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- G protein-coupled receptors: structure- and function-based drug discovery
- G protein-coupled receptor
- G protein-coupled receptor
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G protein-coupled receptors: structure- and function-based drug discovery
Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native.
These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately predicted models should have the correct folds.
The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors.
Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis.
G protein—coupled receptors GPCRs are a large superfamily of integral membrane proteins that transduce signals across the cell membrane. Because of the breadth and importance of the physiological roles undertaken by the GPCR family, many of its members are important pharmacological targets. Although the knowledge of a protein's native structure can provide important insight into understanding its function and for the design of new drugs, the experimental determination of the three-dimensional structure of GPCR membrane proteins has proved to be very difficult.
This is demonstrated by the fact that there is only one solved GPCR structure from bovine rhodopsin deposited in the Protein Data Bank library. To address the need for the tertiary structures of human GPCRs, using just sequence information, the authors use a newly developed threading-assembly-refinement method to generate models for all registered GPCRs in the human genome.
About GPCRs are anticipated to have correct topology and transmembrane helix arrangement. A subset of the resulting models is validated by comparison with mutagenesis experimental data, and consistent agreement is demonstrated.
PLoS Comput Biol 2 2 : e This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Competing interests: The authors have declared that no competing interests exist. Many diseases involve the malfunction of these receptors, making them important drug targets.
While knowledge of a protein's structure furnishes important information for understanding its function and for drug design [ 6 ], progress in solving GPCR structures has been slow [ 7 ].
Nuclear magnetic resonance NMR spectroscopy and X-ray crystallography are the two major techniques used to determine protein structures. NMR spectroscopy has the advantages that the protein does not need to be crystallized and dynamical information can be extracted. However, high concentrations of dissolved proteins are needed; and as yet no complete GPCR structure has been solved by the method.
X-ray crystallography can provide very precise atomic information for globular proteins, but GPCRs are extremely difficult to crystallize. It is unlikely that a significant number of high-resolution GPCR structures will be experimentally solved in the very near future. This situation limits the use of structure-based approaches for drug design and restricts research into the mechanisms that control ligand binding to GPCRs, activation and regulation of GPCRs, and signal transduction mediated by GPCRs [ 9 ].
Fortunately, as demonstrated by the recent CASP experiments [ 10 ], computer-based methods for deducing the three-dimensional structure of a protein from its amino acid sequence have been increasingly successful. Among the three types of structure prediction algorithms—homology modeling comparative modeling [CM] [ 11 , 12 ], threading [ 13 , 14 ], and ab initio folding [ 15 — 17 ]—CM, which builds models by aligning the target sequence to an evolutionarily related template structure, provides the most accurate models.
However, its success is largely dictated by the evolutionary relationship between target and template proteins. Here, the models provided by CM are often closer to the template on which the model is based rather than the native structure of the sequence of interest.
This has been a significant unsolved problem [ 19 ]. Recently [ 14 , 17 , 20 , 21 ], we developed the threading assembly refinement TASSER methodology, which combines threading and ab initio algorithms to span the homologous to nonhomologous regimens. As a significant advance over traditional homology modeling, many models including membrane proteins are improved with respect to their threading templates of 2, targets have an RMSD improvement of greater than 1.
In the absence of additional GPCR crystal structures, computer-based modeling may provide the best alternative to obtaining structural information [ 23 — 28 ]. This is especially important in GPCR modeling as the extracellular loops are often critical in determining ligand specificity [ 31 — 33 ].
Therefore, full-length TASSER models offer substantial advantages over traditional comparative modeling methods and are likely to be of greater aid in understanding the ligand and signaling interactions of GPCRs.
Two forms of TASSER were developed for this study that slightly differ from our previously published work [ 14 , 17 , 20 , 21 ]. The average RMSD of these structures to the cluster centroid is 4. In Figure 1 , we show the comparison of both threading templates and the model of highest structure density with respect to the crystal structure.
An RMSD of 4. The major modeling errors are in the N- and C-termini and the C3 loop. If we excise the tails and superimpose the model onto the core region residues 32 to of the native structure, the RMSD between the model and native structure is 3. Blue to red runs from N- to C-terminus. The numbers are the RMSD to native. A second integrated form of TASSER was constructed that incorporates a TM potential but selectively applies it without prior knowledge as to whether a target sequence is a membrane protein.
A detailed list of the threading templates and final model information for the 38 membrane proteins is presented at Table 1. Applying this to the four other known seven-TM proteins in the PDB database, archeorhodopsin 1uaz , sensory rhodopsin 1jgj , halorhodopsin 1e12 , and bacteriorhodopsin 1ap9 , yields final models with RMSDs to native of 2.
First, the dominant factor is the correct identification of analog templates from the threading algorithm [ 14 ]. The result of the final predictions is a combination of complex threading and simulation procedures, which prohibits the induction of a simple and explicit rule for when TASSER will succeed.
One of the difficulties in validating GPCR models is the paucity of experimental evidence that would provide a strong validation or invalidation of a given model. However, by providing a detailed benchmark of membrane proteins including seven-TM proteins and bovine RH itself, we have clearly demonstrated the ability of TASSER to refine membrane structures from low sequence—identity templates to structures that are closer to the native structure in an automated fashion.
The automated nature of this approach offers a potential advantage over many other human expert—based methods that may introduce biases by a priori assuming specific structural characteristics or restraints.
Sequence analysis estimates that there are about GPCRs in the human genome [ 3 ]. To establish their evolutionary distance, we made an all-against-all sequence comparison and grouped them into clusters based on their sequence identities. The second largest cluster has 38 GPCR sequences, of which half are chemokine receptors. Three hundred sixty-five GPCRs belong to 68 smaller clusters with two to 30 members, including the four-member cluster homologous to bovine RH.
These data demonstrate the high sequence and therefore structure diversity among the GPCRs. If the assumption is made that GPCRs should all contain seven-TM regions—which may be incorrect—better alignments should be constructed by identifying helical regions explicitly.
However, these sequence diversity data strongly suggest that direct comparative modeling with the bovine RH structure alone is highly unlikely to capture the nature of the structural differences among GPCRs not only in the highly diverse loop regions but within the core TM regions, too.
The average sequence identities between the target and template are Among the 48 sequence clusters with three or more members, all members in 40 of the clusters are easy targets. Although further refinement of the core region and the ab initio prediction of the loop conformations are needed, these alignments provide a reasonable initial conformation for TASSER. In fact, even for proteins that do not hit these four templates, due to TASSER refinement, many are predicted to have the TM helix topology through a fully automated procedure.
As shown below, there are cases where the GPCR model has a typical TM helix topology but only targets have these four TM helical proteins as starting templates. Since the quality of threading templates is better for the GPCR proteins reflected by the larger fraction of Easy targets and higher alignment coverage , many more GPCR models are populated at high C-scores.
The C-score is defined as in Equation 1. Inset: The cumulative foldable fraction calculated under the assumption that the GPCR proteins have the same correlation between success and C-score as that of the PDB benchmark proteins.
For the 2, benchmark proteins ranging in size from 41 to residues, the correlation coefficient between C-score and RMSD of the first model corresponding to the most populated cluster to native is 0. Of 38 membrane proteins in the benchmark, the correlation coefficient is 0. There are , , and cases with C-scores above 0. Here, we note that a low RMSD just indicates the correctness of the overall topology of the helical arrangements. But the details of the loop regions and especially the ligand-binding sites may still be inaccurate.
Further refinement at an atomic level as well as including the binding ligands in the modeling may be helpful. For example, among targets with C-score greater than 1. This correlation indicates that although TASSER has the ability of structural refinement, the overall success still strongly relies on the quality of threading templates [ 34 ].
Furthermore, models generated with the explicit membrane potential showed little difference from those generated with the integrated form of TASSER average TM score, 0. One of the major differences of the current approach from traditional CM methods is that TASSER refines the topology of threading alignments by rearranging the continuous fragments, while CM builds the model through optimally satisfying the restraints of the template structures. This results in the best CM models having the smallest variations from their initial template.
Given the low sequence identity among GPCRs as a big family, one might expect significant differences from bovine RH, the only template available for CM methods.
Thus, an interesting question is the extent to which TASSER has changed the conformation with respect to the initial template. In Figure 4 B, we also show the helix angle changes of the predicted models with respect to bovine RH after superposition with TM-align [ 35 ].
Obviously, these conformational changes are significantly larger than the inherent resolution of TASSER modeling—as shown in the green triangles in Figure 4 A and 4 B; if we model bovine RH using its own crystal structure as the template, the overall RMSD of the model is 0. This degree of conformational change from the template is higher than could be expected by using a comparative modeling approach.
Based on our previous benchmark and blind test results [ 20 , 21 , 36 , 37 ], most of the conformational deviations from the templates are in the correct direction toward native structures. Even starting from the best structure alignments, similar improvements of final models relative to templates have been demonstrated e. These data give us confidence that the observed deviations from the bovine RH template are most likely in the direction toward their native state.
Data are the average from those targets where bovine RH is a template with C-score greater than 1. TM helices are marked in gray.
Using an automatic procedure to identify TM helices by structurally aligning the models to a long helix, we can count the number of TM helices in the predicted models. Consistent with the cell membrane thickness, these are typically 17 to 25 residues long [ 38 ]. Ten GPCRs have eight long helices, where, as visually confirmed, the eighth helix is located in a tail outside the seven-TM helix bundle. We also checked by visual inspection all other targets that have fewer than seven helices.
Most have shorter sequence lengths and a regular TM-like topology. In general, these are truncated fragments of complete GPCR sequences [ 39 , 40 ]. There are 45 sequences whose global topology is not TM helix—like. Most have zero- to three-long, non-TM helices. Although there is little experimental evidence with which to directly test the validity of TASSER GPCR models, there exist indirect means of increasing the confidence in our predictions.
Second, we can check the self-consistency of the models under the assumption that closely related GPCRs or those with similar ligand specificities should in general adopt structures that are most similar to one another.
G protein-coupled receptor
G protein-coupled receptors GPCRs , also known as seven- pass -transmembrane domain receptors , 7TM receptors , heptahelical receptors , serpentine receptors , and G protein-linked receptors GPLR , form a large group of evolutionarily-related proteins that are cell surface receptors that detect molecules outside the cell and activate cellular responses. Coupling with G proteins , they are called seven-transmembrane receptors because they pass through the cell membrane seven times. They are all activated by agonists although a spontaneous auto-activation of an empty receptor can also be observed. G protein-coupled receptors are found only in eukaryotes , including yeast , choanoflagellates ,  and animals. The ligands that bind and activate these receptors include light-sensitive compounds, odors , pheromones , hormones , and neurotransmitters , and vary in size from small molecules to peptides to large proteins.
Structure of G Protein G proteins, also known as guanine nucleotide-binding proteins, involved in transmitting signals and function as molecular.
G protein-coupled receptor
Membrane receptors coupling to intracellular G proteins G protein-coupled receptors form one of the major classes of membrane signaling proteins. They are of great importance to the practice of anesthesiology because they are involved in many systems of relevance to the specialty cardiovascular and respiratory control, pain transmission, and others and many drugs target these systems. In recent years, understanding of these signaling systems has grown. The structure of receptors and G proteins has been elucidated in more detail, their regulation is better understood, and the complexity of interactions between the various parts of the system receptors, G proteins, effectors, and regulatory molecules has become clear.
Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures.
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Мидж, послушай. - Он засмеялся.
G Protein–coupled Receptors
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Это должно было гарантировать, что АНБ не сможет перехватывать частную переписку законопослушных граждан во всем мире. Однако когда настало время загрузки программного обеспечения, персоналу, работавшему с ТРАНСТЕКСТОМ, объявили, что планы изменились. В связи с чрезвычайной обстановкой, в которой обычно осуществляется антитеррористическая деятельность АНБ, ТРАНСТЕКСТ станет независимым инструментом дешифровки, использование которого будет регулироваться исключительно самим АНБ. Энсей Танкадо был возмущен. Получалось, что АНБ фактически получило возможность вскрывать всю почту и затем пересылать ее без какого-либо уведомления. Это было все равно что установить жучки во все телефонные аппараты на земле. Стратмор попытался убедить Танкадо, что ТРАНСТЕКСТ - это орудие охраны правопорядка, но безуспешно: Танкадо продолжал настаивать на том, что это грубейшее нарушение гражданских прав.
Господи Иисусе. - Морант закашлялся. - Давайте попробуем кандзи. И словно по волшебству все встало на свое место. Это произвело на дешифровщиков впечатление, но тем не менее Беккер продолжал переводить знаки вразнобой, а не в той последовательности, в какой они были расположены в тексте. - Это для вашей же безопасности, - объяснил Морант. - Вам незачем знать, что вы переводите.