Evolutionary trace of G protein-coupled receptors reveals clusters of residues that determine global and class-specific functions

Glu1022.53-Mediated Early Conformational Changes in the Process of Light-Induced Green Cone Pigment Activation

Ligand-triggered activation of G protein-coupled receptors (GPCRs) relies on the phenomenon of loose allosteric coupling, which involves conformational alterations spanning from the extracellular ligand-binding domain to the cytoplasmic region, where interactions with G proteins occur. During the GPCR activation process, several intermediate and equilibrium states orchestrate the movement of the flexible and rigid transmembrane (TM) segments of the GPCR. Monitoring early conformational changes is important in unraveling the structural intricacies of the loose allosteric coupling. Here, we focus on the lumi intermediate formed by thermal relaxation from the initial photointermediate, batho in primate green cone pigment (MG), a light-sensitive GPCR responsible for color vision. Our findings from light-induced Fourier transform infrared difference spectroscopy reveal its similarity with rhodopsin, which mediates twilight vision, specifically involving the flip motion of the β-ionone ring, the relaxation of the torsional structure of the retinal, and local perturbations in the α-helix upon lumi intermediate formation. Conversely, we observe a hydrogen bond modification specific to MG's protonated carboxylic acid, identifying its origin as Glu1022.53 situated in TM2. The weakening of the hydrogen bond strength at Glu1022.53 during the transition from the batho to the lumi intermediates corresponds to a slight outward movement of TM2. Additionally, within the X-ray crystal structure of the rhodopsin lumi intermediate, we note the relocation of the Met862.53 side chain in TM2, expanding the volume of the retinal binding pocket. Consequently, the position of 2.53 emerges as the early step in the conformational shift toward light-induced activation. Moreover, given the prevalence of IR-insensitive hydrophobic amino acids at position 2.53 in many rhodopsin-like GPCRs, including rhodopsin, the hydrogen bond alteration in the C═O stretching band at Glu1022.53 of MG can be used as a probe for tracing conformational changes during the GPCR activation process.

Molecular determinants of ligand efficacy and potency in GPCR signaling

Heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) bind to extracellular ligands and drugs and modulate intracellular responses through conformational changes. Despite their importance as drug targets, the molecular origins of pharmacological properties such as efficacy (maximum signaling response) and potency (the ligand concentration at half-maximal response) remain poorly understood for any ligand-receptor-signaling system. We used the prototypical adrenaline-β2 adrenergic receptor-G protein system to reveal how specific receptor residues decode and translate the information encoded in a ligand to mediate a signaling response. We present a data science framework to integrate pharmacological and structural data to uncover structural changes and allosteric networks relevant for ligand pharmacology. These methods can be tailored to study any ligand-receptor-signaling system, and the principles open possibilities for designing orthosteric and allosteric compounds with defined signaling properties.

Molecular Evolution of Malacostracan Short Wavelength Sensitive Opsins

Investigations of the molecular mechanisms behind detection of short, and particularly ultraviolet, wavelengths in arthropods have relied heavily on studies from insects due to the relative ease of heterologous expression of modified opsin proteins in model organisms like Drosophila. However, species outside of the Insecta can provide information on mechanisms for spectral tuning as well as the evolutionary history of pancrustacean visual pigments. Here we investigate the basis of spectral tuning in malacostracan short wavelength sensitive (SWS) opsins using phylogenetic comparative methods. Tuning sites that may be responsible for the difference between ultraviolet (UV) and violet visual pigment absorbance in the Malacostraca are identified, and the idea that an amino acid polymorphism at a single site is responsible for this shift is shown to be unlikely. Instead, we suggest that this change in absorbance is accomplished through multiple amino acid substitutions. On the basis of our findings, we conducted further surveys to identify spectral tuning mechanisms in the order Stomatopoda where duplication of UV opsins has occurred. Ancestral state reconstructions of stomatopod opsins from two main clades provide insight into the amino acid changes that lead to differing absorption by the visual pigments they form, and likely contribute the basis for the wide array of UV spectral sensitivities found in this order.

CovET: A covariation-evolutionary trace method that identifies protein structure-function modules

Measuring the relative effect that any two sequence positions have on each other may improve protein design or help better interpret coding variants. Current approaches use statistics and machine learning but rarely consider phylogenetic divergences which, as shown by Evolutionary Trace studies, provide insight into the functional impact of sequence perturbations. Here, we reframe covariation analyses in the Evolutionary Trace framework to measure the relative tolerance to perturbation of each residue pair during evolution. This approach (CovET) systematically accounts for phylogenetic divergences: at each divergence event, we penalize covariation patterns that belie evolutionary coupling. We find that while CovET approximates the performance of existing methods to predict individual structural contacts, it performs significantly better at finding structural clusters of coupled residues and ligand binding sites. For example, CovET found more functionally critical residues when we examined the RNA recognition motif and WW domains. It correlates better with large-scale epistasis screen data. In the dopamine D2 receptor, top CovET residue pairs recovered accurately the allosteric activation pathway characterized for Class A G protein-coupled receptors. These data suggest that CovET ranks highest the sequence position pairs that play critical functional roles through epistatic and allosteric interactions in evolutionarily relevant structure-function motifs. CovET complements current methods and may shed light on fundamental molecular mechanisms of protein structure and function.

Mechanism of Activation of the Visual Receptor Rhodopsin

Rhodopsin is the photoreceptor in human rod cells responsible for dim-light vision. The visual receptors are part of the large superfamily of G protein-coupled receptors (GPCRs) that mediate signal transduction in response to diverse diffusible ligands. The high level of sequence conservation within the transmembrane helices of the visual receptors and the family A GPCRs has long been considered evidence for a common pathway for signal transduction. I review recent studies that reveal a comprehensive mechanism for how light absorption by the retinylidene chromophore drives rhodopsin activation and highlight those features of the mechanism that are conserved across the ligand-activated GPCRs.

Coevolutionary signals in metabotropic glutamate receptors capture residue contacts and long-range functional interactions

Upon ligand binding to a G protein-coupled receptor, extracellular signals are transmitted into a cell through sets of residue interactions that translate ligand binding into structural rearrangements. These interactions needed for functions impose evolutionary constraints so that, on occasion, mutations in one position may be compensated by other mutations at functionally coupled positions. To quantify the impact of amino acid substitutions in the context of major evolutionary divergence in the G protein-coupled receptor subfamily of metabotropic glutamate receptors (mGluRs), we combined two phylogenetic-based algorithms, Evolutionary Trace and covariation Evolutionary Trace, to infer potential structure-function couplings and roles in mGluRs. We found a subset of evolutionarily important residues at known functional sites and evidence of coupling among distinct structural clusters in mGluR. In addition, experimental mutagenesis and functional assays confirmed that some highly covariant residues are coupled, revealing their synergy. Collectively, these findings inform a critical step toward understanding the molecular and structural basis of amino acid variation patterns within mGluRs and provide insight for drug development, protein engineering, and analysis of naturally occurring variants.

Breaking barriers in antibody discovery: harnessing divergent species for accessing difficult and conserved drug targets

To exploit highly conserved and difficult drug targets, including multipass membrane proteins, monoclonal antibody discovery efforts increasingly rely on the advantages offered by divergent species such as rabbits, camelids, and chickens. Here, we provide an overview of antibody discovery technologies, analyze gaps in therapeutic antibodies that stem from the historic use of mice, and examine opportunities to exploit previously inaccessible targets through discovery now possible in alternate species. We summarize the clinical development of antibodies raised from divergent species, discussing how these animals enable robust immune responses against highly conserved binding sites and yield antibodies capable of penetrating functional pockets via long HCDR3 regions. We also discuss the value of pan-reactive molecules often produced by these hosts, and how these antibodies can be tested in accessible animal models, offering a faster path to clinical development.

Mechanistic Studies on the Stereoselectivity of FFAR1 Modulators

Free fatty acid receptor 1 (FFAR1) is a potential therapeutic target for the treatment of type 2 diabetes (T2D). It has been validated that agonists targeting FFAR1 can achieve the initial therapeutic endpoints of T2D, and the epimer agonists (R,S) AM-8596 can activate FFAR1 differently, with one acting as a partial agonist and the other as a full agonist. Up to now, the origin of the stereoselectivity of FFAR1 agonists remains elusive. In this work, we used molecular simulation methods to elucidate the mechanism of the stereoselectivity of the FFAR1 agonists (R)-AM-8596 and (S)-AM-8596. We found that the full agonist (R)-AM-8596 disrupts the residue interaction network around the receptor binding pocket and promotes the opening of the binding site for the G-protein, thereby resulting in the full activation of FFAR1. In contrast, the partial agonist (S)-AM-8596 forms stable electrostatic interactions with FFAR1, which stabilizes the residue network and hinders the conformational transition of the receptor. Our work thus clarifies the selectivity and underlying molecular activation mechanism of FFAR1 agonists.

Open Search-Based Proteomics Reveals Widespread Tryptophan Modifications Associated with Hypoxia in Lung Cancer

The tryptophan residue has a large hydrophobic surface that plays a unique role in the folded protein conformation and functions. Tryptophan modifications are presumably to be readily detected in proteins due to the vulnerability of the indole structure to electrophilic attacks. In this study, we report a systematic identification of sequence variations at tryptophan, termed tryptophan variants, from the proteome of patients with nonsmall cell lung cancer (NSCLC). Using shotgun proteomics and a modified open search algorithm, 25 tryptophan variants on 2481 sites in over 858 proteins were identified. Among these, 6 tryptophan variants are previously identified, 15 are newly annotated, and 4 are still unknown, most of which are involved in the cascade of oxidation in the blood microparticle. Remarkably, Trp313 of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was up-oxidized whereas Trp16 and Trp38 of hemoglobin (HBB) were down-oxidized in NCSLC tissues. The results were further supported by an independent cohort of 103 lung adenocarcinoma samples, reflecting a negative feedback and potential detoxification mechanism against tumor glycolysis and hypoxia. Overall, the study reports a quick approach to explore tryptophan variants at the proteomic scale. Our findings highlight the predominant role of tryptophan oxidation in regulating the redox balance of cancer cells and its potential role as prognostic biomarker for patients with NSCLC.

Magic angle spinning NMR of G protein-coupled receptors

G protein-coupled receptors (GPCRs) have a simple seven transmembrane helix architecture which has evolved to recognize a diverse number of chemical signals. The more than 800 GPCRs encoded in the human genome function as receptors for vision, smell and taste, and mediate key physiological processes. Consequently, these receptors are a major target for pharmaceuticals. Protein crystallography and electron cryo-microscopy have provided high resolution structures of many GPCRs in both active and inactive conformations. However, these structures have not sparked a surge in rational drug design, in part because GPCRs are inherently dynamic and the structural changes induced by ligand or drug binding to stabilize inactive or active conformations are often subtle rearrangements in packing or hydrogen-bonding interactions. NMR spectroscopy provides a sensitive probe of local structure and dynamics at specific sites within these receptors as well as global changes in receptor structure and dynamics. These methods can also capture intermediate states and conformations with low populations that provide insights into the activation pathways. We review the use of solid-state magic angle spinning NMR to address the structure and activation mechanisms of GPCRs. The focus is on the large and diverse class A family of receptors. We highlight three specific class A GPCRs in order to illustrate how solid-state, as well as solution-state, NMR spectroscopy can answer questions in the field involving how different GPCR classes and subfamilies are activated by their associated ligands, and how small molecule drugs can modulate GPCR activation.

The Functional Differences between the GroEL Chaperonin of Escherichia coli and the HtpB Chaperonin of Legionella pneumophila Can Be Mapped to Specific Amino Acid Residues

Group I chaperonins are a highly conserved family of essential proteins that self-assemble into molecular nanoboxes that mediate the folding of cytoplasmic proteins in bacteria and organelles. GroEL, the chaperonin of Escherichia coli, is the archetype of the family. Protein folding-independent functions have been described for numerous chaperonins, including HtpB, the chaperonin of the bacterial pathogen Legionella pneumophila. Several protein folding-independent functions attributed to HtpB are not shared by GroEL, suggesting that differences in the amino acid (aa) sequence between these two proteins could correlate with functional differences. GroEL and HtpB differ in 137 scattered aa positions. Using the Evolutionary Trace (ET) bioinformatics method, site-directed mutagenesis, and a functional reporter test based upon a yeast-two-hybrid interaction with the eukaryotic protein ECM29, it was determined that out of those 137 aa, ten (M68, M212, S236, K298, N507 and the cluster AEHKD in positions 471-475) were involved in the interaction of HtpB with ECM29. GroEL was completely unable to interact with ECM29, but when GroEL was modified at those 10 aa positions, to display the HtpB aa, it acquired a weak ability to interact with ECM29. This constitutes proof of concept that the unique functional abilities of HtpB can be mapped to specific aa positions.

Recurrent high-impact mutations at cognate structural positions in class A G protein-coupled receptors expressed in tumors

GPCRs and GPCR pathways are increasingly being implicated in human malignancies, placing them among the most promising cancer drug candidates. Our results reveal enrichment of highly impactful, recurrent GPCR mutations within cancers. We found that cognate mutations in selected class A GPCRs have deleterious effects on signaling function. The results also suggest that olfactory receptors, often considered inconsequential, display a nonrandom mutation pattern in tumors in which they are expressed. These findings support the idea that protein paralogs can act in parallel as members of an onco-group.

G protein-coupled receptors (GPCRs) are the largest family of human proteins. They have a common structure and, signaling through a much smaller set of G proteins, arrestins, and effectors, activate downstream pathways that often modulate hallmark mechanisms of cancer. Because there are many more GPCRs than effectors, mutations in different receptors could perturb signaling similarly so as to favor a tumor. We hypothesized that somatic mutations in tumor samples may not be enriched within a single gene but rather that cognate mutations with similar effects on GPCR function are distributed across many receptors. To test this possibility, we systematically aggregated somatic cancer mutations across class A GPCRs and found a nonrandom distribution of positions with variant amino acid residues. Individual cancer types were enriched for highly impactful, recurrent mutations at selected cognate positions of known functional motifs. We also discovered that no single receptor drives this pattern, but rather multiple receptors contain amino acid substitutions at a few cognate positions. Phenotypic characterization suggests these mutations induce perturbation of G protein activation and/or β-arrestin recruitment. These data suggest that recurrent impactful oncogenic mutations perturb different GPCRs to subvert signaling and promote tumor growth or survival. The possibility that multiple different GPCRs could moonlight as drivers or enablers of a given cancer through mutations located at cognate positions across GPCR paralogs opens a window into cancer mechanisms and potential approaches to therapeutics.

Deconstructing the transmembrane core of class A G protein-coupled receptors

Class A G protein-coupled receptors have evolved to recognize ligands ranging from small-molecule odorants to proteins. Although they are among the most diverse membrane receptors in eukaryotic organisms, they possess a highly conserved core within their seven-transmembrane helix framework. The conservation of the transmembrane core has led to the idea of a common mechanism by which ligand binding is coupled to the outward rotation of helix H6, the hallmark of an active receptor. Nevertheless, there is still no consensus on the mechanism of coupling or on the roles of specific residues within the core. Recent insights from crystallography and NMR spectroscopy provide a way to decompose the core into its essential structural and functional elements that shed new light on this important region.

Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.

Conserved C-terminal motifs in odorant receptors instruct their cell surface expression and cAMP signaling

The highly individual plasma membrane expression and cAMP signaling of odorant receptors have hampered their ligand assignment and functional characterization in test cell systems. Chaperones have been identified to support the cell surface expression of only a portion of odorant receptors, with mechanisms remaining unclear. The presence of amino acid motifs that might be responsible for odorant receptors' individual intracellular retention or cell surface expression, and thus, for cAMP signaling, is under debate: so far, no such protein motifs have been suggested. Here, we demonstrate the existence of highly conserved C-terminal amino acid motifs, which discriminate at least between class-I and class-II odorant receptors, with their numbers of motifs increasing during evolution, by comparing C-terminal protein sequences from 4808 receptors across eight species. Truncation experiments and mutation analysis of C-terminal motifs, largely overlapping with helix 8, revealed single amino acids and their combinations to have differential impact on the cell surface expression and on stimulus-dependent cAMP signaling of odorant receptors in NxG 108CC15 cells. Our results demonstrate class-specific and individual C-terminal motif equipment of odorant receptors, which instruct their functional expression in a test cell system, and in situ may regulate their individual cell surface expression and intracellular cAMP signaling.

Allosteric communication regulates ligand-specific GPCR activity

G protein-coupled receptors (GPCRs) are membrane-bound proteins that are ubiquitously expressed in many cell types and take part in mediating multiple signaling pathways. GPCRs are dynamic proteins and exist in an equilibrium between an ensemble of conformational states such as inactive and fully active states. This dynamic nature of GPCRs is one of the factors that confers their basal activity even in the absence of any ligand-mediated activation. Ligands selectively bind and stabilize a subset of the conformations from the ensemble leading to a shift in the equilibrium toward the inactive or the active state depending on the nature of the ligand. This ligand-selective effect is achieved through allosteric communication between the ligand binding site and G protein or β-arrestin coupling site. Similarly, the G protein coupling to the receptor exerts the allosteric effect on the ligand binding region leading to increased binding affinity for agonists and decreased affinity for antagonists or inverse agonists. In this review, we enumerate the current state of our understanding of the mechanism of allosteric communication in GPCRs with a specific focus on the critical role of computational methods in delineating the residues involved in allosteric communication. Analyzing allosteric communication mechanism using molecular dynamics simulations has revealed (a) a structurally conserved mechanism of allosteric communication that regulates the G protein coupling, (b) a rational structure-based approach to designing selective ligands, and (c) an approach to designing allosteric GPCR mutants that are either ligand and G protein or β-arrestin selective.

Genome-wide identification and characterization of olfactory receptor genes in common carp (Cyprinus carpio)

The environment contains a large extent of chemical information, which could be detected as olfactory sense. Olfactory in vertebrates plays important roles on many aspects during life time, including localizing prey or food, avoiding predators, mating behavior and social communication. Considering the essential role of olfactory receptors in the specific recognition of diverse stimuli, understanding the evolutionary dynamics of olfactory receptors in teleost means a lot, especially in the allotetraploid common carp, who has undergone the fourth whole-genome duplication event. Here, we identified the whole set of olfactory receptor genes in representative teleosts and found a significant contraction in common carp when compared with other teleosts. Odorant receptor genes (OR) occupy the most among four groups of olfactory receptors, including 33 functional genes and 16 pseudogenes. Furthermore, 6 trace amine-associated receptor (TAAR) genes (including 1 pseudogene), 7 odorant-related-A receptor genes, and 10 olfactory C family receptor genes (including 3 pseudogenes) were identified in common carp. Phylogenetic and motif analysis were performed to illustrate the phylogenetic relationship and structural conservation of teleost olfactory receptors. Selection pressure analysis suggested that olfactory receptor groups in common carp were all under relaxed purifying-selection. Additionally, gene expression divergences for olfactory receptor genes were investigated during embryonic development stages of common carp. We aim to determine the abundance of common carp olfactory receptor genes, explore the evolutionary fate and expression dynamics, and provide some genomic clues for the evolution of polyploid olfactory after whole-genome duplication and for future studies of teleost olfactory.

Synchronous and Asynchronous Response in Dynamically Perturbed Proteins

We present a dynamic perturbation-response model of proteins based on the Gaussian Network Model, where a residue is perturbed periodically, and the dynamic response of other residues is determined. The model shows that periodic perturbation causes a synchronous response in phase with the perturbation and an asynchronous response that is out of phase. The asynchronous component results from the viscous effects of the solvent and other dispersive factors in the system. The model is based on the solution of the Langevin equation in the presence of solvent, noise, and perturbation. We introduce several novel ideas: The concept of storage and loss compliance of the protein and their dependence on structure and frequency; the amount of work lost and the residues that contribute significantly to the lost work; new dynamic correlations that result from perturbation; causality, that is, the response of j when i is perturbed is not equal to the response of i when j is perturbed. As examples, we study two systems, namely, bovine rhodopsin and the class of nanobodies. The general results obtained are (i) synchronous and asynchronous correlations depend strongly on the frequency of perturbation, their magnitude decreases with increasing frequency, (ii) time-delayed mean-squared fluctuations of residues have only synchronous components. Asynchronicity is present only in cross correlations, that is, correlations between different residues, (iii) perturbation of loop residues leads to a large dissipation of work, (iv) correlations satisfy the hypothesis of pre-existing pathways according to which information transfer by perturbation rides on already existing equilibrium correlations in the system, (v) dynamic perturbation can introduce a selective response in the system, where the perturbation of each residue excites different sets of responding residues, and (vi) it is possible to identify nondissipative residues whose perturbation does not lead to dissipation in the protein. Despite its simplicity, the model explains several features of allosteric manipulation.

Transcriptome analysis of phototransduction-related genes in tentacles of the sea cucumber Apostichopus japonicus

The sea cucumber Apostichopus japonicus (Selenka)is a typical nocturnal echinoderm, which is believed to be almost completely dependent on light intensity for the regulation of endogenous rhythms. Under conditions of high light intensity, this species shows clear evidence of light avoidance behavior, seeking out shaded areas of reef in which to reside. In this study, we performed RNA-Seq analysis to examine the tentacle transcriptome of A. japonicus specimens that had been subjected to dark and light (5 min and 1 h) conditions. We specifically focused on detecting genes involved in opsin-based light perception, including opsins and members of phototransduction-related pathways. On the basis of comparisons with both vertebrate and invertebrate phototransduction pathways, we determined that components of two of the main metazoan phototransduction pathways were altered in response to illumination. Among the key phototransduction-related genes in tentacles, we identified retinol dehydrogenase, members of the dehydrogenase/reductase family, and myosin III, and also detected a pair of visual pigment-like receptors, peropsin and peropsin-like, the homologous genes of which are believed to have the same function but show opposite expression patterns in response to different light environments. In general, the up-regulation of key genes in sea cucumber exposed to illumination indicated that the tentacles can respond to differences in the light environment at the molecular level.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.

Common activation mechanism of class A GPCRs

Class A G-protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology. Understanding receptor activation mechanism is critical for discovering novel therapeutics since about one-third of all marketed drugs target members of this family. GPCR activation is an allosteric process that couples agonist binding to G-protein recruitment, with the hallmark outward movement of transmembrane helix 6 (TM6). However, what leads to TM6 movement and the key residue level changes of this movement remain less well understood. Here, we report a framework to quantify conformational changes. By analyzing the conformational changes in 234 structures from 45 class A GPCRs, we discovered a common GPCR activation pathway comprising of 34 residue pairs and 35 residues. The pathway unifies previous findings into a common activation mechanism and strings together the scattered key motifs such as CWxP, DRY, Na+ pocket, NPxxY and PIF, thereby directly linking the bottom of ligand-binding pocket with G-protein coupling region. Site-directed mutagenesis experiments support this proposition and reveal that rational mutations of residues in this pathway can be used to obtain receptors that are constitutively active or inactive. The common activation pathway provides the mechanistic interpretation of constitutively activating, inactivating and disease mutations. As a module responsible for activation, the common pathway allows for decoupling of the evolution of the ligand binding site and G-protein-binding region. Such an architecture might have facilitated GPCRs to emerge as a highly successful family of proteins for signal transduction in nature.

Residues and residue pairs of evolutionary importance differentially direct signaling bias of D2 dopamine receptors

The D2 dopamine receptor and the serotonin 5-hydroxytryptamine 2A receptor (5-HT2A) are closely-related G-protein-coupled receptors (GPCRs) from the class A bioamine subfamily. Despite structural similarity, they respond to distinct ligands through distinct downstream pathways, whose dysregulation is linked to depression, bipolar disorder, addiction, and psychosis. They are important drug targets, and it is important to understand how their bias toward G-protein versus β-arrestin signaling pathways is regulated. Previously, evolution-based computational approaches, difference Evolutionary Trace and Evolutionary Trace-Mutual information (ET-Mip), revealed residues and residue pairs that, when switched in the D2 receptor to the corresponding residues from 5-HT2A, altered ligand potency and G-protein activation efficiency. We have tested these residue swaps for their ability to trigger recruitment of β-arrestin2 in response to dopamine or serotonin. The results reveal that the selected residues modulate agonist potency, maximal efficacy, and constitutive activity of β-arrestin2 recruitment. Whereas dopamine potency for most variants was similar to that for WT and lower than for G-protein activation, potency in β-arrestin2 recruitment for N124H^3.42 was more than 5-fold higher. T205M^5.54 displayed high constitutive activity, enhanced dopamine potency, and enhanced efficacy in β-arrestin2 recruitment relative to WT, and L379F^6.41 was virtually inactive. These striking differences from WT activity were largely reversed by a compensating mutation (T205M^5.54/L379F^6.41) at residues previously identified by ET-Mip as functionally coupled. The observation that the signs and relative magnitudes of the effects of mutations in several cases are at odds with their effects on G-protein activation suggests that they also modulate signaling bias.

Evolutionary Stability of Salt Bridges Hints Its Contribution to Stability of Proteins

The contribution of newly designed salt bridges to protein stabilization remains controversial even today. In order to solve this problem, we investigated salt bridges from two aspects: spatial distribution and evolutionary characteristics of salt bridges. Firstly, we analyzed spatial distribution of salt bridges in proteins, elucidating the basic requirements of forming salt bridges. Then, from an evolutionary point of view, the evolutionary characteristics of salt bridges as well as their neighboring residues were investigated in our study. The results demonstrate that charged residues appear more frequently than other neutral residues at certain positions of sequence even under evolutionary pressure, which are able to form electrostatic interactions that could increase the evolutionary stability of corresponding amino acid regions, enhancing their importance to stability of proteins. As a corollary, we conjectured that the newly designed salt bridges with more contribution to proteins, not only, are qualified spatial distribution of salt bridges, but also, are needed to further increase the evolutionary stability of corresponding amino acid regions. Based on analysis, the 8 mutations were accordingly constructed in the 1,4-α-glucan branching enzyme (EC 2.4.1.18, GBE) from Geobacillus thermoglucosidans STB02, of which 7 mutations improved thermostability of GBE. The enhanced thermostability of 7 mutations might be a result of additional salt bridges on residue positions that at least one of amino acids positions is conservative, improving their contribution of stabilization to proteins.

Applications of sequence coevolution in membrane protein biochemistry

Recently, protein sequence coevolution analysis has matured into a predictive powerhouse for protein structure and function. Direct methods, which use global statistical models of sequence coevolution, have enabled the prediction of membrane and disordered protein structures, protein complex architectures, and the functional effects of mutations in proteins. The field of membrane protein biochemistry and structural biology has embraced these computational techniques, which provide functional and structural information in an otherwise experimentally-challenging field. Here we review recent applications of protein sequence coevolution analysis to membrane protein structure and function and highlight the promising directions and future obstacles in these fields. We provide insights and guidelines for membrane protein biochemists who wish to apply sequence coevolution analysis to a given experimental system.

Most yeast SH3 domains bind peptide targets with high intrinsic specificity

A need exists to develop bioinformatics for predicting differences in protein function, especially for members of a domain family who share a common fold, yet are found in a diverse array of proteins. Many domain families have been conserved over large evolutionary spans and representative genomic data during these periods are now available. This allows a simple method for grouping domain sequences to reveal common and unique/specific binding residues. As such, we hypothesize that sequence alignment analysis of the yeast SH3 domain family across ancestral species in the fungal kingdom can determine whether each member encodes specific information to bind unique peptide targets. With this approach, we identify important specific residues for a given domain as those that show little conservation within an alignment of yeast domain family members (paralogs) but are conserved in an alignment of its direct relatives (orthologs). We find most of the yeast SH3 domain family members have maintained unique amino acid conservation patterns that suggest they bind peptide targets with high intrinsic specificity through varying degrees of non-canonical recognition. For a minority of domains, we predict a less diverse binding surface, likely requiring additional factors to bind targets specifically. We observe that our predictions are consistent with high throughput binding data, which suggests our approach can probe intrinsic binding specificity in any other interaction domain family that is maintained during evolution.

G Protein-Coupled Receptors Contain Two Conserved Packing Clusters

G protein-coupled receptors (GPCRs) have evolved a seven-transmembrane helix framework that is responsive to a wide range of extracellular signals. An analysis of the interior packing of family A GPCR crystal structures reveals two clusters of highly packed residues that facilitate tight transmembrane helix association. These clusters are centered on amino acid positions 2.47 and 4.53, which are highly conserved as alanine and serine, respectively. Ala2.47 mediates the interaction between helices H1 and H2, while Ser4.53 mediates the interaction between helices H3 and H4. The helical interfaces outside of these clusters are lined with residues that are more loosely packed, a structural feature that facilitates motion of helices H5, H6, and H7, which is required for receptor activation. Mutation of the conserved small side chain at position 4.53 within packing cluster 2 is shown to disrupt the structure of the visual receptor rhodopsin, whereas sites in packing cluster 1 (e.g., positions 1.46 and 2.47) are more tolerant to mutation but affect the overall stability of the protein. These findings reveal a common structural scaffold of GPCRs that is important for receptor folding and activation.

Methods used to study the oligomeric structure of G-protein-coupled receptors

G-protein-coupled receptors (GPCRs), which constitute the largest family of cell surface receptors, were originally thought to function as monomers, but are now recognized as being able to act in a wide range of oligomeric states and indeed, it is known that the oligomerization state of a GPCR can modulate its pharmacology and function. A number of experimental techniques have been devised to study GPCR oligomerization including those based upon traditional biochemistry such as blue-native PAGE (BN-PAGE), co-immunoprecipitation (Co-IP) and protein-fragment complementation assays (PCAs), those based upon resonance energy transfer, FRET, time-resolved FRET (TR-FRET), FRET spectrometry and bioluminescence resonance energy transfer (BRET). Those based upon microscopy such as FRAP, total internal reflection fluorescence microscopy (TIRFM), spatial intensity distribution analysis (SpIDA) and various single molecule imaging techniques. Finally with the solution of a growing number of crystal structures, X-ray crystallography must be acknowledged as an important source of discovery in this field. A different, but in many ways complementary approach to the use of more traditional experimental techniques, are those involving computational methods that possess obvious merit in the study of the dynamics of oligomer formation and function. Here, we summarize the latest developments that have been made in the methods used to study GPCR oligomerization and give an overview of their application.

Human native kappa opioid receptor functions not predicted by recombinant receptors: Implications for drug design

If activation of recombinant G protein-coupled receptors in host cells (by drugs or other ligands) has predictive value, similar data must be obtained with native receptors naturally expressed in tissues. Using mouse and human recombinant κ opioid receptors transfected into a host cell, two selectively-acting compounds (ICI204448, asimadoline) equi-effectively activated both receptors, assessed by measuring two different cell signalling pathways which were equally affected without evidence of bias. In mouse intestine, naturally expressing κ receptors within its nervous system, both compounds also equi-effectively activated the receptor, inhibiting nerve-mediated muscle contraction. However, whereas ICI204448 acted similarly in human intestine, where κ receptors are again expressed within its nervous system, asimadoline was inhibitory only at very high concentrations; instead, low concentrations of asimadoline reduced the activity of ICI204448. This demonstration of species-dependence in activation of native, not recombinant κ receptors may be explained by different mouse/human receptor structures affecting receptor expression and/or interactions with intracellular signalling pathways in native environments, to reveal differences in intrinsic efficacy between receptor agonists. These results have profound implications in drug design for κ and perhaps other receptors, in terms of recombinant-to-native receptor translation, species-dependency and possibly, a need to use human, therapeutically-relevant, not surrogate tissues.

Allosteric communication pipelines in G-protein-coupled receptors

The binding of ligands to G-protein-coupled receptors (GPCRs) in the extracellular region transmits the signal to the intracellular region to initiate coupling to effector proteins. The mechanism of this allosteric communication remains largely unexplored. Knowledge of the residues involved in the pipeline of the allosteric communication from the extracellular to the intracellular region will provide means to (a) design ligands with bias in potency towards one signaling pathway over others, and (b) design allosteric modulators that show subtype selectivity in GPCRs. In this review we describe the current state of the computational methods that provide insights into the allosteric communication in GPCRs and elucidate how this information can be used to design allosteric modulators.

Integrating structural and mutagenesis data to elucidate GPCR ligand binding

G protein-coupled receptors (GPCRs) represent the largest family of human membrane proteins, as well as drug targets. A recent boom in GPCR structural biology has provided detailed images of receptor ligand binding sites and interactions on the molecular level. An ever-increasing number of ligands is reported that exhibit activity through multiple receptors, binding in allosteric sites, and bias towards different intracellular signalling pathways. Furthermore, a wealth of single point mutants has accumulated in literature and public databases. Integrating these structural and mutagenesis data will help elucidate new GPCR ligand binding sites, and ultimately design drugs with tailored pharmacological activity.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Structure-Based Sequence Alignment of the Transmembrane Domains of All Human GPCRs: Phylogenetic, Structural and Functional Implications

The understanding of G-protein coupled receptors (GPCRs) is undergoing a revolution due to increased information about their signaling and the experimental determination of structures for more than 25 receptors. The availability of at least one receptor structure for each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide analysis to identify signatures involving the role of conserved residues, conserved contacts, and downstream signaling in the context of receptor structures. In this study, we align the transmembrane (TM) domains of all experimental GPCR structures to maximize the conserved inter-helical contacts. The resulting superfamily-wide GpcR Sequence-Structure (GRoSS) alignment of the TM domains for all human GPCR sequences is sufficient to generate a phylogenetic tree that correctly distinguishes all different GPCR classes, suggesting that the class-level differences in the GPCR superfamily are encoded at least partly in the TM domains. The inter-helical contacts conserved across all GPCR classes describe the evolutionarily conserved GPCR structural fold. The corresponding structural alignment of the inactive and active conformations, available for a few GPCRs, identifies activation hot-spot residues in the TM domains that get rewired upon activation. Many GPCR mutations, known to alter receptor signaling and cause disease, are located at these conserved contact and activation hot-spot residue positions. The GRoSS alignment places the chemosensory receptor subfamilies for bitter taste (TAS2R) and pheromones (Vomeronasal, VN1R) in the rhodopsin family, known to contain the chemosensory olfactory receptor subfamily. The GRoSS alignment also enables the quantification of the structural variability in the TM regions of experimental structures, useful for homology modeling and structure prediction of receptors. Furthermore, this alignment identifies structurally and functionally important residues in all human GPCRs. These residues can be used to make testable hypotheses about the structural basis of receptor function and about the molecular basis of disease-associated single nucleotide polymorphisms.

G-protein coupled receptors (GPCRs) are a large superfamily of integral membrane proteins that share a characteristic 7 transmembrane helix fold. They detect various molecules outside of the cell and signal their presence to the inside of the cell. At least half of the 800 human GPCRs are potential drug targets, so understanding their structure and function is critical. Experimental structures are now available for at least one receptor from each GPCR class. The structure of the 7 helix fold is highly conserved even for receptors with very low sequence similarity. We analyze the available experimental structures and compare the common inter-helical contacts. Our analysis leads to a unified sequence-structure alignment of the GPCR superfamily that can then be used as the starting point for structure prediction of all other GPCRs. A key result of our analysis is a list of conserved contact residues and activation “hot-spots” residues that are critical for GPCR folding and function. We propose that mutations and natural variants of amino acids at these locations in the GPCRs can dramatically influence their activation state and alter intracellular signaling. This provides hypotheses for the molecular mechanisms underlying disease causing mutants for any GPCR.

Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation

The structural basis of allosteric signaling in G protein-coupled receptors (GPCRs) is important in guiding design of therapeutics and understanding phenotypic consequences of genetic variation. The Evolutionary Trace (ET) algorithm previously proved effective in redesigning receptors to mimic the ligand specificities of functionally distinct homologs. We now expand ET to consider mutual information, with validation in GPCR structure and dopamine D2 receptor (D2R) function. The new algorithm, called ET-MIp, identifies evolutionarily relevant patterns of amino acid covariations. The improved predictions of structural proximity and D2R mutagenesis demonstrate that ET-MIp predicts functional interactions between residue pairs, particularly potency and efficacy of activation by dopamine. Remarkably, although most of the residue pairs chosen for mutagenesis are neither in the binding pocket nor in contact with each other, many exhibited functional interactions, implying at-a-distance coupling. The functional interaction between the coupled pairs correlated best with the evolutionary coupling potential derived from dopamine receptor sequences rather than with broader sets of GPCR sequences. These data suggest that the allosteric communication responsible for dopamine responses is resolved by ET-MIp and best discerned within a short evolutionary distance. Most double mutants restored dopamine response to wild-type levels, also suggesting that tight regulation of the response to dopamine drove the coevolution and intramolecular communications between coupled residues. Our approach provides a general tool to identify evolutionary covariation patterns in small sets of close sequence homologs and to translate them into functional linkages between residues.

Progress and challenges in predicting protein interfaces

The majority of biological processes are mediated via protein-protein interactions. Determination of residues participating in such interactions improves our understanding of molecular mechanisms and facilitates the development of therapeutics. Experimental approaches to identifying interacting residues, such as mutagenesis, are costly and time-consuming and thus, computational methods for this purpose could streamline conventional pipelines. Here we review the field of computational protein interface prediction. We make a distinction between methods which address proteins in general and those targeted at antibodies, owing to the radically different binding mechanism of antibodies. We organize the multitude of currently available methods hierarchically based on required input and prediction principles to provide an overview of the field.

Differences in allosteric communication pipelines in the inactive and active states of a GPCR

G-protein-coupled receptors (GPCRs) are membrane proteins that allosterically transduce the signal of ligand binding in the extracellular (EC) domain to couple to proteins in the intracellular (IC) domain. However, the complete pathway of allosteric communication from the EC to the IC domain, including the role of individual amino acids in the pathway is not known. Using the correlation in torsion angle movements calculated from microseconds-long molecular-dynamics simulations, we elucidated the allosteric pathways in three different conformational states of β2-adrenergic receptor (β2AR): 1), the inverse-agonist-bound inactive state; 2), the agonist-bound intermediate state; and (3), the agonist- and G-protein-bound fully active state. The inactive state is less dynamic compared with the intermediate and active states, showing dense clusters of allosteric pathways (allosteric pipelines) connecting the EC with the IC domain. The allosteric pipelines from the EC domain to the IC domain are weakened in the intermediate state, thus decoupling the EC domain from the IC domain and making the receptor more dynamic compared with the other states. Also, the orthosteric ligand-binding site becomes the initiator region for allosteric communication in the intermediate state. This finding agrees with the paradigm that the nature of the agonist governs the specific signaling state of the receptor. These results provide an understanding of the mechanism of allosteric communication in class A GPCRs. In addition, our analysis shows that mutations that affect the ligand efficacy, but not the binding affinity, are located in the allosteric pipelines. This clarifies the role of such mutations, which has hitherto been unexplained.

Sequence, structure and ligand binding evolution of rhodopsin-like G protein-coupled receptors: a crystal structure-based phylogenetic analysis

G protein-coupled receptors (GPCRs) form the largest family of membrane receptors in the human genome. Advances in membrane protein crystallization so far resulted in the determination of 24 receptors available as high-resolution atomic structures. We performed the first phylogenetic analysis of GPCRs based on the available set of GPCR structures. We present a new phylogenetic tree of known human rhodopsin-like GPCR sequences based on this structure set. We can distinguish the three separate classes of small-ligand binding GPCRs, peptide binding GPCRs, and olfactory receptors. Analyzing different structural subdomains, we found that small molecule binding receptors most likely have evolved from peptide receptor precursors, with a rhodopsin/S1PR1 ancestor, most likely an ancestral opsin, forming the link between both classes. A light-activated receptor therefore seems to be the origin of the small molecule hormone receptors of the central nervous system. We find hints for a common evolutionary path of both ligand binding site and central sodium/water binding site. Surprisingly, opioid receptors exhibit both a binding cavity and a central sodium/water binding site similar to the one of biogenic amine receptors instead of peptide receptors, making them seemingly prone to bind small molecule ligands, e.g. opiates. Our results give new insights into the relationship and the pharmacological properties of rhodopsin-like GPCRs.

Bioinformatics and evolution of vertebrate nociceptin and opioid receptors

G protein-coupled receptors (GPCRs) are ancestrally related membrane proteins on cells that mediate the pharmacological effect of most drugs and neurotransmitters. GPCRs are the largest group of membrane receptor proteins encoded in the human genome. One of the most famous types of GPCRs is the opioid receptors. Opioid family receptors consist of four closely related proteins expressed in all vertebrate brains and spinal cords examined to date. The three classical types of opioid receptors shown unequivocally to mediate analgesia in animal models and in humans are the mu- (MOR), delta- (DOR), and kappa-(KOR) opioid receptor proteins. The fourth and most recent member of the opioid receptor family discovered is the nociceptin or orphanin FQ receptor (ORL). The role of ORL and its ligands in producing analgesia is not as clear, with both analgesic and hyperalgesic effects reported. All four opioid family receptor genes were cloned from expressed mRNA in a number of vertebrate species, and there are enough sequences presently available to carry out bioinformatic analysis. This chapter presents the results of a comparative analysis of vertebrate opioid receptors using pharmacological studies, bioinformatics, and the latest data from human whole-genome studies. Results confirm our initial hypotheses that the four opioid receptor genes most likely arose by whole-genome duplication, that there is an evolutionary vector of opioid receptor type divergence in sequence and function, and that the hMOR gene shows evidence of positive selection or adaptive evolution in Homo sapiens.

Determinants of endogenous ligand specificity divergence among metabotropic glutamate receptors

To determine the structural origins of diverse ligand response specificities among metabotropic glutamate receptors (mGluRs), we combined computational approaches with mutagenesis and ligand response assays to identify specificity-determining residues in the group I receptor, mGluR1, and the group III receptors, mGluR4 and mGluR7. Among these, mGluR1 responds to L-glutamate effectively, whereas it binds weakly to another endogenous ligand, L-serine-O-phosphate (L-SOP), which antagonizes the effects of L-glutamate. In contrast, mGluR4 has in common with other group III mGluR that it is activated with higher potency and efficacy by L-SOP. mGluR7 differs from mGluR4 and other group III mGluR in that L-glutamate and L-SOP activate it with low potency and efficacy. Enhanced versions of the evolutionary trace (ET) algorithm were used to identify residues that when swapped between mGluR1 and mGluR4 increased the potency of L-SOP inhibition relative to the potency of L-glutamate activation in mGluR1 mutants and others that diminished the potency/efficacy of L-SOP for mGluR4 mutants. In addition, combining ET identified swaps from mGluR4 with one identified by computational docking produced mGluR7 mutants that respond with dramatically enhanced potency/efficacy to L-SOP. These results reveal that an early functional divergence between group I/II and group III involved variation at positions primarily at allosteric sites located outside of binding pockets, whereas a later divergence within group III occurred through sequence variation both at the ligand-binding pocket and at loops near the dimerization interface and interlobe hinge region. They also demonstrate the power of ET for identifying allosteric determinants of evolutionary importance.

Discovering co-occurring patterns and their biological significance in protein families

Background

The large influx of biological sequences poses the importance of identifying and correlating conserved regions in homologous sequences to acquire valuable biological knowledge. These conserved regions contain statistically significant residue associations as sequence patterns. Thus, patterns from two conserved regions co-occurring frequently on the same sequences are inferred to have joint functionality. A method for finding conserved regions in protein families with frequent co-occurrence patterns is proposed. The biological significance of the discovered clusters of conserved regions with co-occurrences patterns can be validated by their three-dimensional closeness of amino acids and the biological functionality found in those regions as supported by published work.

Methods

Using existing algorithms, we discovered statistically significant amino acid associations as sequence patterns. We then aligned and clustered them into Aligned Pattern Clusters (APCs) corresponding to conserved regions with amino acid conservation and variation. When one APC frequently co-occured with another APC, the two APCs have high co-occurrence. We then clustered APCs with high co-occurrence into what we refer to as Co-occurrence APC Clusters (Co-occurrence Clusters).

Results

Our results show that for Co-occurrence Clusters, the three-dimensional distance between their amino acids is closer than average amino acid distances. For the Co-occurrence Clusters of the ubiquitin and the cytochrome c families, we observed biological significance among the residing amino acids of the APCs within the same cluster. In ubiquitin, the residues are responsible for ubiquitination as well as conventional and unconventional ubiquitin-bindings. In cytochrome c, amino acids in the first co-occurrence cluster contribute to binding of other proteins in the electron transport chain, and amino acids in the second co-occurrence cluster contribute to the stability of the axial heme ligand.

Conclusions

Thus, our co-occurrence clustering algorithm can efficiently find and rank conserved regions that contain patterns that frequently co-occurring on the same proteins. Co-occurring patterns are biologically significant due to their three-dimensional closeness and other evidences reported in literature. These results play an important role in drug discovery as biologists can quickly identify the target for drugs to conduct detailed preclinical studies.

G Protein and β-arrestin signaling bias at the ghrelin receptor

The G protein-coupled ghrelin receptor GHSR1a is a potential pharmacological target for treating obesity and addiction because of the critical role ghrelin plays in energy homeostasis and dopamine-dependent reward. GHSR1a enhances growth hormone release, appetite, and dopamine signaling through G(q/11), G(i/o), and G(12/13) as well as β-arrestin-based scaffolds. However, the contribution of individual G protein and β-arrestin pathways to the diverse physiological responses mediated by ghrelin remains unknown. To characterize whether a signaling bias occurs for GHSR1a, we investigated ghrelin signaling in a number of cell-based assays, including Ca(2+) mobilization, serum response factor response element, stress fiber formation, ERK1/2 phosphorylation, and β-arrestin translocation, utilizing intracellular second loop and C-tail mutants of GHSR1a. We observed that GHSR1a and β-arrestin rapidly form metastable plasma membrane complexes following exposure to an agonist, but replacement of the GHSR1a C-tail by the tail of the vasopressin 2 receptor greatly stabilizes them, producing complexes observable on the plasma membrane and also in endocytic vesicles. Mutations of the contiguous conserved amino acids Pro-148 and Leu-149 in the GHSR1a intracellular second loop generate receptors with a strong bias to G protein and β-arrestin, respectively, supporting a role for conformation-dependent signaling bias in the wild-type receptor. Our results demonstrate more balance in GHSR1a-mediated ERK signaling from G proteins and β-arrestin but uncover an important role for β-arrestin in RhoA activation and stress fiber formation. These findings suggest an avenue for modulating drug abuse-associated changes in synaptic plasticity via GHSR1a and indicate the development of GHSR1a-biased ligands as a promising strategy for selectively targeting downstream signaling events.

A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness

The relationship between genotype mutations and phenotype variations determines health in the short term and evolution over the long term, and it hinges on the action of mutations on fitness. A fundamental difficulty in determining this action, however, is that it depends on the unique context of each mutation, which is complex and often cryptic. As a result, the effect of most genome variations on molecular function and overall fitness remains unknown and stands apart from population genetics theories linking fitness effect to polymorphism frequency. Here, we hypothesize that evolution is a continuous and differentiable physical process coupling genotype to phenotype. This leads to a formal equation for the action of coding mutations on fitness that can be interpreted as a product of the evolutionary importance of the mutated site with the difference in amino acid similarity. Approximations for these terms are readily computable from phylogenetic sequence analysis, and we show mutational, clinical, and population genetic evidence that this action equation predicts the effect of point mutations in vivo and in vitro in diverse proteins, correlates disease-causing gene mutations with morbidity, and determines the frequency of human coding polymorphisms, respectively. Thus, elementary calculus and phylogenetics can be integrated into a perturbation analysis of the evolutionary relationship between genotype and phenotype that quantitatively links point mutations to function and fitness and that opens a new analytic framework for equations of biology. In practice, this work explicitly bridges molecular evolution with population genetics with applications from protein redesign to the clinical assessment of human genetic variations.

Prediction and redesign of protein-protein interactions

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.

Bioinformatics tools for predicting GPCR gene functions

The automatic classification of GPCRs by bioinformatics methodology can provide functional information for new GPCRs in the whole 'GPCR proteome' and this information is important for the development of novel drugs. Since GPCR proteome is classified hierarchically, general ways for GPCR function prediction are based on hierarchical classification. Various computational tools have been developed to predict GPCR functions; those tools use not simple sequence searches but more powerful methods, such as alignment-free methods, statistical model methods, and machine learning methods used in protein sequence analysis, based on learning datasets. The first stage of hierarchical function prediction involves the discrimination of GPCRs from non-GPCRs and the second stage involves the classification of the predicted GPCR candidates into family, subfamily, and sub-subfamily levels. Then, further classification is performed according to their protein-protein interaction type: binding G-protein type, oligomerized partner type, etc. Those methods have achieved predictive accuracies of around 90 %. Finally, I described the future subject of research of the bioinformatics technique about functional prediction of GPCR.

Structural-functional analysis of the third transmembrane domain of the corticotropin-releasing factor type 1 receptor: role in activation and allosteric antagonism

The corticotropin-releasing factor (CRF) type 1 receptor (CRF1R) for the 41-amino acid peptide CRF is a class B G protein-coupled receptor, which plays a key role in the response of our body to stressful stimuli and the maintenance of homeostasis by regulating neural and endocrine functions. CRF and related peptides, such as sauvagine, bind to the extracellular regions of CRF1R and activate the receptor. In contrast, small nonpeptide antagonists, which are effective against stress-related disorders, such as depression and anxiety, have been proposed to interact with the helical transmembrane domains (TMs) of CRF1R and allosterically antagonize peptide binding and receptor activation. Here, we aimed to elucidate the role of the third TM (TM3) in the molecular mechanisms underlying activation of CRF1R. TM3 was selected because its tilted orientation, relative to the membrane, allows its residues to establish key interactions with ligands, other TM helices, and the G protein. Using a combination of pharmacological, biochemical, and computational approaches, we found that Phe-203(3.40) and Gly-210(3.47) in TM3 play an important role in receptor activation. Our experimental findings also suggest that Phe-203(3.40) interacts with nonpeptide antagonists.

Toward an understanding of agonist binding to human Orexin-1 and Orexin-2 receptors with G-protein-coupled receptor modeling and site-directed mutagenesis

The class A G-protein-coupled receptors (GPCRs) Orexin-1 (OX1) and Orexin-2 (OX2) are located predominantly in the brain and are linked to a range of different physiological functions, including the control of feeding, energy metabolism, modulation of neuro-endocrine function, and regulation of the sleep-wake cycle. The natural agonists for OX1 and OX2 are two neuropeptides, Orexin-A and Orexin-B, which have activity at both receptors. Site-directed mutagenesis (SDM) has been reported on both the receptors and the peptides and has provided important insight into key features responsible for agonist activity. However, the structural interpretation of how these data are linked together is still lacking. In this work, we produced and used SDM data, homology modeling followed by MD simulation, and ensemble-flexible docking to generate binding poses of the Orexin peptides in the OX receptors to rationalize the SDM data. We also developed a protein pairwise similarity comparing method (ProS) and a GPCR-likeness assessment score (GLAS) to explore the structural data generated within a molecular dynamics simulation and to help distinguish between different GPCR substates. The results demonstrate how these newly developed methods of structural assessment for GPCRs can be used to provide a working model of neuropeptide-Orexin receptor interaction.

Relevance of rhodopsin studies for GPCR activation

Rhodopsin, the dim-light photoreceptor present in the rod cells of the retina, is both a retinal-binding protein and a G protein-coupled receptor (GPCR). Due to this conjunction, it benefits from an arsenal of spectroscopy techniques that can be used for its characterization, while being a model system for the important family of Class A (also referred to as "rhodopsin-like") GPCRs. For instance, rhodopsin has been a crucial player in the field of GPCR structural biology. Until 2007, it was the only GPCR for which a high-resolution crystal structure was available, so all structure-activity analyses on GPCRs, from structure-based drug discovery to studies of structural changes upon activation, were based on rhodopsin. At present, about a third of currently available GPCR structures are still from rhodopsin. In this review, I show some examples of how these structures can still be used to gain insight into general aspects of GPCR activation. First, the analysis of the third intracellular loop in rhodopsin structures allows us to gain an understanding of the structural and dynamic properties of this region, which is absent (due to protein engineering or poor electron density) in most of the currently available GPCR structures. Second, a detailed analysis of the structure of the transmembrane domains in inactive, intermediate and active rhodopsin structures allows us to detect early conformational changes in the process of ligand-induced GPCR activation. Finally, the analysis of a conserved ligand-activated transmission switch in the transmembrane bundle of GPCRs in the context of the rhodopsin activation cycle, allows us to suggest that the structures of many of the currently available agonist-bound GPCRs may correspond to intermediate active states. While the focus in GPCR structural biology is inevitably moving away from rhodopsin, in other aspects rhodopsin is still at the forefront. For instance, the first studies of the structural basis of disease mutants in GPCRs, or the most detailed analysis of cellular GPCR signal transduction networks using a systems biology approach, have been carried out in rhodopsin. Finally, due again to its unique properties among GPCRs, rhodopsin will likely play an important role in the application of X-ray free electron laser crystallography to time-resolved structural biology in membrane proteins. Rhodopsin, thus, still remains relevant as a model system to study the molecular mechanisms of GPCR activation. This article is part of a Special Issue entitled: Retinal Proteins-You can teach an old dog new tricks.

Accounting for epistatic interactions improves the functional analysis of protein structures

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure.

Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions.

Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction.

Contact:lichtarge@bcm.edu

Supplementary information:Supplementary data are available at Bioinformatics online.