Network analysis to uncover the structural communication in GPCRs

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

Protein conformational switch discerned via network centrality properties

Network analysis has emerged as a powerful tool for examining structural biology systems. The spatial organization of the components of a biomolecular structure has been rendered as a graph representation and analyses have been performed to deduce the biophysical and mechanistic properties of these components. For proteins, the analysis of protein structure networks (PSNs), especially via network centrality measurements and cluster coefficients, has led to identifying amino acid residues that play key functional roles and classifying amino acid residues in general. Whether these network properties examined in various studies are sensitive to subtle (yet biologically significant) conformational changes remained to be addressed. Here, we focused on four types of network centrality properties (betweenness, closeness, degree, and eigenvector centralities) for conformational changes upon ligand binding of a sensor protein (constitutive androstane receptor) and an allosteric enzyme (ribonucleotide reductase). We found that eigenvector centrality is sensitive and can distinguish salient structural features between protein conformational states while other centrality measures, especially closeness centrality, are less sensitive and rather generic with respect to the structural specificity. We also demonstrated that an ensemble-informed, modified PSN with static edges removed (which we term PSN*) has enhanced sensitivity at discerning structural changes.

Structural aspects of rod opsin and their implication in genetic diseases

Vision in dim-light conditions is triggered by photoactivation of rhodopsin, the visual pigment of rod photoreceptor cells. Rhodopsin is made of a protein, the G protein coupled receptor (GPCR) opsin, and the chromophore 11-cis-retinal. Vertebrate rod opsin is the GPCR best characterized at the atomic level of detail. Since the release of the first crystal structure 20 years ago, a huge number of structures have been released that, in combination with valuable spectroscopic determinations, unveiled most aspects of the photobleaching process. A number of spontaneous mutations of rod opsin have been found linked to vision-impairing diseases like autosomal dominant or autosomal recessive retinitis pigmentosa (adRP or arRP, respectively) and autosomal congenital stationary night blindness (adCSNB). While adCSNB is mainly caused by constitutive activation of rod opsin, RP shows more variegate determinants affecting different aspects of rod opsin function. The vast majority of missense rod opsin mutations affects folding and trafficking and is linked to adRP, an incurable disease that awaits light on its molecular structure determinants. This review article summarizes all major structural information available on vertebrate rod opsin conformational states and the insights gained so far into the structural determinants of adCSNB and adRP linked to rod opsin mutations. Strategies to design small chaperones with therapeutic potential for selected adRP rod opsin mutants will be discussed as well.

Dynamics and structural communication in the ternary complex of fully phosphorylated V2 vasopressin receptor, vasopressin, and β-arrestin 1

G protein-coupled receptors (GPCRs) are critically regulated by arrestins, which not only desensitize G-protein signaling but also initiate a G protein-independent wave of signaling. The information from structure determination was herein exploited to build a structural model of the ternary complex, comprising fully phosphorylated V2 vasopressin receptor (V2R), the agonist arginine vasopressin (AVP), and β-arrestin 1 (β-arr1). Molecular simulations served to explore dynamics and structural communication in the ternary complex. Flexibility and mechanical profiles reflect fold of V2R and β-arr1. Highly conserved amino acids tend to behave as hubs in the structure network and contribute the most to the mechanical rigidity of V2R seven-helix bundle and of β-arr1. Two structurally and dynamically distinct receptor-arrestin interfaces assist the twist of the N- and C-terminal domains (ND and CD, respectively) of β-arr1 with respect to each other, which is linked to arrestin activation. While motion of the ND is essentially assisted by the fully phosphorylated C-tail of V2R (V2RCt), that of CD is assisted by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. In the presence of the receptor, the β-arr1 inter-domain twist angle correlates with the modes describing the essential subspace of the ternary complex. β-arr1 motions are also influenced by the anchoring to the membrane of the C-edge-loops in the β-arr1-CD. Overall fluctuations reveal a coupling between motions of the agonist binding site and of β-arr1-ND, which are in allosteric communication between each other. Mechanical rigidity points, often acting as hubs in the structure network and distributed along the main axis of the receptor helix bundle, contribute to establish a preferential communication pathway between agonist ligand and the ND of arrestin. Such communication, mediated by highly conserved amino acids, involves also the first amino acid in the arrestin C-tail, which is highly dynamic and is involved in clathrin-mediated GPCR internalization.

Evolutionary-Conserved Allosteric Properties of Three Neuronal Calcium Sensor Proteins

Neuronal Calcium Sensors (NCS) are highly conserved proteins specifically expressed in neurons. Calcium (Ca²⁺)-binding to their EF-hand motifs results in a conformational change, which is crucial for the recognition of a specific target and the downstream biological process. Here we present a comprehensive analysis of the allosteric communication between Ca²⁺-binding sites and the target interfaces of three NCS, namely NCS1, recoverin (Rec), and GCAP1. In particular, Rec was investigated in different Ca²⁺-loading states and in complex with a peptide from the Rhodopsin Kinase (GRK1) while NCS1 was studied in a Ca²⁺-loaded state in complex with either the same GRK1 target or a peptide from the D₂ Dopamine receptor. A Protein Structure Network (PSN) accounting for persistent non-covalent interactions between amino acids was built for each protein state based on exhaustive Molecular Dynamics simulations. Structural network analysis helped unveiling the role of key amino acids in allosteric mechanisms and their evolutionary conservation among homologous proteins. Results for NCS1 highlighted allosteric inter-domain interactions between Ca²⁺-binding motifs and residues involved in target recognition. Robust long range, allosteric protein-target interactions were found also in Rec, in particular originating from the EF3 motif. Interestingly, Tyr 86, involved the hydrophobic packing of the N-terminal domain, was found to be a key residue for both intra- and inter-molecular communication with EF3, regardless of the presence of target or Ca²⁺ ions. Finally, based on a comprehensive topological PSN analysis for Rec, NCS1, and GCAP1 and multiple sequence alignments with homolog proteins, we propose that an evolution-driven correlation may exist between the amino acids mediating the highest number of persistent interactions (high-degree hubs) and their conservation. Such conservation is apparently fundamental for the specific structural dynamics required in signaling events.

A Small Chaperone Improves Folding and Routing of Rhodopsin Mutants Linked to Inherited Blindness

The autosomal dominant form of retinitis pigmentosa (adRP) is a blindness-causing conformational disease largely linked to mutations of rhodopsin. Molecular simulations coupled to the graph-based protein structure network (PSN) analysis and in vitro experiments were conducted to determine the effects of 33 adRP rhodopsin mutations on the structure and routing of the opsin protein. The integration of atomic and subcellular levels of analysis was accomplished by the linear correlation between indices of mutational impairment in structure network and in routing. The graph-based index of structural perturbation served also to divide the mutants in four clusters, consistent with their differences in subcellular localization and responses to 9-cis retinal. The stability core of opsin inferred from PSN analysis was targeted by virtual screening of over 300,000 anionic compounds leading to the discovery of a reversible orthosteric inhibitor of retinal binding more effective than retinal in improving routing of three adRP mutants.

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In silico and in vitro analyses of adRP rhodopsin mutants bridged folding and routing

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Structure network analysis grouped mutants amenable to treatment with small chaperones

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Virtual compound screening against the stability core of opsin found a small chaperone

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The pharmacoperone is a reversible orthosteric inhibitor of retinal binding

Visualization and analysis of non-covalent contacts using the Protein Contacts Atlas

Visualizations of biomolecular structures empower us to gain insights into biological functions, generate testable hypotheses, and communicate biological concepts. Typical visualizations (such as ball and stick) primarily depict covalent bonds. In contrast, non-covalent contacts between atoms, which govern normal physiology, pathogenesis, and drug action, are seldom visualized. We present the Protein Contacts Atlas, an interactive resource of non-covalent contacts from over 100,000 PDB crystal structures. We developed multiple representations for visualization and analysis of non-covalent contacts at different scales of organization: atoms, residues, secondary structure, subunits, and entire complexes. The Protein Contacts Atlas enables researchers from different disciplines to investigate diverse questions in the framework of non-covalent contacts, including the interpretation of allostery, disease mutations and polymorphisms, by exploring individual subunits, interfaces, and protein-ligand contacts and by mapping external information. The Protein Contacts Atlas is available at http://www.mrc-lmb.cam.ac.uk/pca/ and also through PDBe.

Uncovering GPCR and G Protein Function by Protein Structure Network Analysis

Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used for investigating structural communication in biomolecular systems. Information on the system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). This chapter reports on selected applications of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs) and G proteins. Strategies to highlight changes in structural communication caused by mutations, ligand and protein binding are described. Conserved amino acids, sites of misfolding mutations, or ligands acting as functional switches tend to behave as hubs in the native structure networks. Densely linked regions in the protein structure graphs could be identified as playing central roles in protein stability and function. Changes in the communication pathway fingerprints depending on the bound ligand or following amino acid mutation could be highlighted as well. A bridge between misfolding and misrouting could be established in rhodopsin mutants linked to inherited blindness. The analysis of native network perturbations by misfolding mutations served to infer key structural elements of protein responsiveness to small chaperones with implications for drug discovery.

Structure network analysis to gain insights into GPCR function

G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM–NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM–NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor.

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Use of network model to explore dynamic and allosteric properties of three GPCR homodimers

We used an elastic network model and protein structure network to study three class A GPCR homodimers.

Protein-Protein Interface and Disease: Perspective from Biomolecular Networks

Protein-protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein-protein interactions. Characterizing protein-protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein-protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.