Crystal structures of a Rab protein in its inactive and active conformations

We have determined crystal structures of Sec4, a member of the Rab family in the G protein superfamily, in two states: bound to GDP, and to a non-hydrolyzable GTP analog, guanosine-5'-(beta, gamma)-imidotriphosphate (GppNHp). This represents the first structure of a Rab protein bound to GDP. Sec4 in both states grossly resembles other G proteins bound to GDP and GppNHp. In Sec4-GppNHp, structural features common to active Rab proteins are observed. In Sec4-GDP, the switch I region is highly disordered and displaced relative to the switch I region of Ras-GDP. In two of the four molecules of Sec4-GDP in the asymmetric unit of the Sec4-GDP crystals, the switch II region adopts a conformation similar to that seen in the structure of the small G protein Ran bound to GDP. This allows residues threonine 76, glutamate 80, and arginine 81 of Sec4 to make contacts with other conserved residues and water molecules important for nucleotide binding. In the other two molecules in the asymmetric unit, these interactions do not take place. This structural variability in both the switch I and switch II regions of GDP-bound Sec4 provides a possible explanation for the high off-rate of GDP bound to Sec4, and suggests a mechanism for regulation of the GTPase cycle of Rab proteins by GDI proteins.     

Identification of transient hub proteins and the possible structural basis for their multiple interactions

Proteins that can interact with multiple partners play central roles in the network of protein-protein interactions. They are called hub proteins, and recently it was suggested that an abundance of intrinsically disordered regions on their surfaces facilitates their binding to multiple partners. However, in those studies, the hub proteins were identified as proteins with multiple partners, regardless of whether the interactions were transient or permanent. As a result, a certain number of hub proteins are subunits of stable multi-subunit proteins, such as supramolecules. It is well known that stable complexes and transient complexes have different structural features, and thus the statistics based on the current definition of hub proteins will hide the true nature of hub proteins. Therefore, in this paper, we first describe a new approach to identify proteins with multiple partners dynamically, using the Protein Data Bank, and then we performed statistical analyses of the structural features of these proteins. We refer to the proteins as transient hub proteins or sociable proteins, to clarify the difference with hub proteins. As a result, we found that the main difference between sociable and nonsociable proteins is not the abundance of disordered regions, in contrast to the previous studies, but rather the structural flexibility of the entire protein. We also found greater predominance of charged and polar residues in sociable proteins than previously reported.     

Structural and molecular characterization of a preferred protein interaction surface on G protein beta gamma subunits

G protein betagamma subunits associate with many binding partners in cellular signaling cascades. In previous work, we used random-peptide phage display screening to identify a diverse family of peptides that bound to a common surface on Gbetagamma subunits and blocked a subset of Gbetagamma effectors. Later studies showed that one of the peptides caused G protein activation through a novel Gbetagamma-dependent, nucleotide exchange-independent mechanism. Here we report the X-ray crystal structure of Gbeta(1)gamma(2) bound to this peptide, SIGK (SIGKAFKILGYPDYD), at 2.7 A resolution. SIGK forms a helical structure that binds the same face of Gbeta(1) as the switch II region of Galpha. The interaction interface can be subdivided into polar and nonpolar interfaces that together contain a mixture of binding determinants that may be responsible for the ability of this surface to recognize multiple protein partners. Systematic mutagenic analysis of the peptide-Gbeta(1) interface indicates that distinct sets of amino acids within this interface are required for binding of different peptides. Among these unique amino acid interactions, specific electrostatic binding contacts within the polar interface are required for peptide-mediated subunit dissociation. The data provide a mechanistic basis for multiple target recognition by Gbetagamma subunits with diverse functional interactions within a common interface and suggest that pharmacological targeting of distinct regions within this interface could allow for selective manipulation of Gbetagamma-dependent signaling pathways.     

Hidden partners: Using cross‐docking calculations to predict binding sites for proteins with multiple interactions

Protein‐protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein‐protein interactions. Cross‐docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross‐docking simulations of 358 proteins with 2 different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity‐sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross‐docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, that is, partners not included in the original cross‐docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.     

The Inherent Dynamics and Interaction Sites of the SARS-CoV-2 Nucleocapsid N-Terminal Region

The nucleocapsid protein is one of four structural proteins encoded by SARS-CoV-2 and plays a central role in packaging viral RNA and manipulating the host cell machinery, yet its dynamic behavior and promiscuity in nucleotide binding has made standard structural methods to address its atomic-resolution details difficult. To begin addressing the SARS-CoV-2 nucleocapsid protein interactions with both RNA and the host cell along with its dynamic behavior, we have specifically focused on the folded N-terminal domain (NTD) and its flanking regions using nuclear magnetic resonance solution studies. Studies performed here reveal a large repertoire of interactions, which includes a temperature-dependent self-association mediated by the disordered flanking regions that also serve as binding sites for host cell cyclophilin-A while nucleotide binding is largely mediated by the central NTD core. NMR studies that include relaxation experiments have revealed the complicated dynamic nature of this viral protein. Specifically, while much of the N-terminal core domain exhibits micro-millisecond motions, a central β-hairpin shows elevated inherent flexibility on the pico-nanosecond timescale and the serine/arginine-rich region of residues 176–209 undergoes multiple exchange phenomena. Collectively, these studies have begun to reveal the complexities of the nucleocapsid protein dynamics and its preferred interaction sites with its biological targets.     

Analysis of molecular recognition features (MoRFs)

Several proteomic studies in the last decade revealed that many proteins are either completely disordered or possess long structurally flexible regions. Many such regions were shown to be of functional importance, often allowing a protein to interact with a large number of diverse partners. Parallel to these findings, during the last five years structural bioinformatics has produced an explosion of results regarding protein-protein interactions and their importance for cell signaling. We studied the occurrence of relatively short (10-70 residues), loosely structured protein regions within longer, largely disordered sequences that were characterized as bound to larger proteins. We call these regions molecular recognition features (MoRFs, also known as molecular recognition elements, MoREs). Interestingly, upon binding to their partner(s), MoRFs undergo disorder-to-order transitions. Thus, in our interpretation, MoRFs represent a class of disordered region that exhibits molecular recognition and binding functions. This work extends previous research showing the importance of flexibility and disorder for molecular recognition. We describe the development of a database of MoRFs derived from the RCSB Protein Data Bank and present preliminary results of bioinformatics analyses of these sequences. Based on the structure adopted upon binding, at least three basic types of MoRFs are found: α-MoRFs, β-MoRFs, and ι-MoRFs, which form α-helices, β-strands, and irregular secondary structure when bound, respectively. Our data suggest that functionally significant residual structure can exist in MoRF regions prior to the actual binding event. The contribution of intrinsic protein disorder to the nature and function of MoRFs has also been addressed. The results of this study will advance the understanding of protein-protein interactions and help towards the future development of useful protein-protein binding site predictors.     

Chimeric G alpha i2/G alpha 13 proteins reveal the structural requirements for the binding and activation of the RGS-like (RGL)-containing Rho guanine nucleotide exchange factors (GEFs) by G alpha 13

The alpha-subunit of G proteins of the G(12/13) family stimulate Rho by their direct binding to the RGS-like (RGL) domain of a family of Rho guanine nucleotide exchange factors (RGL-RhoGEFs) that includes PDZ-RhoGEF (PRG), p115RhoGEF, and LARG, thereby regulating cellular functions as diverse as shape and movement, gene expression, and normal and aberrant cell growth. The structural features determining the ability of G alpha(12/13) to bind RGL domains and the mechanism by which this association results in the activation of RGL-RhoGEFs are still poorly understood. Here, we explored the structural requirements for the functional interaction between G alpha(13) and RGL-RhoGEFs based on the structure of RGL domains and their similarity with the area by which RGS4 binds the switch region of G alpha(i) proteins. Using G alpha(i2), which does not bind RGL domains, as the backbone in which G alpha(13) sequences were swapped or mutated, we observed that the switch region of G alpha(13) is strictly necessary to bind PRG, and specific residues were identified that are critical for this association, likely by contributing to the binding surface. Surprisingly, the switch region of G alpha(13) was not sufficient to bind RGL domains, but instead most of its GTPase domain is required. Furthermore, membrane localization of G alpha(13) and chimeric G alpha(i2) proteins was also necessary for Rho activation. These findings revealed the structural features by which G alpha(13) interacts with RGL domains and suggest that molecular interactions occurring at the level of the plasma membrane are required for the functional activation of the RGL-containing family of RhoGEFs.     

Regional covariation and its application for predicting protein contact patches

Correlated mutation analysis (CMA) is an effective approach for predicting functional and structural residue interactions from multiple sequence alignments (MSAs) of proteins. As nearby residues may also play a role in a given functional interaction, we were interested in seeing whether covarying sites were clustered, and whether this could be used to enhance the predictive power of CMA. A large‐scale search for coevolving regions within protein domains revealed that if two sites in a MSA covary, then neighboring sites in the alignment also typically covary, resulting in clusters of covarying residues. The program PatchD( http://www.uhnres.utoronto.ca/labs/tillier/ ) was developed to measure the covariation between disconnected sequence clusters to reveal patch covariation. Patches that exhibit strong covariation identify multiple residues that are generally nearby in the protein structure, suggesting that the detection of covarying patches can be used in conjunction with traditional CMA approaches to reveal functional interaction partners. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Exploring functional roles of multibinding protein interfaces

Cellular processes are highly interconnected and many proteins are shared in different pathways. Some of these shared proteins or protein families may interact with diverse partners using the same interface regions; such multibinding proteins are the subject of our study. The main goal of our study is to attempt to decipher the mechanisms of specific molecular recognition of multiple diverse partners by promiscuous protein regions. To address this, we attempt to analyze the physicochemical properties of multibinding interfaces and highlight the major mechanisms of functional switches realized through multibinding. We find that only 5% of protein families in the structure database have multibinding interfaces, and multibinding interfaces do not show any higher sequence conservation compared with the background interface sites. We highlight several important functional mechanisms utilized by multibinding families. (a) Overlap between different functional pathways can be prevented by the switches involving nearby residues of the same interfacial region. (b) Interfaces can be reused in pathways where the substrate should be passed from one protein to another sequentially. (c) The same protein family can develop different specificities toward different binding partners reusing the same interface; and finally, (d) inhibitors can attach to substrate binding sites as substrate mimicry and thereby prevent substrate binding.     

Structural stability of binding sites: Consequences for binding affinity and allosteric effects

During the course of biological function, proteins interact with other proteins, ligands, substrates, inhibitors, etc. These interactions occur at precisely defined locations within the protein but their effects are sometimes propagated to distal regions, triggering highly specific responses. These effects can be used as signals directed to activate or inhibit other sites, modulate interactions with other molecules, and/or establish inter‐molecular communication networks. During the past decade, it has become evident that the energy of stabilization of the protein structure is not evenly distributed throughout the molecule and that, under native conditions, proteins lack global cooperativity and are characterized by the occurrence of multiple independent local unfolding events. From a biological point of view, it is important to assess if this uneven distribution reflects specific functional requirements. For example, are binding sites more likely to be found in well structured regions, unstable regions, or mixed regions? In this article, we have addressed these questions by performing a structure‐based thermodynamic stability analysis of non‐structurally homologous proteins for which high resolution structures of their complexes with specific ligands are available. The results of these studies indicate that for all 16 proteins considered, the binding sites have a dual character and are characterized by the presence of regions with very low structural stability and regions with high stability. In many cases the low stability regions are loops that become stable and cover a significant portion of low molecular weight ligands upon binding. For enzymes, catalytic residues are usually, but not always, located in regions with high structural stability. It is shown that this arrangement provides significant advantages for the optimization of binding affinity of small ligands. In allosteric enzymes, low stability regions in the regulatory site are shown to play a crucial role in the transmission of information to the catalytic site. Proteins 2000;41:63–71. © 2000 Wiley‐Liss, Inc.     

Myristoylation exerts direct and allosteric effects on Gα conformation and dynamics in solution

Coupling of heterotrimeric G proteins to activated G protein-coupled receptors results in nucleotide exchange on the Gα subunit, which in turn decreases its affinity for both Gβγ and activated receptors. N-Terminal myristoylation of Gα subunits aids in membrane localization of inactive G proteins. Despite the presence of the covalently attached myristoyl group, Gα proteins are highly soluble after GTP binding. This study investigated factors facilitating the solubility of the activated, myristoylated protein. In doing so, we also identified myristoylation-dependent differences in regions of Gα known to play important roles in interactions with receptors, effectors, and nucleotide binding. Amide hydrogen-deuterium exchange and site-directed fluorescence of activated proteins revealed a solvent-protected amino terminus that was enhanced by myristoylation. Furthermore, fluorescence quenching confirmed that the myristoylated amino terminus is in proximity to the Switch II region in the activated protein. Myristoylation also stabilized the interaction between the guanine ring and the base of the α5 helix that contacts the bound nucleotide. The allosteric effects of myristoylation on protein structure, function, and localization indicate that the myristoylated amino terminus of Gα(i) functions as a myristoyl switch, with implications for myristoylation in the stabilization of nucleotide binding and in the spatial regulation of G protein signaling.     

Active and Inactive Cdc42 Differ in Their Insert Region Conformational Dynamics

Cell division control protein 42 homolog (Cdc42) protein, a Ras superfamily GTPase, regulates cellular activities, including cancer progression. Using all-atom molecular dynamics (MD) simulations and essential dynamic analysis, we investigated the structure and dynamics of the catalytic domains of GDP-bound (inactive) and GTP-bound (active) Cdc42 in solution. We discovered substantial differences in the dynamics of the inactive and active forms, particularly in the “insert region” (residues 122–135), which plays a role in Cdc42 activation and binding to effectors. The insert region has larger conformational flexibility in the GDP-bound Cdc42 than in the GTP-bound Cdc42. The G2 loop and switch I at the effector lobe of the catalytic domain exhibit large conformational changes in both the GDP- and the GTP-bound systems, but in the GTP-bound Cdc42, the switch I interactions with GTP are retained. Oncogenic mutations were identified in the Ras superfamily. In Cdc42, the G12V and Q61L mutations decrease the GTPase activity. We simulated these mutations in both GDP- and GTP-bound Cdc42. Although the overall structural organization is quite similar between the wild type and the mutants, there are small differences in the conformational dynamics, especially in the two switch regions. Taken together, the G12V and Q61L mutations may play a role similar to their K-Ras counterparts in nucleotide binding and activation. The conformational differences, which are mainly in the insert region and, to a lesser extent, in the switch regions flanking the nucleotide binding site, can shed light on binding and activation. We propose that the differences are due to a network of hydrogen bonds that gets disrupted when Cdc42 is bound to GDP, a disruption that does not exist in other Rho GTPases. The differences in the dynamics between the two Cdc42 states suggest that the inactive conformation has reduced ability to bind to effectors.     

Structural basis of beta-adrenergic receptor function

Receptors that mediate their actions by stimulating guanine nucleotide binding regulatory proteins (G proteins) share structural as well as functional similarities. The structural motif characteristic of receptors of this class includes seven hydrophobic putative transmembrane domains linked by hydrophilic loops. Genetic analysis of the beta-adrenergic receptor (beta AR) revealed that the ligand binding domain of this receptor, like that of rhodopsin, involves residues within the hydrophobic core of the protein. On the basis of these studies, a model for ligand binding to the receptor has been developed in which the amino group of an agonist or antagonist is anchored to the receptor through the carboxylate side chain of Asp113 in the third transmembrane helix. Other interactions between specific residues of the receptor and functional groups on the ligand have also been proposed. The interaction between the beta AR and the G protein Gs has been shown to involve an intracellular region that is postulated to form an amphiphilic alpha helix. This region of the beta AR is also critical for sequestration, which accompanies agonist-mediated desensitization, to occur. Structural similarities among G protein-linked receptors suggest that the information gained from the genetic analysis of the beta AR should help define functionally important regions of other receptors of this class.     

Multispecificity of a recombinant anti‐ras monoclonal antibody

Recombinant monoclonal antibodies (Ab's) have widespread application as research tools, diagnostic reagents and as biotherapeutics. Whilst studying the cellular molecular switch protein m‐ras, a recombinant monoclonal antibody to m‐ras was generated for use as a research tool. Antibody genes from a single rabbit B cell secreting IgG to an m‐ras specific peptide sequence were expressed in mammalian cells, and monoclonal rabbit IgG binding was characterized by ELISA and peptide array blotting. Although the monoclonal Ab was selected for specificity to m‐ras peptide, it also bound to both recombinant full‐length m‐ras and h‐ras proteins. The cross‐reactive binding of the monoclonal Ab to h‐ras was defined by peptide array blot revealing that the Ab showed preference for peptide sequences containing multiple positively charged amino acid residues. These data reinforce the concept of antibody multispecificity through multiple interactions of the Ab paratope with diverse polypeptides. They also emphasize the importance of immunogen and Ab selection processes when generating recombinant monoclonal Ab's.     

The structural GDP/GTP cycle of human Arf6

The small GTP-binding protein Arf6 coordinates membrane traffic at the plasma membrane with aspects of cytoskeleton organization. This function does not overlap with that of other members of the ADP-ribosylation factor (Arf) family, although their switch regions, which are their major sites of interaction with regulators and effectors, have virtually identical sequences. Here we report the crystal structure of full-length, non-myristoylated human Arf6 bound to GTPγS. Unlike their GDP-bound forms, the active forms of Arf6 and Arf1 are very similar. Thus, the switch regions are discriminatory elements between Arf isoforms in their inactive but not in their active forms, a property that may generalize to other families of small G proteins. This suggests that GTP-bound Arfs may establish specific interactions outside the switch regions and/or be recognized in their cellular context rather than as isolated proteins. The structure also allows further insight into the lack of spontaneous GTPase activity of Arf proteins.     

Prediction of Protein Binding Regions in Disordered Proteins

Many disordered proteins function via binding to a structured partner and undergo a disorder-to-order transition. The coupled folding and binding can confer several functional advantages such as the precise control of binding specificity without increased affinity. Additionally, the inherent flexibility allows the binding site to adopt various conformations and to bind to multiple partners. These features explain the prevalence of such binding elements in signaling and regulatory processes. In this work, we report ANCHOR, a method for the prediction of disordered binding regions. ANCHOR relies on the pairwise energy estimation approach that is the basis of IUPred, a previous general disorder prediction method. In order to predict disordered binding regions, we seek to identify segments that are in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner. The performance of ANCHOR was found to be largely independent from the amino acid composition and adopted secondary structure. Longer binding sites generally were predicted to be segmented, in agreement with available experimentally characterized examples. Scanning several hundred proteomes showed that the occurrence of disordered binding sites increased with the complexity of the organisms even compared to disordered regions in general. Furthermore, the length distribution of binding sites was different from disordered protein regions in general and was dominated by shorter segments. These results underline the importance of disordered proteins and protein segments in establishing new binding regions. Due to their specific biophysical properties, disordered binding sites generally carry a robust sequence signal, and this signal is efficiently captured by our method. Through its generality, ANCHOR opens new ways to study the essential functional sites of disordered proteins.     

Design of multispecific protein sequences using probabilistic graphical modeling

In nature, proteins partake in numerous protein– protein interactions that mediate their functions. Moreover, proteins have been shown to be physically stable in multiple structures, induced by cellular conditions, small ligands, or covalent modifications. Understanding how protein sequences achieve this structural promiscuity at the atomic level is a fundamental step in the drug design pipeline and a critical question in protein physics. One way to investigate this subject is to computationally predict protein sequences that are compatible with multiple states, i.e., multiple target structures or binding to distinct partners. The goal of engineering such proteins has been termed multispecific protein design. We develop a novel computational framework to efficiently and accurately perform multispecific protein design. This framework utilizes recent advances in probabilistic graphical modeling to predict sequences with low energies in multiple target states. Furthermore, it is also geared to specifically yield positional amino acid probability profiles compatible with these target states. Such profiles can be used as input to randomly bias high‐throughput experimental sequence screening techniques, such as phage display, thus providing an alternative avenue for elucidating the multispecificity of natural proteins and the synthesis of novel proteins with specific functionalities. We prove the utility of such multispecific design techniques in better recovering amino acid sequence diversities similar to those resulting from millions of years of evolution. We then compare the approaches of prediction of low energy ensembles and of amino acid profiles and demonstrate their complementarity in providing more robust predictions for protein design. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Coupled folding and binding with alpha-helix-forming molecular recognition elements

Many protein-protein and protein-nucleic acid interactions involve coupled folding and binding of at least one of the partners. Here, we propose a protein structural element or feature that mediates the binding events of initially disordered regions. This element consists of a short region that undergoes coupled binding and folding within a longer region of disorder. We call these features "molecular recognition elements" (MoREs). Examples of MoREs bound to their partners can be found in the alpha-helix, beta-strand, polyproline II helix, or irregular secondary structure conformations, and in various mixtures of the four structural forms. Here we describe an algorithm that identifies regions having propensities to become alpha-helix-forming molecular recognition elements (alpha-MoREs) based on a discriminant function that indicates such regions while giving a low false-positive error rate on a large collection of structured proteins. Application of this algorithm to databases of genomics and functionally annotated proteins indicates that alpha-MoREs are likely to play important roles protein-protein interactions involved in signaling events.     

Global signatures of protein binding on structured RNAs in Saccharomyces cerevisiae

Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing environmental conditions are poorly understood.Here,we integrated various high-throughput data and introduced a computational framework to describe the global interactions between RNA binding proteins(RBPs)and structured RNAs in yeast at single-nucleotide resolution.We found that on average,in terms of percent total lengths,~15%of mRNA untranslated regions(UTRs),~37%of canonical non-coding RNAs(ncRNAs)and~11%of long ncRNAs(lncRNAs)are bound by proteins.The RBP binding sites,in general,tend to occur at single-stranded loops,with evolutionarily conserved signatures,and often facilitate a specific RNA structure conformation in vivo.We found that four nucleotide modifications of tRNA are significantly associated with RBP binding.We also identified various structural motifs bound by RBPs in the UTRs of mRNAs,associated with localization,degradation and stress responses.Moreover,we identified>200 novel lncRNAs bound by RBPs,and about half of them contain conserved secondary structures.We present the first ensemble pattern of RBP binding sites in the structured non-coding regions of a eukaryotic genome,emphasizing their structural context and cellular functions.