A genome-wide Ras-effector interaction network

From disorder comes function: Regulation of small GTPase function by intrinsically disordered lipidated membrane anchor

The intrinsically disordered, lipid-modified membrane anchor of small GTPases is emerging as a critical modulator of function through its ability to sort lipids in a conformation-dependent manner. We reviewed recent computational and experimental studies that have begun to shed light on the sequence-ensemble-function relationship in this unique class of lipidated intrinsically disordered regions (LIDRs).

Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer

To delineate the mechanisms by which the ERK1 and ERK2 mitogen-activated protein kinases support mutant KRAS-driven cancer growth, we determined the ERK-dependent phosphoproteome in KRAS-mutant pancreatic cancer. We determined that ERK1 and ERK2 share near-identical signaling and transforming outputs and that the KRAS-regulated phosphoproteome is driven nearly completely by ERK. We identified 4666 ERK-dependent phosphosites on 2123 proteins, of which 79 and 66%, respectively, were not previously associated with ERK, substantially expanding the depth and breadth of ERK-dependent phosphorylation events and revealing a considerably more complex function for ERK in cancer. We established that ERK controls a highly dynamic and complex phosphoproteome that converges on cyclin-dependent kinase regulation and RAS homolog guanosine triphosphatase function (RHO GTPase). Our findings establish the most comprehensive molecular portrait and mechanisms by which ERK drives KRAS-dependent pancreatic cancer growth.

Defining bone fide effectors of RAS GTPases

RAS GTPases play essential roles in normal development and are direct drivers of human cancers. Three decades of study have failed to wholly characterize pathways stimulated by activated RAS, driven by engagement with 'effector' proteins that have RAS binding domains (RBDs). Bone fide effectors must bind directly to RAS GTPases in a nucleotide-dependent manner, and this interaction must impart a clear change in effector activity. Despite this, for most proteins currently deemed effectors there is little mechanistic understanding of how binding to the GTPase alters protein function. There has also been limited effort to comprehensively resolve the specificity of effector binding to the full array of RAS superfamily GTPase proteins. This review will summarize what is known about RAS-driven activation for an array of potential effector proteins, focusing on structural and mechanistic effects and highlighting how little is still known regarding this key paradigm of cellular signal transduction.

Structure-based prediction of Ras-effector binding affinities and design of "branchegetic" interface mutations

Ras is a central cellular hub protein controlling multiple cell fates. How Ras interacts with a variety of potential effector proteins is relatively unexplored, with only some key effectors characterized in great detail. Here, we have used homology modeling based on X-ray and AlphaFold2 templates to build structural models for 54 Ras-effector complexes. These models were used to estimate binding affinities using a supervised learning regressor. Furthermore, we systematically introduced Ras "branch-pruning" (or branchegetic) mutations to identify 200 interface mutations that affect the binding energy with at least one of the model structures. The impacts of these branchegetic mutants were integrated into a mathematical model to assess the potential for rewiring interactions at the Ras hub on a systems level. These findings have provided a quantitative understanding of Ras-effector interfaces and their impact on systems properties of a key cellular hub.

Functional diversity in the RAS subfamily of small GTPases

RAS small GTPases regulate important signalling pathways and are notorious drivers of cancer development and progression. While most research to date has focused on understanding and addressing the oncogenic potential of three RAS oncogenes: HRAS, KRAS, and NRAS; the full RAS subfamily is composed of 35 related GTPases with diverse cellular functions. Most remain deeply understudied despite strong evolutionary conservation. Here, we highlight a group of 17 poorly characterized RAS GTPases that are frequently down-regulated in cancer and evidence suggests may function not as oncogenes, but as tumour suppressors. These GTPases remain largely enigmatic in terms of their cellular function, regulation, and interaction with effector proteins. They cluster within two families we designate as 'distal-RAS' (D-RAS; comprised of DIRAS, RASD, and RASL10) and 'CaaX-Less RAS' (CL-RAS; comprised of RGK, NKIRAS, RERG, and RASL11/12 GTPases). Evidence of a tumour suppressive role for many of these GTPases supports the premise that RAS subfamily proteins may collectively regulate cellular proliferation.

Reconstruction and analysis of a large-scale binary Ras-effector signaling network

BACKGROUND

Ras is a key cellular signaling hub that controls numerous cell fates via multiple downstream effector pathways. While pathways downstream of effectors such as Raf, PI3K and RalGDS are extensively described in the literature, how other effectors signal downstream of Ras is often still enigmatic.

METHODS

A comprehensive and unbiased Ras-effector network was reconstructed downstream of 43 effector proteins (converging onto 12 effector classes) using public pathway and protein-protein interaction (PPI) databases. The output is an oriented graph of pairwise interactions defining a 3-layer signaling network downstream of Ras. The 2290 proteins comprising the network were studied for their implication in signaling crosstalk and feedbacks, their subcellular localizations, and their cellular functions.

RESULTS

The final Ras-effector network consists of 2290 proteins that are connected via 19,080 binary PPIs, increasingly distributed across the downstream layers, with 441 PPIs in layer 1, 1660 in layer 2, and 16,979 in layer 3. We identified a high level of crosstalk among proteins of the 12 effector classes. A class-specific Ras sub-network was generated in CellDesigner (.xml file) and a functional enrichment analysis thereof shows that 58% of the processes have previously been associated to a respective effector pathway, with the remaining providing insights into novel and unexplored functions of specific effector pathways.

CONCLUSIONS

Our large-scale and cell general Ras-effector network is a crucial steppingstone towards defining the network boundaries. It constitutes a 'reference interactome' and can be contextualized for specific conditions, e.g. different cell types or biopsy material obtained from cancer patients. Further, it can serve as a basis for elucidating systems properties, such as input-output relationships, crosstalk, and pathway redundancy. Video Abstract.

The Importance of Being PI3K in the RAS Signaling Network

Ras proteins are essential mediators of a multitude of cellular processes, and its deregulation is frequently associated with cancer appearance, progression, and metastasis. Ras-driven cancers are usually aggressive and difficult to treat. Although the recent Food and Drug Administration (FDA) approval of the first Ras G12C inhibitor is an important milestone, only a small percentage of patients will benefit from it. A better understanding of the context in which Ras operates in different tumor types and the outcomes mediated by each effector pathway may help to identify additional strategies and targets to treat Ras-driven tumors. Evidence emerging in recent years suggests that both oncogenic Ras signaling in tumor cells and non-oncogenic Ras signaling in stromal cells play an essential role in cancer. PI3K is one of the main Ras effectors, regulating important cellular processes such as cell viability or resistance to therapy or angiogenesis upon oncogenic Ras activation. In this review, we will summarize recent advances in the understanding of Ras-dependent activation of PI3K both in physiological conditions and cancer, with a focus on how this signaling pathway contributes to the formation of a tumor stroma that promotes tumor cell proliferation, migration, and spread.

A comprehensive analysis of RAS-effector interactions reveals interaction hotspots and new binding partners

RAS effectors specifically interact with GTP-bound RAS proteins to link extracellular signals to downstream signaling pathways. These interactions rely on two types of domains, called RAS-binding (RB) and RAS association (RA) domains, which share common structural characteristics. Although the molecular nature of RAS-effector interactions is well-studied for some proteins, most of the RA/RB-domain-containing proteins remain largely uncharacterized. Here, we searched through human proteome databases, extracting 41 RA domains in 39 proteins and 16 RB domains in 14 proteins, each of which can specifically select at least one of the 25 members in the RAS family. We next comprehensively investigated the sequence–structure–function relationship between different representatives of the RAS family, including HRAS, RRAS, RALA, RAP1B, RAP2A, RHEB1, and RIT1, with all members of RA domain family proteins (RASSFs) and the RB-domain-containing CRAF. The binding affinity for RAS-effector interactions, determined using fluorescence polarization, broadly ranged between high (0.3 μM) and very low (500 μM) affinities, raising interesting questions about the consequence of these variable binding affinities in the regulation of signaling events. Sequence and structural alignments pointed to two interaction hotspots in the RA/RB domains, consisting of an average of 19 RAS-binding residues. Moreover, we found novel interactions between RRAS1, RIT1, and RALA and RASSF7, RASSF9, and RASSF1, respectively, which were systematically explored in sequence–structure–property relationship analysis, and validated by mutational analysis. These data provide a set of distinct functional properties and putative biological roles that should now be investigated in the cellular context.

Analysis of Ras-effector interaction competition in large intestine and colorectal cancer context

Cancer is the second leading cause of death globally, and colorectal cancer (CRC) is among the five most common cancers. The small GTPase KRAS is an oncogene that is mutated in ~30% of all CRCs. Pharmacological treatments of CRC are currently unsatisfactory, but much hope rests on network-centric approaches to drug development and cancer treatment. These approaches, however, require a better understanding of how networks downstream of Ras oncoproteins are connected in a particular tissue context – here colon and CRC. Previously we have shown that competition for binding to a ‘hub’ protein, such as Ras, can induce a rewiring of signal transduction networks. In this study, we analysed 56 established and predicted effectors that contain a structural domain with the potential ability to bind to Ras oncoproteins and their link to pathways coordinating intestinal homoeostasis and barrier function. Using protein concentrations in colon tissue and Ras-effector binding affinities, a computational network model was generated that predicted how effectors differentially and competitively bind to Ras in colon context. The model also predicted both qualitative and quantitative changes in Ras-effector complex formations with increased levels of active Ras – to simulate its upregulation in cancer – simply as an emergent property of competition for the same binding interface on the surface of Ras. We also considered how the number of Ras-effector complexes at the membrane can be increased by additional domains present in some effectors that are recruited to the membrane in response to specific conditions (inputs/stimuli/growth factors) in colon context and CRC.

GTPase activity of Di-Ras proteins is stimulated by Rap1GAP proteins

The Ras family is the largest and most diverse sub-group of Ras-like G proteins. This complexity is further increased by the high number of regulatory Guanine nucleotide Exchange Factors (GEFs) and GTPase Activating Proteins (GAPs) that target specific members of this subfamily. Di-Ras1 and Di-Ras2 are little characterized members of the Ras-like sub-group with still unidentified regulatory and effector proteins. Here we determined the nucleotide binding properties of Di-Ras1/Di-Ras2. The above nanomolar affinity and the inability to react with members of the Cdc25 RasGEF family might suggest that activation does not require a GEF. We identified Rap1GAP1 and Rap1GAP2 as specific GTPase activating proteins of the Di-Ras family. Dual-specificity GAPs of the GAP1(m) family could not activate Di-Ras proteins, despite the presence of the required catalytic residue. Although Di-Ras proteins share GAPs with Rap G proteins, no common effectors could be identified in vitro.

Imaging the activity of Ras superfamily GTPase proteins in small subcellular compartments in neurons

Resolving the spatiotemporal dynamics of intracellular signaling is important for understanding the molecular mechanisms of various cellular processes induced by extracellular signals. Two-photon fluorescence lifetime imaging microscopy (2pFLIM) in combination with a fluorescence resonance energy transfer (FRET)-based signaling sensors allows one to image signaling within small subcellular compartments, such as dendritic spines of neurons, with high sensitivity and spatiotemporal resolution. In this protocol, we describe the procedures and equipment required for imaging intracellular signaling activity, with a particular focus on signaling mediated by the Ras superfamily of small GTPase proteins.

Comparative analysis of interactions of RASSF1-10

Members of the RASSF family (RASSF1-10) have been identified as candidate tumour suppressors that are frequently downregulated by promoter hypermethylation in cancers. These proteins carry a common Ras-association (RA) and SARAH domain (RASSF1-6) that can potentially bind Ras oncoproteins and mediate protein-protein interactions with other SARAH domain proteins. However, there is a notable lack of comparative characterisation of the RASSF family, as well as molecular and structural information that facilitate their tumour suppressive functions. As part of our comparative analysis, we modelled the RA and SARAH domains of the RASSF members based on existing structures and predicted their potential interactions. These in silico predictions were compared to in vitro interaction studies with Ras and MST kinase (a SARAH domain-containing protein). Our data shows a diversity of interaction within the RASSF family RA domain, whereas the SARAH domain-mediated interactions for RASSF1-6 are consistent with the predictions. This suggests that different members, despite shared general architecture, could have distinct functional properties. Additionally, we identify a new interacting partner for MST kinase in the form of RASSF7. Current data supports an interaction model where RASSF serves as an adaptor for the assembly of multiple protein complexes and further functional interactions, involving MST kinases and other SARAH domain proteins, which could be regulated by Ras.

The GTPase-deficient Rnd proteins are stabilized by their effectors

Rnd proteins are Rho family GTP-binding proteins with cellular functions that antagonize RhoA signaling. We recently described a new Rnd3 effector Syx, also named PLEKHG5, that interacts with Rnds via a Raf1-like "Ras-binding domain." Syx is a multidomain RhoGEF that participates in early zebrafish development. Here we demonstrated that Rnd1, Rnd2, and Rnd3 stability is acutely dependent on interaction with their effectors such as Syx or p190 RhoGAP. Although Rnd3 turnover is blocked by treatment of cells with MG132, we provide evidence that such turnover is mediated indirectly by effects on the Rnd3 effectors, rather than on Rnd3 itself, which is not significantly ubiquitinated. The minimal regions of Syx and p190 RhoGAP that bind Rnd3 are not sequence-related but have similar effects. We have identified features that allow for Rnd3 turnover including a conserved Lys-45 close to the switch I region and the C-terminal membrane-binding domain of Rnd3, which cannot be substituted by the equivalent Cdc42 CAAX sequence. By contrast, an effector binding-defective mutant of Rnd3 when overexpressed undergoes turnover at normal rates. Interestingly the activity of the RhoA-regulated kinase ROCK stimulates Rnd3 turnover. This study suggests that Rnd proteins are regulated through feedback mechanisms in cells where the level of effectors and RhoA activity influence the stability of Rnd proteins. This effector feedback behavior is analogous to the ability of ACK1 and PAK1 to prolong the lifetime of the active GTP-bound state of Cdc42 and Rac1.

The Ras protein superfamily: evolutionary tree and role of conserved amino acids

The Ras superfamily is a fascinating example of functional diversification in the context of a preserved structural framework and a prototypic GTP binding site. Thanks to the availability of complete genome sequences of species representing important evolutionary branch points, we have analyzed the composition and organization of this superfamily at a greater level than was previously possible. Phylogenetic analysis of gene families at the organism and sequence level revealed complex relationships between the evolution of this protein superfamily sequence and the acquisition of distinct cellular functions. Together with advances in computational methods and structural studies, the sequence information has helped to identify features important for the recognition of molecular partners and the functional specialization of different members of the Ras superfamily.

Selection of near-native poses in CAPRI rounds 13-19

In CAPRI rounds 13-19, we submitted models that are of acceptable or higher quality for 6 of the total of 13 targets. This success builds on our record in previous CAPRI rounds. The docking problem can be divided into two steps. In the first, translational/rotational and conformational space is searched to generate a pool of docked poses; the success of this search step is measured by whether near-native poses are included in the pool. In the second step, the pool is selected for near-native poses. In our previous assessment of CAPRI results, we suggested that the search problem is largely solved; a remaining problem is to select near-native poses. Our work in these new rounds of CAPRI was guided by this assessment. To solve the selection problem, we used an assortment of criteria on the interfaces of candidate poses. In one extreme, represented by T29, with very little known interface information, our criterion for top models was based on interface prediction. Poses in which the predicted interface residues occurred in interfaces were selected. Our model 1 for T29 was of medium quality. In the other extreme, represented by T40, with reliably known interface information, our selection was solely based on such information. Nine of the ten models submitted for T40 were of high (3 models), medium (4 models), and acceptable (2 models) quality. Our strategy of mixing predicted and known interface information appears to be widely applicable for the selection of near-native poses.

The RhoA GEF Syx is a target of Rnd3 and regulated via a Raf1-like ubiquitin-related domain

Background

Rnd3 (RhoE) protein belongs to the unique branch of Rho family GTPases that has low intrinsic GTPase activity and consequently remains constitutively active [1], [2]. The current consensus is that Rnd1 and Rnd3 function as important antagonists of RhoA signaling primarily by activating the ubiquitous p190 RhoGAP [3], but not by inhibiting the ROCK family kinases.

Methodology/Principal Findings

Rnd3 is abundant in mouse embryonic stem (mES) cells and in an unbiased two-step affinity purification screen we identified a new Rnd3 target, termed synectin-binding RhoA exchange factor (Syx), by mass spectrometry. The Syx interaction with Rnd3 does not occur through the Syx DH domain but utilizes a region similar to the classic Raf1 Ras-binding domain (RBD), and most closely related to those in RGS12 and RGS14. We show that Syx behaves as a genuine effector of Rnd3 (and perhaps Rnd1), with binding characteristics similar to p190-RhoGAP. Morpholino-oligonucleotide knockdown of Syx in zebrafish at the one cell stage resulted in embryos with shortened anterior-posterior body axis: this phenotype was effectively rescued by introducing mouse Syx1b mRNA. A Rnd3-binding defective mutant of Syx1b mutated in the RBD (E164A/R165D) was more potent in rescuing the embryonic defects than wild-type Syx1b, showing that Rnd3 negatively regulates Syx activity in vivo.

Conclusions/Significance

This study uncovers a well defined Rnd3 effector Syx which is widely expressed and directly impacts RhoA activation. Experiments conducted in vivo indicate that Rnd3 negatively regulates Syx, and that as a RhoA-GEF it plays a key role in early embryonic cell shape changes. Thus a connection to signaling via the planar cell polarity pathway is suggested.

Analysis of the human E2 ubiquitin conjugating enzyme protein interaction network

In eukaryotic cells the stability and function of many proteins are regulated by the addition of ubiquitin or ubiquitin-like peptides. This process is dependent upon the sequential action of an E1-activating enzyme, an E2-conjugating enzyme, and an E3 ligase. Different combinations of these proteins confer substrate specificity and the form of protein modification. However, combinatorial preferences within ubiquitination networks remain unclear. In this study, yeast two-hybrid (Y2H) screens were combined with true homology modeling methods to generate a high-density map of human E2/E3-RING interactions. These data include 535 experimentally defined novel E2/E3-RING interactions and >1300 E2/E3-RING pairs with more favorable predicted free-energy values than the canonical UBE2L3-CBL complex. The significance of Y2H predictions was assessed by both mutagenesis and functional assays. Significantly, 74/80 (>92%) of Y2H predicted complexes were disrupted by point mutations that inhibit verified E2/E3-RING interactions, and a approximately 93% correlation was observed between Y2H data and the functional activity of E2/E3-RING complexes in vitro. Analysis of the high-density human E2/E3-RING network reveals complex combinatorial interactions and a strong potential for functional redundancy, especially within E2 families that have undergone evolutionary expansion. Finally, a one-step extended human E2/E3-RING network, containing 2644 proteins and 5087 edges, was assembled to provide a resource for future functional investigations.

Fast predictions of thermodynamics and kinetics of protein-protein recognition from structures: from molecular design to systems biology

The increasing call for an overall picture of the interactions between the components of a biological system that give rise to the observed function is often summarized by the expression systems biology. Both the interpretative and predictive capabilities of holistic models of biochemical systems, however, depend to a large extent on the level of physico-chemical knowledge of the individual molecular interactions making up the network. This review is focused on the structure-based quantitative characterization of protein-protein interactions, ubiquitous in any biochemical pathway. Recently developed, fast and effective computational methods are reviewed, which allow the assessment of kinetic and thermodynamic features of the association-dissociation processes of protein complexes, both in water soluble and membrane environments. The performance and the accuracy of fast and semi-empirical structure-based methods have reached comparable levels with respect to the classical and more elegant molecular simulations. Nevertheless, the broad accessibility and lower computational cost provide the former methods with the advantageous possibility to perform systems-level analyses including extensive in silico mutagenesis screenings and large-scale structural predictions of multiprotein complexes.

Association rate constants of ras-effector interactions are evolutionarily conserved

Evolutionary conservation of protein interaction properties has been shown to be a valuable indication for functional importance. Here we use homology interface modeling of 10 Ras-effector complexes by selecting ortholog proteins from 12 organisms representing the major eukaryotic branches, except plants. We find that with increasing divergence time the sequence similarity decreases with respect to the human protein, but the affinities and association rate constants are conserved as predicted by the protein design algorithm, FoldX. In parallel we have done computer simulations on a minimal network based on Ras-effector interactions, and our results indicate that in the absence of negative feedback, changes in kinetics that result in similar binding constants have strong consequences on network behavior. This, together with the previous results, suggests an important biological role, not only for equilibrium binding constants but also for kinetics in signaling processes involving Ras-effector interactions. Our findings are important to take into consideration in system biology approaches and simulations of biological networks.

Cellular signal transductions processes are based on protein interactions. Proteins can either associate transiently with each other or form stable complexes, and the strength of the interaction is described by the affinity (the affinity is the ratio between the rate of dissociation and association). Protein complexes with similar affinities can bind and dissociate with different rates, and these rates describe the kinetic properties of protein binding. These kinetic rates are important for signaling; however, to what extent individual changes in such rate constants are biologically important or whether the affinity is more crucial might be different in different signaling processes. In this study we analyze whether association rates are conserved during evolution, because evolutionary conservation of protein biochemical properties is usually a valuable indication of its importance. We analyzed the binding of Ras proteins to effector domains, which are central proteins in many signal transduction pathways, in different organisms. On the basis of homology modeling and energy calculations we find that association rates are conserved, although the sequence similarity decreases compared to the human protein. Our finding should encourage further analysis of the importance of kinetics for cellular signal transduction.

Contextual specificity in peptide-mediated protein interactions

Most biological processes are regulated through complex networks of transient protein interactions where a globular domain in one protein recognizes a linear peptide from another, creating a relatively small contact interface. Although sufficient to ensure binding, these linear motifs alone are usually too short to achieve the high specificity observed, and additional contacts are often encoded in the residues surrounding the motif (i.e. the context). Here, we systematically identified all instances of peptide-mediated protein interactions of known three-dimensional structure and used them to investigate the individual contribution of motif and context to the global binding energy. We found that, on average, the context is responsible for roughly 20% of the binding and plays a crucial role in determining interaction specificity, by either improving the affinity with the native partner or impeding non-native interactions. We also studied and quantified the topological and energetic variability of interaction interfaces, finding a much higher heterogeneity in the context residues than in the consensus binding motifs. Our analysis partially reveals the molecular mechanisms responsible for the dynamic nature of peptide-mediated interactions, and suggests a global evolutionary mechanism to maximise the binding specificity. Finally, we investigated the viability of non-native interactions and highlight cases of potential cross-reaction that might compensate for individual protein failure and establish backup circuits to increase the robustness of cell networks.

Genome-wide prediction of SH2 domain targets using structural information and the FoldX algorithm

Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new hypothesis for the role of SH2 domains in signaling.

Understanding the functional role of every protein in the cell is a long-standing goal of cellular biology. An important step in this direction is to discover how and when proteins interact inside the cell to accomplish their tasks. Many of the cellular functions depend on reversible protein modifications like phosphorylation. To sense these modifications, cells have protein domains capable of binding phosphorylated proteins such as the SH2 domain. In this work, we show that it is possible to use the three-dimensional structure of protein domains to predict its binding preferences. Using a computational tool called FoldX, we have predicted the binding specificity of several human SH2 domains. These predictions, based on the computational analysis of the 3-D structure, were shown to be of similar accuracy as those obtained from experimental binding assays. We show here that it is also possible to understand how a mutation changes the binding preference of protein binding domains, opening the way for better understanding of some disease causing mutations. The combination of this novel computational approach with other sources of information allowed us to provide a set of high-confidence novel interactions for the proteins here studied.

Shaping dots and lines: adding modularity into protein interaction networks using structural information

Determining protein interaction networks and generating models to simulate network changes in time and space are crucial for understanding a biological system and for predicting the effect of mutants found in diseases. In this review we discuss the great potential of using structural information together with computational tools towards reaching this goal: the prediction of new protein interactions, the estimation of affinities and kinetic rate constants between protein complexes, and finally the determination of which interactions are compatible with each other and which interactions are exclusive. The latter one will be important to reorganize large scale networks into functional modular networks.

Choose your own path: specificity in Ras GTPase signaling

The Ras superfamily of small G proteins contributes importantly to numerous cellular and physiological processes (M. F. Olsen and R. Marais, Semin. Immunol., 2000, 12, 63). This family comprises a large class of proteins (more than 150) which all share a common enzymatic function: hydrolysis of the gamma-phosphate of guanosine triphosphate (GTP) to create the products guanosine diphosphate (GDP) and inorganic phosphate (Y. Takai, T. Sasaki and T. Matozaki, Physiol. Rev., 2001, 81, 153). For this reason Ras family proteins, which include the Ras, Rho, Arf/Sara, Ran and Rab subfamilies, are classified as GTPases (G. W. Reuther and C. J. Der, Curr. Opin. Cell Biol., 2000, 12, 157). Guanine nucleotide coupling is a key regulator of enzymatic function; thus, Ras family GTPases participate in signal transduction. Ras signaling depends on binding to effectors. Many of the known effectors can bind to multiple Ras isotypes, often leading to common cellular outcomes, but each Ras isotype also engages specific effector pathways to mediate unique functions. Further, each Ras isotype can propagate multiple signaling pathways, indicating the presence of cellular determinants which allow for promiscuity in Ras-effector interactions while also maintaining specificity. Small distinctions in sequence, structure, and/or cellular regulation contribute to these differences in Ras-effector binding and subsequent cellular effects. A major focus of investigation in the Ras signaling field is identifying the determinants of these individualized functions. This review will attempt to summarize the current state of understanding of this question (with a particular focus on the Ras subfamily) and the approaches being taken to address it, and will discuss prospective areas for future investigation.

Prediction of Ras-effector interactions using position energy matrices

MOTIVATION

One of the more challenging problems in biology is to determine the cellular protein interaction network. Progress has been made to predict protein-protein interactions based on structural information, assuming that structural similar proteins interact in a similar way. In a previous publication, we have determined a genome-wide Ras-effector interaction network based on homology models, with a high accuracy of predicting binding and non-binding domains. However, for a prediction on a genome-wide scale, homology modelling is a time-consuming process. Therefore, we here successfully developed a faster method using position energy matrices, where based on different Ras-effector X-ray template structures, all amino acids in the effector binding domain are sequentially mutated to all other amino acid residues and the effect on binding energy is calculated. Those pre-calculated matrices can then be used to score for binding any Ras or effector sequences.

RESULTS

Based on position energy matrices, the sequences of putative Ras-binding domains can be scanned quickly to calculate an energy sum value. By calibrating energy sum values using quantitative experimental binding data, thresholds can be defined and thus non-binding domains can be excluded quickly. Sequences which have energy sum values above this threshold are considered to be potential binding domains, and could be further analysed using homology modelling. This prediction method could be applied to other protein families sharing conserved interaction types, in order to determine in a fast way large scale cellular protein interaction networks. Thus, it could have an important impact on future in silico structural genomics approaches, in particular with regard to increasing structural proteomics efforts, aiming to determine all possible domain folds and interaction types.

AVAILABILITY

All matrices are deposited in the ADAN database (http://adan-embl.ibmc.umh.es/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.