Quantifying intramolecular binding in multivalent interactions: a structure-based synergistic study on Grb2-Sos1 complex

Physics of the Nuclear Pore Complex: Theory, Modeling and Experiment

The hallmark of eukaryotic cells is the nucleus that contains the genome, enclosed by a physical barrier known as the nuclear envelope (NE). On the one hand, this compartmentalization endows the eukaryotic cells with high regulatory complexity and flexibility. On the other hand, it poses a tremendous logistic and energetic problem of transporting millions of molecules per second across the nuclear envelope, to facilitate their biological function in all compartments of the cell. Therefore, eukaryotes have evolved a molecular "nanomachine" known as the Nuclear Pore Complex (NPC). Embedded in the nuclear envelope, NPCs control and regulate all the bi-directional transport between the cell nucleus and the cytoplasm. NPCs combine high molecular specificity of transport with high throughput and speed, and are highly robust with respect to molecular noise and structural perturbations. Remarkably, the functional mechanisms of NPC transport are highly conserved among eukaryotes, from yeast to humans, despite significant differences in the molecular components among various species. The NPC is the largest macromolecular complex in the cell. Yet, despite its significant complexity, it has become clear that its principles of operation can be largely understood based on fundamental physical concepts, as have emerged from a combination of experimental methods of molecular cell biology, biophysics, nanoscience and theoretical and computational modeling. Indeed, many aspects of NPC function can be recapitulated in artificial mimics with a drastically reduced complexity compared to biological pores. We review the current physical understanding of the NPC architecture and function, with the focus on the critical analysis of experimental studies in cells and artificial NPC mimics through the lens of theoretical and computational models. We also discuss the connections between the emerging concepts of NPC operation and other areas of biophysics and bionanotechnology.

The intramolecular allostery of GRB2 governing its interaction with SOS1 is modulated by phosphotyrosine ligands

Growth factor receptor-bound protein 2 (GRB2) is a trivalent adaptor protein and a key element in signal transduction. It interacts via its flanking nSH3 and cSH3 domains with the proline-rich domain (PRD) of the RAS activator SOS1 and via its central SH2 domain with phosphorylated tyrosine residues of receptor tyrosine kinases (RTKs; e.g. HER2). The elucidation of structural organization and mechanistic insights into GRB2 interactions, however, remain challenging due to their inherent flexibility. This study represents an important advance in our mechanistic understanding of how GRB2 links RTKs to SOS1. Accordingly, it can be proposed that (1) HER2 pYP-bound SH2 potentiates GRB2 SH3 domain interactions with SOS1 (an allosteric mechanism); (2) the SH2 domain blocks cSH3, enabling nSH3 to bind SOS1 first before cSH3 follows (an avidity-based mechanism); and (3) the allosteric behavior of cSH3 to other domains appears to be unidirectional, although there is an allosteric effect between the SH2 and SH3 domains.

A Non-immunogenic Bivalent d-Protein Potently Inhibits Retinal Vascularization and Tumor Growth

We report a general approach to engineering multivalent d-proteins with antibody-like activities in vivo. Mirror-image phage display and structure-guided design were utilized to create a d-protein that uses receptor mimicry to antagonize vascular endothelial growth factor A (VEGF-A). Selections against the d-protein form of VEGF-A using phage-displayed libraries of two different domain scaffolds yielded two proteins that bound distinct receptor interaction sites on VEGF-A. X-ray crystal structures of the d-protein/VEGF-A complexes were used to guide affinity maturation and to construct a heterodimeric d-protein VEGF-A antagonist with picomolar activity. The d-protein VEGF-A antagonist prevented vascular leakage in a rabbit eye model of wet age-related macular degeneration and slowed tumor growth in the MC38 syngeneic mouse tumor model with efficacies comparable to those of approved antibody drugs, and in contrast with antibodies, the d-protein was non-immunogenic during treatment and following subcutaneous immunizations.

Combinatorial diversity of Syk recruitment driven by its multivalent engagement with FcεRIγ

Syk/Zap70 family kinases are essential for signaling via multichain immune-recognition receptors such as tetrameric (αβγ2) FcεRI. Syk activation is generally attributed to cis binding of its tandem SH2 domains to dual phosphotyrosines within FcεRIγ-ITAMs (immunoreceptor tyrosine-based activation motifs). However, the mechanistic details of Syk docking on γ homodimers are unresolved. Here, we estimate that multivalent interactions for WT Syk improve cis-oriented binding by three orders of magnitude. We applied molecular dynamics (MD), hybrid MD/worm-like chain polymer modeling, and live cell imaging to evaluate relative binding and signaling output for all possible cis and trans Syk-FcεRIγ configurations. Syk binding is likely modulated during signaling by autophosphorylation on Y130 in interdomain A, since a Y130E phosphomimetic form of Syk is predicted to lead to reduced helicity of interdomain A and alter Syk's bias for cis binding. Experiments in reconstituted γ-KO cells, whose γ subunits are linked by disulfide bonds, as well as in cells expressing monomeric ITAM or hemITAM γ-chimeras, support model predictions that short distances between γ ITAM pairs are required for trans docking. We propose that the full range of docking configurations improves signaling efficiency by expanding the combinatorial possibilities for Syk recruitment, particularly under conditions of incomplete ITAM phosphorylation.

Human Cytomegalovirus Nuclear Capsids Associate with the Core Nuclear Egress Complex and the Viral Protein Kinase pUL97

The nuclear phase of herpesvirus replication is regulated through the formation of regulatory multi-component protein complexes. Viral genomic replication is followed by nuclear capsid assembly, DNA encapsidation and nuclear egress. The latter has been studied intensely pointing to the formation of a viral core nuclear egress complex (NEC) that recruits a multimeric assembly of viral and cellular factors for the reorganization of the nuclear envelope. To date, the mechanism of the association of human cytomegalovirus (HCMV) capsids with the NEC, which in turn initiates the specific steps of nuclear capsid budding, remains undefined. Here, we provide electron microscopy-based data demonstrating the association of both nuclear capsids and NEC proteins at nuclear lamina budding sites. Specifically, immunogold labelling of the core NEC constituent pUL53 and NEC-associated viral kinase pUL97 suggested an intranuclear NEC-capsid interaction. Staining patterns with phospho-specific lamin A/C antibodies are compatible with earlier postulates of targeted capsid egress at lamina-depleted areas. Important data were provided by co-immunoprecipitation and in vitro kinase analyses using lysates from HCMV-infected cells, nuclear fractions, or infectious virions. Data strongly suggest that nuclear capsids interact with pUL53 and pUL97. Combined, the findings support a refined concept of HCMV nuclear trafficking and NEC-capsid interaction.

Simple biophysics underpins collective conformations of the intrinsically disordered proteins of the Nuclear Pore Complex

Nuclear Pore Complexes (NPCs) are key cellular transporter that control nucleocytoplasmic transport in eukaryotic cells, but its transport mechanism is still not understood. The centerpiece of NPC transport is the assembly of intrinsically disordered polypeptides, known as FG nucleoporins, lining its passageway. Their conformations and collective dynamics during transport are difficult to assess in vivo. In vitro investigations provide partially conflicting results, lending support to different models of transport, which invoke various conformational transitions of the FG nucleoporins induced by the cargo-carrying transport proteins. We show that the spatial organization of FG nucleoporin assemblies with the transport proteins can be understood within a first principles biophysical model with a minimal number of key physical variables, such as the average protein interaction strengths and spatial densities. These results address some of the outstanding controversies and suggest how molecularly divergent NPCs in different species can perform essentially the same function.

DOI:http://dx.doi.org/10.7554/eLife.10785.001

Animal, plant and fungal cells contain a structure called the nucleus, inside which the genetic material of the cell is stored. For the cell to work properly, certain proteins and other molecules need to be able to enter and exit the nucleus. This transport is carried out by pore-like molecular “devices” known as Nuclear Pore Complexes, whose architecture and mode of operation are unique among cellular transporters.

Nuclear Pore Complexes are charged with a daunting task of deciding which of the hundreds of molecules it conducts per second should go through and which should not. Small molecules can pass freely through Nuclear Pore Complexes. However, larger molecules can only pass through the pore efficiently if they are bound to specialized transport proteins that interact with the proteins – called FG nucleoporins – that line the pore. A unique feature of the FG nucleoporins is that, unlike typical proteins, they do not have a defined three-dimensional structure. Instead, they form a soft and pliable lining inside the Nuclear Pore Complex passageway.

Exactly how interacting with transport proteins affects the structure and spatial arrangements of the FG nucleoporins in a way that allows them to control transport is not well understood. This is in part because existing experimental techniques are unable to study the structures of the FG nucleoporins in enough detail to track how they change during transport. The complexity and the diversity of the FG nucleoporins also make them difficult to model in detail.

Vovk, Gu et al. have developed a theoretical model that is based on just three basic physical properties of the FG nucleoporins – their flexibility, their ability to interact with each other, and their binding with the transport proteins. Future work can refine the model by incorporating further molecular details about the interactions between FG nucleoporins and transport proteins.

The predictions made by this simple model agree well with experimental results in a wide range of situations – from single molecules to complex spatial assemblies. They also explain why some of the experimental results appear to contradict each other and suggest how several outstanding controversies in the field can be reconciled. Because the model invokes only fundamental physical principles of FG nucleoporin assemblies, it shows that some of their general properties do not depend on the exact conditions. In particular, this might shed light on why Nuclear Pore Complexes in different organisms perform essentially the same function, although the details of their molecular structure may differ. This also suggests how the FG nucleoporins can be manipulated to build artificial devices based on the same principles.

DOI:http://dx.doi.org/10.7554/eLife.10785.002

Multiple Weak Linear Motifs Enhance Recruitment and Processivity in SPOP-Mediated Substrate Ubiquitination

Primary sequence motifs, with millimolar affinities for binding partners, are abundant in disordered protein regions. In multivalent interactions, such weak linear motifs can cooperate to recruit binding partners via avidity effects. If linear motifs recruit modifying enzymes, optimal placement of weak motifs may regulate access to modification sites. Weak motifs may thus exert physiological relevance stronger than that suggested by their affinities, but molecular mechanisms of their function are still poorly understood. Herein, we use the N-terminal disordered region of the Hedgehog transcriptional regulator Gli3 (Gli3(1-90)) to determine the role of weak motifs encoded in its primary sequence for the recruitment of its ubiquitin ligase CRL3(SPOP) and the subsequent effect on ubiquitination efficiency. The substrate adaptor SPOP binds linear motifs through its MATH (meprin and TRAF homology) domain and forms higher-order oligomers through its oligomerization domains, rendering SPOP multivalent for its substrates. Gli3 has multiple weak SPOP binding motifs. We map three such motifs in Gli3(1-90), the weakest of which has a millimolar dissociation constant. Multivalency of ligase and substrate for each other facilitates enhanced ligase recruitment and stimulates Gli3(1-90) ubiquitination in in vitro ubiquitination assays. We speculate that the weak motifs enable processivity through avidity effects and by providing steric access to lysine residues that are otherwise not prioritized for polyubiquitination. Weak motifs may generally be employed in multivalent systems to act as gatekeepers regulating post-translational modification.

Regions outside of conserved PxxPxR motifs drive the high affinity interaction of GRB2 with SH3 domain ligands

SH3 domains are evolutionarily conserved protein interaction domains that control nearly all cellular processes in eukaryotes. The current model is that most SH3 domains bind discreet PxxPxR motifs with weak affinity and relatively low selectivity. However, the interactions of full-length SH3 domain-containing proteins with ligands are highly specific and have much stronger affinity. This suggests that regions outside of PxxPxR motifs drive these interactions. In this study, we observed that PxxPxR motifs were required for the binding of the adaptor protein GRB2 to short peptides from its ligand SOS1. Surprisingly, PxxPxR motifs from the proline rich region of SOS1 or CBL were neither necessary nor sufficient for the in vitro or in vivo interaction with full-length GRB2. Together, our findings show that regions outside of the consensus PxxPxR sites drive the high affinity association of GRB2 with SH3 domain ligands, suggesting that the binding mechanism for this and other SH3 domain interactions may be more complex than originally thought.

Modeling biomolecular site dynamics in immunoreceptor signaling systems

The immune system plays a central role in human health. The activities of immune cells, whether defending an organism from disease or triggering a pathological condition such as autoimmunity, are driven by the molecular machinery of cellular signaling systems. Decades of experimentation have elucidated many of the biomolecules and interactions involved in immune signaling and regulation, and recently developed technologies have led to new types of quantitative, systems-level data. To integrate such information and develop nontrivial insights into the immune system, computational modeling is needed, and it is essential for modeling methods to keep pace with experimental advances. In this chapter, we focus on the dynamic, site-specific, and context-dependent nature of interactions in immunoreceptor signaling (i.e., the biomolecular site dynamics of immunoreceptor signaling), the challenges associated with capturing these details in computational models, and how these challenges have been met through use of rule-based modeling approaches.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation).

Deducing conformational variability of intrinsically disordered proteins from infrared spectroscopy with Bayesian statistics

As it remains practically impossible to generate ergodic ensembles for large intrinsically disordered proteins (IDP) with molecular dynamics (MD) simulations, it becomes critical to compare spectroscopic characteristics of the theoretically generated ensembles to corresponding measurements. We develop a Bayesian framework to infer the ensemble properties of an IDP using a combination of conformations generated by MD simulations and its measured infrared spectrum. We performed 100 different MD simulations totaling more than 10 µs to characterize the conformational ensemble of αsynuclein, a prototypical IDP, in water. These conformations are clustered based on solvent accessibility and helical content. We compute the amide-I band for these clusters and predict the thermodynamic weights of each cluster given the measured amide-I band. Bayesian analysis produces a reproducible and non-redundant set of thermodynamic weights for each cluster, which can then be used to calculate the ensemble properties. In a rigorous validation, these weights reproduce measured chemical shifts.

Identification of minimally interacting modules in an intrinsically disordered protein

The conformational characterization of intrinsically disordered proteins (IDPs) is complicated by their conformational heterogeneity and flexibility. If an IDP could somehow be divided into smaller fragments and reconstructed later, theoretical and spectroscopic studies could probe its conformational variability in detail. Here, we used replica molecular-dynamics simulations and network theory to explore whether such a divide-and-conquer strategy is feasible for α-synuclein, a prototypical IDP. We characterized the conformational variability of α-synuclein by conducting >100 unbiased all-atom molecular-dynamics simulations, for a total of >10 μs of trajectories. In these simulations, α-synuclein formed a heterogeneous ensemble of collapsed coil states in an aqueous environment. These states were stabilized by heterogeneous contacts between sequentially distant regions. We find that α-synuclein contains residual secondary structures in the collapsed states, and the heterogeneity in the collapsed state makes it feasible to split α-synuclein into sequentially contiguous minimally interacting fragments. This study reveals previously unknown characteristics of α-synuclein and provides a new (to our knowledge) approach for studying other IDPs.

The Combinatorial Nature of Osmosensing in Fishes

Organisms exposed to altered salinity must be able to perceive osmolality change because metabolism has evolved to function optimally at specific intracellular ionic strength and composition. Such osmosensing comprises a complex physiological process involving many elements at organismal and cellular levels of organization. Input from numerous osmosensors is integrated to encode magnitude, direction, and ionic basis of osmolality change. This combinatorial nature of osmosensing is discussed with emphasis on fishes.