed by our success in the first blind assessment of GPCR modeling and docking, organized in coordination with the solution of the X-ray structure of the adenosine A(2A) receptor. Taken together, these data indicate that: a) the transmembrane helical bundle can be modeled with considerable accuracy; b) predicting the binding mode of a ligand, although doable, is challenging; c) modeling of the extracellular and intracellular loops is still problematic.