Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The RAS-Effector Interaction as a Drug Target.

ABSTRACT: About a third of all human cancers harbor mutations in one of the K-, N-, or HRAS genes that encode an abnormal RAS protein locked in a constitutively activated state to drive malignant transformation and tumor growth. Despite more than three decades of intensive research aimed at the discovery of RAS-directed therapeutics, there are no FDA-approved drugs that are broadly effective against RAS-driven cancers. Although RAS proteins are often said to be "undruggable," there is mounting evidence suggesting it may be feasible to develop direct inhibitors of RAS proteins. Here, we review this evidence with a focus on compounds capable of inhibiting the interaction of RAS proteins with their effectors that transduce the signals of RAS and that drive and sustain malignant transformation and tumor growth. These reports of direct-acting RAS inhibitors provide valuable insight for further discovery and development of clinical candidates for RAS-driven cancers involving mutations in RAS genes or otherwise activated RAS proteins. Cancer Res; 77(2); 221-6. ©2017 AACR.

SUBMITTER: Keeton AB

PROVIDER: S-EPMC5243175 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

The RAS-Effector Interaction as a Drug Target.

Keeton Adam B AB Salter E Alan EA Piazza Gary A GA

Cancer research 20170106 2

About a third of all human cancers harbor mutations in one of the K-, N-, or HRAS genes that encode an abnormal RAS protein locked in a constitutively activated state to drive malignant transformation and tumor growth. Despite more than three decades of intensive research aimed at the discovery of RAS-directed therapeutics, there are no FDA-approved drugs that are broadly effective against RAS-driven cancers. Although RAS proteins are often said to be "undruggable," there is mounting evidence su ...[more]

PMID: 28062402

Similar Datasets

Inhibition of Ras-Effector Interaction by Cyclic Peptides.

Project description:A combinatorial library of 6 × 106 cyclic peptides was synthesized in the one bead-two compound format, with each bead displaying a unique cyclic peptide on its surface and a linear peptide encoding tag in its interior. Screening of the library against K-Ras identified compounds that bound K-Ras with submicromolar affinity and disrupted its interaction with effector proteins.

| S-EPMC3621770 | biostudies-literature

Ras GTPases' interaction with effector domains: Breaking the families' barrier.

Project description:THE RAS SUPERFAMILY OF PROTEINS CONSISTS OF FIVE BRANCHES:Ras, Rho, Arf, Rab and Ran subfamilies. These proteins are involved in a plethora of biological functions spanning cytoskeletal organization, cell proliferation, transcription and intracellular trafficking. Ras-Binding Domains (RBDs) have classically been identified as autonomous ubiquitin-like folded regions that bind certain activated Ras GTPases of the Ras subfamily. In general, RBDs in many proteins have been tagged with membrane-targeting functions as in the case of the well-characterized c-Raf-RBD/Ras interaction. However, it is becoming apparent that the definition and functions of RBDs need to be revamped in order to reflect the new discoveries associated with this domain. Here, we discuss in more detail the recent advances associated with these RBDs. We highlight research identifying RBDs in formins, ELMOs and the RhoGEF, Syx and discuss the emerging role for RBDs in controlling autoinhibition relief and the newly recognized versatility of RBDs to interact with Rho and Arf family GTPases. In addition, these recent findings raise the exciting hypothesis that functional RBDs remain hidden in the proteome and are ready to be uncovered.

| S-EPMC3737747 | biostudies-literature

Novel type of Ras effector interaction established between tumour suppressor NORE1A and Ras switch II.

Project description:A class of putative Ras effectors called Ras association domain family (RASSF) represents non-enzymatic adaptors that were shown to be important in tumour suppression. RASSF5, a member of this family, exists in two splice variants known as NORE1A and RAPL. Both of them are involved in distinct cellular pathways triggered by Ras and Rap, respectively. Here we describe the crystal structure of Ras in complex with the Ras binding domain (RBD) of NORE1A/RAPL. All Ras effectors share a common topology in their RBD creating an interface with the switch I region of Ras, whereas NORE1A/RAPL RBD reveals additional structural elements forming a unique Ras switch II binding site. Consequently, the contact area of NORE1A is extended as compared with other Ras effectors. We demonstrate that the enlarged interface provides a rationale for an exceptionally long lifetime of the complex. This is a specific attribute characterizing the effector function of NORE1A/RAPL as adaptors, in contrast to classical enzymatic effectors such as Raf, RalGDS or PI3K, which are known to form highly dynamic short-lived complexes with Ras.

| S-EPMC2486280 | biostudies-literature

In silico discovery of small-molecule Ras inhibitors that display antitumor activity by blocking the Ras-effector interaction.

Project description:Mutational activation of the Ras oncogene products (H-Ras, K-Ras, and N-Ras) is frequently observed in human cancers, making them promising anticancer drug targets. Nonetheless, no effective strategy has been available for the development of Ras inhibitors, partly owing to the absence of well-defined surface pockets suitable for drug binding. Only recently, such pockets have been found in the crystal structures of a unique conformation of Ras?GTP. Here we report the successful development of small-molecule Ras inhibitors by an in silico screen targeting a pocket found in the crystal structure of M-Ras?GTP carrying an H-Ras-type substitution P40D. The selected compound Kobe0065 and its analog Kobe2602 exhibit inhibitory activity toward H-Ras?GTP-c-Raf-1 binding both in vivo and in vitro. They effectively inhibit both anchorage-dependent and -independent growth and induce apoptosis of H-ras(G12V)-transformed NIH 3T3 cells, which is accompanied by down-regulation of downstream molecules such as MEK/ERK, Akt, and RalA as well as an upstream molecule, Son of sevenless. Moreover, they exhibit antitumor activity on a xenograft of human colon carcinoma SW480 cells carrying the K-ras(G12V) gene by oral administration. The NMR structure of a complex of the compound with H-Ras?GTP(T35S), exclusively adopting the unique conformation, confirms its insertion into one of the surface pockets and provides a molecular basis for binding inhibition toward multiple Ras?GTP-interacting molecules. This study proves the effectiveness of our strategy for structure-based drug design to target Ras?GTP, and the resulting Kobe0065-family compounds may serve as a scaffold for the development of Ras inhibitors with higher potency and specificity.

| S-EPMC3657810 | biostudies-literature

Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities.

Project description:Activating mutations in RAS GTPases drive many cancers, but limited understanding of less-studied RAS interactors, and of the specific roles of different RAS interactor paralogs, continues to limit target discovery. We developed a multistage discovery and screening process to systematically identify genes conferring RAS-related susceptibilities in lung adenocarcinoma. Using affinity purification mass spectrometry, we generated a protein-protein interaction map of RAS interactors and pathway components containing hundreds of interactions. From this network, we constructed a CRISPR dual knockout library targeting 119 RAS-related genes that we screened for KRAS-dependent genetic interactions (GI). This approach identified new RAS effectors, including the adhesion controller RADIL and the endocytosis regulator RIN1, and >250 synthetic lethal GIs, including a potent KRAS-dependent interaction between RAP1GDS1 and RHOA. Many GIs link specific paralogs within and between gene families. These findings illustrate the power of multiomic approaches to uncover synthetic lethal combinations specific for hitherto untreatable cancer genotypes. SIGNIFICANCE: We establish a deep network of protein-protein and genetic interactions in the RAS pathway. Many interactions validated here demonstrate important specificities and redundancies among paralogous RAS regulators and effectors. By comparing synthetic lethal interactions across KRAS-dependent and KRAS-independent cell lines, we identify several new combination therapy targets for RAS-driven cancers.This article is highlighted in the In This Issue feature, p. 1775.

| S-EPMC7710624 | biostudies-literature

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

Project description: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.

| S-EPMC7939564 | biostudies-literature

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

Project description: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.

| S-EPMC8163975 | biostudies-literature

MolTrans: Molecular Interaction Transformer for drug-target interaction prediction.

Project description:MotivationDrug-target interaction (DTI) prediction is a foundational task for in-silico drug discovery, which is costly and time-consuming due to the need of experimental search over large drug compound space. Recent years have witnessed promising progress for deep learning in DTI predictions. However, the following challenges are still open: (i) existing molecular representation learning approaches ignore the sub-structural nature of DTI, thus produce results that are less accurate and difficult to explain and (ii) existing methods focus on limited labeled data while ignoring the value of massive unlabeled molecular data.ResultsWe propose a Molecular Interaction Transformer (MolTrans) to address these limitations via: (i) knowledge inspired sub-structural pattern mining algorithm and interaction modeling module for more accurate and interpretable DTI prediction and (ii) an augmented transformer encoder to better extract and capture the semantic relations among sub-structures extracted from massive unlabeled biomedical data. We evaluate MolTrans on real-world data and show it improved DTI prediction performance compared to state-of-the-art baselines.Availability and implementationThe model scripts are available at https://github.com/kexinhuang12345/moltrans.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC8098026 | biostudies-literature

Toward more realistic drug-target interaction predictions.

Project description:A number of supervised machine learning models have recently been introduced for the prediction of drug-target interactions based on chemical structure and genomic sequence information. Although these models could offer improved means for many network pharmacology applications, such as repositioning of drugs for new therapeutic uses, the prediction models are often being constructed and evaluated under overly simplified settings that do not reflect the real-life problem in practical applications. Using quantitative drug-target bioactivity assays for kinase inhibitors, as well as a popular benchmarking data set of binary drug-target interactions for enzyme, ion channel, nuclear receptor and G protein-coupled receptor targets, we illustrate here the effects of four factors that may lead to dramatic differences in the prediction results: (i) problem formulation (standard binary classification or more realistic regression formulation), (ii) evaluation data set (drug and target families in the application use case), (iii) evaluation procedure (simple or nested cross-validation) and (iv) experimental setting (whether training and test sets share common drugs and targets, only drugs or targets or neither). Each of these factors should be taken into consideration to avoid reporting overoptimistic drug-target interaction prediction results. We also suggest guidelines on how to make the supervised drug-target interaction prediction studies more realistic in terms of such model formulations and evaluation setups that better address the inherent complexity of the prediction task in the practical applications, as well as novel benchmarking data sets that capture the continuous nature of the drug-target interactions for kinase inhibitors.

| S-EPMC4364066 | biostudies-literature

The Ras-Erk-ETS-Signaling Pathway Is a Drug Target for Longevity.

Project description:Identifying the molecular mechanisms that underlie aging and their pharmacological manipulation are key aims for improving lifelong human health. Here, we identify a critical role for Ras-Erk-ETS signaling in aging in Drosophila. We show that inhibition of Ras is sufficient for lifespan extension downstream of reduced insulin/IGF-1 (IIS) signaling. Moreover, direct reduction of Ras or Erk activity leads to increased lifespan. We identify the E-twenty six (ETS) transcriptional repressor, Anterior open (Aop), as central to lifespan extension caused by reduced IIS or Ras attenuation. Importantly, we demonstrate that adult-onset administration of the drug trametinib, a highly specific inhibitor of Ras-Erk-ETS signaling, can extend lifespan. This discovery of the Ras-Erk-ETS pathway as a pharmacological target for animal aging, together with the high degree of evolutionary conservation of the pathway, suggests that inhibition of Ras-Erk-ETS signaling may provide an effective target for anti-aging interventions in mammals.

| S-EPMC4518474 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data