Exploring CRD mobility during RAS/RAF engagement at the membrane

During the activation of mitogen-activated protein kinase (MAPK) signaling, the RAS-binding domain (RBD) and cysteine-rich domain (CRD) of RAF bind to active RAS at the plasma membrane. The orientation of RAS at the membrane may be critical for formation of the RAS-RBDCRD complex and subsequent signaling. To explore how RAS membrane orientation relates to the protein dynamics within the RAS-RBDCRD complex, we perform multiscale coarse-grained and all-atom molecular dynamics (MD) simulations of KRAS4b bound to the RBD and CRD domains of RAF-1, both in solution and anchored to a model plasma membrane. Solution MD simulations describe dynamic KRAS4b-CRD conformations, suggesting that the CRD has sufficient flexibility in this environment to substantially change its binding interface with KRAS4b. In contrast, when the ternary complex is anchored to the membrane, the mobility of the CRD relative to KRAS4b is restricted, resulting in fewer distinct KRAS4b-CRD conformations. These simulations implicate membrane orientations of the ternary complex that are consistent with NMR measurements. While a crystal structure-like conformation is observed in both solution and membrane simulations, a particular intermolecular rearrangement of the ternary complex is observed only when it is anchored to the membrane. This configuration emerges when the CRD hydrophobic loops are inserted into the membrane and helices α3–5 of KRAS4b are solvent exposed. This membrane-specific configuration is stabilized by KRAS4b-CRD contacts that are not observed in the crystal structure. These results suggest modulatory interplay between the CRD and plasma membrane that correlate with RAS/RAF complex structure and dynamics, and potentially influence subsequent steps in the activation of MAPK signaling.     

KRAS Prenylation Is Required for Bivalent Binding with Calmodulin in a Nucleotide-Independent Manner

Deregulation of KRAS4b signaling pathway has been implicated in 30% of all cancers. Membrane localization of KRAS4b is an essential step for the initiation of the downstream signaling cascades that guide various cellular mechanisms. KRAS4b plasma membrane (PM) binding is mediated by the insertion of a prenylated moiety that is attached to the terminal carboxy-methylated cysteine, in addition to electrostatic interactions of its positively charged hypervariable region with anionic lipids. Calmodulin (CaM) has been suggested to selectively bind KRAS4b to act as a negative regulator of the RAS/mitogen-activated protein kinase (MAPK) signaling pathway by displacing KRAS4b from the membrane. However, the mechanism by which CaM can recognize and displace KRAS4b from the membrane is not well understood. In this study, we employed biophysical and structural techniques to characterize this mechanism in detail. We show that KRAS4b prenylation is required for binding to CaM and that the hydrophobic pockets of CaM can accommodate the prenylated region of KRAS4b, which might represent a novel CaM-binding motif. Remarkably, prenylated KRAS4b forms a 2:1 stoichiometric complex with CaM in a nucleotide-independent manner. The interaction between prenylated KRAS4b and CaM is enthalpically driven, and electrostatic interactions also contribute to the formation of the complex. The prenylated KRAS4b terminal KSKTKC-farnesylation and carboxy-methylation is sufficient for binding and defines the minimal CaM-binding motif. This is the same region implicated in membrane and phosphodiesterase6-δ binding. Finally, we provide a structure-based docking model by which CaM binds to prenylated KRAS4b. Our data provide new insights into the KRAS4b-CaM interaction and suggest a possible mechanism whereby CaM can regulate KRAS4b membrane localization.     

A Dynamic Analysis of IRS-PKR Signaling in Liver Cells: A Discrete Modeling Approach

A major challenge in systems biology is to develop a detailed dynamic understanding of the functions and behaviors in a particular cellular system, which depends on the elements and their inter-relationships in a specific network. Computational modeling plays an integral part in the study of network dynamics and uncovering the underlying mechanisms. Here we proposed a systematic approach that incorporates discrete dynamic modeling and experimental data to reconstruct a phenotype-specific network of cell signaling. A dynamic analysis of the insulin signaling system in liver cells provides a proof-of-concept application of the proposed methodology. Our group recently identified that double-stranded RNA-dependent protein kinase (PKR) plays an important role in the insulin signaling network. The dynamic behavior of the insulin signaling network is tuned by a variety of feedback pathways, many of which have the potential to cross talk with PKR. Given the complexity of insulin signaling, it is inefficient to experimentally test all possible interactions in the network to determine which pathways are functioning in our cell system. Our discrete dynamic model provides an in silico model framework that integrates potential interactions and assesses the contributions of the various interactions on the dynamic behavior of the signaling network. Simulations with the model generated testable hypothesis on the response of the network upon perturbation, which were experimentally evaluated to identify the pathways that function in our particular liver cell system. The modeling in combination with the experimental results enhanced our understanding of the insulin signaling dynamics and aided in generating a context-specific signaling network.     

Computer modeling of human angiogenin-dinucleotide substrate interaction

Structures of substrate bound human angiogenin complexes have been obtained for the first time by computer modeling. The dinucleotides CpA and UpA have been docked onto human angiogenin using a systematic grid search procedure in torsion and Eulerian angle space. The docking was guided throughout by the similarity of angiogenin-substrate interactions with interactions of RNase A and its substrate. The models were subjected to 1 nanosecond of molecular dynamics to access their stability. Structures extracted from MD simulations were refined by simulated annealing. Stable hydrogen bonds that bridged protein and ligand residues during the MD simulations were taken as restraints for simulated annealing. Our analysis on the MD structures and annealed models explains the substrate specificity of human angiogenin and is in agreement with experimental results. This study also predicts the B2 binding site residues of angiogenin, for which no experimental information is available so far. In the case of one of the substrates, CpA, we have also identified the presence of a water molecule that invariantly bridges the B2 base with the protein. We have compared our results to the RNase A-substrate complex and highlight the similarities and differences.     

Ringing in the new ear: resolution of cell interactions in otic development

The vertebrate inner ear is a marvel of structural and functional complexity, which is all the more remarkable because it develops from such a simple structure, the otic placode. Analysis of inner ear development has long been a fascination of experimental embryologists, who sought to understand cellular mechanisms of otic placode induction. More recently, however, molecular and genetic approaches have made the inner ear a useful model system for studying a much broader range of basic developmental mechanisms, including cell fate specification and differentiation, axial patterning, epithelial morphogenesis, cytoskeletal dynamics, stem cell biology, neurobiology, physiology, etc. Of course, there has also been tremendous progress in understanding the functions and processes peculiar to the inner ear. The goal of this review is to recount how historical approaches have shaped our understanding of the signaling interactions controlling early otic development; to discuss how new findings have led to fundamental new insights; and to point out new problems that need to be resolved in future research.     

Lipid Clustering Correlates with Membrane Curvature as Revealed by Molecular Simulations of Complex Lipid Bilayers

Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP₂), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP₂, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.     

Cell-sorting at the A/P boundary in the Drosophila wing primordium: a computational model to consolidate observed non-local effects of Hh signaling

Non-intermingling, adjacent populations of cells define compartment boundaries; such boundaries are often essential for the positioning and the maintenance of tissue-organizers during growth. In the developing wing primordium of Drosophila melanogaster, signaling by the secreted protein Hedgehog (Hh) is required for compartment boundary maintenance. However, the precise mechanism of Hh input remains poorly understood. Here, we combine experimental observations of perturbed Hh signaling with computer simulations of cellular behavior, and connect physical properties of cells to their Hh signaling status. We find that experimental disruption of Hh signaling has observable effects on cell sorting surprisingly far from the compartment boundary, which is in contrast to a previous model that confines Hh influence to the compartment boundary itself. We have recapitulated our experimental observations by simulations of Hh diffusion and transduction coupled to mechanical tension along cell-to-cell contact surfaces. Intriguingly, the best results were obtained under the assumption that Hh signaling cannot alter the overall tension force of the cell, but will merely re-distribute it locally inside the cell, relative to the signaling status of neighboring cells. Our results suggest a scenario in which homotypic interactions of a putative Hh target molecule at the cell surface are converted into a mechanical force. Such a scenario could explain why the mechanical output of Hh signaling appears to be confined to the compartment boundary, despite the longer range of the Hh molecule itself. Our study is the first to couple a cellular vertex model describing mechanical properties of cells in a growing tissue, to an explicit model of an entire signaling pathway, including a freely diffusible component. We discuss potential applications and challenges of such an approach.     

Folding pathway of the b1 domain of protein G explored by multiscale modeling

The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, we developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodynamics, and modeling of protein complexes. In this research, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of experimental facts and theoretical findings for this protein. Performing unbiased, ab initio simulations, we demonstrated that the GB1 folding proceeds via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions drives the folding from the very beginning. The emerging comprehensive picture of GB1 folding perfectly matches and extends the previous experimental and theoretical studies.     

Organization of Farnesylated,Carboxymethylated KRAS4B on Membranes

Mutations of the Ras proteins HRAS, KRAS4A, KRAS4B, and NRAS are associated with a high percentage of all human cancers. The proteins are composed of highly homologous N-terminal catalytic or globular domains, plus C-terminal hypervariable regions (HVRs). Post-translational modifications of all RAS HVRs helps target RAS proteins to cellular membrane locations where they perform their signaling functions. For the predominant KRAS4 isoform, KRAS4B, post-translational farnesylation and carboxymethylation, along with a patch of HVR basic residues help foster membrane binding. Recent investigations implicate membrane-bound RAS dimers, oligomers, and nanoclusters as landing pads for effector proteins that relay RAS signals. The details of these RAS signaling platforms have not been elucidated completely, in part due to the difficulties in preparing modified proteins. We have employed properly farnesylated and carboxymethylated KRAS4B in lipid monolayer incubations to examine how the proteins assemble on membranes. Our results reveal novel insights into to how KRAS4B may organize on membranes.     

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks

Predictive understanding of the myriads of signal transduction pathways in a cell is an outstanding challenge of systems biology. Such pathways are primarily mediated by specific but transient protein-protein interactions, which are difficult to study experimentally. In this study, we dissect the specificity of protein-protein interactions governing two-component signaling (TCS) systems ubiquitously used in bacteria. Exploiting the large number of sequenced bacterial genomes and an operon structure which packages many pairs of interacting TCS proteins together, we developed a computational approach to extract a molecular interaction code capturing the preferences of a small but critical number of directly interacting residue pairs. This code is found to reflect physical interaction mechanisms, with the strongest signal coming from charged amino acids. It is used to predict the specificity of TCS interaction: Our results compare favorably to most available experimental results, including the prediction of 7 (out of 8 known) interaction partners of orphan signaling proteins in Caulobacter crescentus. Surveying among the available bacterial genomes, our results suggest 15～25% of the TCS proteins could participate in out-of-operon "crosstalks". Additionally, we predict clusters of crosstalking candidates, expanding from the anecdotally known examples in model organisms. The tools and results presented here can be used to guide experimental studies towards a system-level understanding of two-component signaling.     

转接蛋白NTAL/LAB在淋巴细胞发育和活化中的作用

由膜受体介导的信号转导过程在淋巴细胞发育、分化和活化过程中起着重要的作用,转接蛋白是淋巴细胞信号转导中发挥承上启下作用的分子。它们被相应的蛋白酶磷酸化后,可以通过招募具有特定氨基酸基序的蛋白质,将信号转导通路中不同阶段的分子募集在一起,从而实现信号的整合和分流。NTAL／LAB是新发现的跨膜转接蛋白,体外B细胞受体、FcγRI和FcεRI受体的交联可以引起该分子的迅速磷酸化,提示NTAL／LAB可能参与了这些受体介导的信号转导途径,从而影响淋巴细胞的发育和功能。本文将对NTAL／LAB在主要淋巴细胞发育和分化中的作用作一介绍。     

Molecular Dynamics Ensemble Refinement of Intrinsically Disordered Peptides According to Deconvoluted Spectra from Circular Dichroism

We have developed a computational method of atomistically refining the structural ensemble of intrinsically disordered peptides (IDPs) facilitated by experimental measurements using circular dichroism spectroscopy (CD). A major challenge surrounding this approach stems from the deconvolution of experimental CD spectra into secondary structure features of the IDP ensemble. Currently available algorithms for CD deconvolution were designed to analyze the spectra of proteins with stable secondary structures. Herein, our work aims to minimize any bias from the peptide deconvolution analysis by implementing a non-negative linear least-squares fitting algorithm in conjunction with a CD reference data set that contains soluble and denatured proteins (SDP48). The non-negative linear least-squares method yields the best results for deconvolution of proteins with higher disordered content than currently available methods, according to a validation analysis of a set of protein spectra with Protein Data Bank entries. We subsequently used this analysis to deconvolute our experimental CD data to refine our computational model of the peptide secondary structure ensemble produced by all-atom molecular dynamics simulations with implicit solvent. We applied this approach to determine the ensemble structures of a set of short IDPs, that mimic the calmodulin binding domain of calcium/calmodulin-dependent protein kinase II and its 1-amino-acid and 3-amino-acid mutants. Our study offers a, to our knowledge, novel way to solve the ensemble secondary structures of IDPs in solution, which is important to advance the understanding of their roles in regulating signaling pathways through the formation of complexes with multiple partners.     

A mathematical model of metabolic insulin signaling pathways

We develop a mathematical model that explicitly represents many of the known signaling components mediating translocation of the insulin-responsive glucose transporter GLUT4 to gain insight into the complexities of metabolic insulin signaling pathways. A novel mechanistic model of postreceptor events including phosphorylation of insulin receptor substrate-1, activation of phosphatidylinositol 3-kinase, and subsequent activation of downstream kinases Akt and protein kinase C-zeta is coupled with previously validated subsystem models of insulin receptor binding, receptor recycling, and GLUT4 translocation. A system of differential equations is defined by the structure of the model. Rate constants and model parameters are constrained by published experimental data. Model simulations of insulin dose-response experiments agree with published experimental data and also generate expected qualitative behaviors such as sequential signal amplification and increased sensitivity of downstream components. We examined the consequences of incorporating feedback pathways as well as representing pathological conditions, such as increased levels of protein tyrosine phosphatases, to illustrate the utility of our model for exploring molecular mechanisms. We conclude that mathematical modeling of signal transduction pathways is a useful approach for gaining insight into the complexities of metabolic insulin signaling.     

Molecular dynamics simulations of the transmembrane domain of the oncogenic ErbB2 receptor dimer in a DMPC bilayer

Molecular dynamics simulations of an atomic model of the transmembrane domain of the oncogenic ErbB2 receptor dimer embedded in an explicit dimyristoylphosphatidylcholine (DMPC) bilayer were performed for more than 4 ns. The oncogenic Glu mutation in the membrane spanning segment plays a major role in tyrosine kinase activity and receptor dimerization, and is thought to be partly responsible for the structure of the transmembrane domain of the active receptor. MD results show that the interactions between the two transmembrane helices are characteristic of a left-handed packing as previously demonstrated from in vacuo simulations. Moreover, MD results reveal the absence of persistent hydrogen bonds between the Glu side chains in a membrane environment, which raise the question of the ability for Glu alone to stabilize the TM domain of the ErbB2 receptor. Interestingly the formation of the alpha-pi motif in the two ErbB2 transmembrane helices confirms the concept of intrinsic sequence-induced conformational flexibility. From a careful analysis of our MD results, we suggest that the left-handed helix-helix packing could be the key to correctly orient the intracellular domain of the activated receptor dimer. The prediction of such interactions from computer simulations represents a new step towards the understanding of signaling mechanisms.     

In silico approach to inhibition of signaling pathways of Toll-like receptors 2 and 4 by ST2L

Toll-like receptors (TLRs) activate a potent immunostimulatory response. There is clear evidence that overactivation of TLRs leads to infectious and inflammatory diseases. Recent biochemical studies have shown that the membrane-bound form of ST2 (ST2L), a member of the Toll-like/IL-1 receptor superfamily, negatively regulates MyD88-dependent TLR signaling pathways by sequestrating the adapters MyD88 and Mal (TIRAP). Specifically, ST2L attenuates the recruitment of Mal and MyD88 adapters to their receptors through its intracellular TIR domain. Thus, ST2L is a potent molecule that acts as a key regulator of endotoxin tolerance and modulates innate immunity. So far, the inhibitory mechanism of ST2L at the molecular level remains elusive. To develop a working hypothesis for the interactions between ST2L, TLRs (TLR1, 2, 4, and 6), and adapter molecules (MyD88 and Mal), we constructed three-dimensional models of the TIR domains of TLR4, 6, Mal, and ST2L based on homology modeling. Since the crystal structures of the TIR domains of TLR1, 2 as well as the NMR solution structure of MyD88 are known, we utilized these structures in our analysis. The TIR domains of TLR1, 2, 4, 6, MyD88, Mal and ST2L were subjected to molecular dynamics (MD) simulations in an explicit solvent environment. The refined structures obtained from the MD simulations were subsequently used in molecular docking studies to probe for potential sites of interactions. Through protein-protein docking analysis, models of the essential complexes involved in TLR2 and 4 signaling and ST2L inhibiting processes were developed. Our results suggest that ST2L may exert its inhibitory effect by blocking the molecular interface of Mal and MyD88 adapters mainly through its BB-loop region. Our predicted oligomeric signaling models may provide a basis for the understanding of the assembly process of TIR domain interactions, which has thus far proven to be difficult via in vivo studies.     

Surface plasmon resonance spectroscopy: an emerging tool for the study of peptide-membrane interactions

The interactions between peptides and membranes mediate a wide variety of biological processes, and characterization of the molecular details of these interactions is central to our understanding of cellular events such as protein trafficking, cellular signaling and ion-channel formation. A wide variety of biophysical techniques have been combined with the use of model membrane systems to study peptide-membrane interactions, and have provided important information on the relationship between membrane-active peptide structure and their biological function. However, what has generally not been reported is a detailed analysis of the affinity of peptide for different membrane systems, which has largely been due to the difficulty in obtaining this information. To address this issue, surface plasmon resonance (SPR) spectroscopy has recently been applied to the study of biomembrane-based systems using both planar mono- or bilayers or liposomes. This article provides an overview of these recent applications that demonstrate the potential of SPR to enhance our molecular understanding of membrane-mediated peptide function.