Multi-domain Architecture Research Articles

Telomerase RNA structural heterogeneity in living human cells detected by DMS-MaPseq.

Telomerase is a specialized reverse transcriptase that uses an intrinsic RNA subunit as the template for telomeric DNA synthesis. Biogenesis of human telomerase requires its RNA subunit (hTR) to fold into a multi-domain architecture that includes the template-containing pseudoknot (t/PK) and the three-way junction (CR4/5). These two hTR domains bind the telomerase reverse transcriptase (hTERT) protein and are thus essential for telomerase catalytic activity. Here, we probe the structure of hTR in living cells using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and ensemble deconvolution analysis. Unexpectedly, approximately 15% of the steady state population of hTR has a CR4/5 conformation lacking features thought to be required for hTERT binding. The proportion of hTR CR4/5 that is folded into the primary functional conformation does not require hTERT expression and the fraction of hTR that assumes a misfolded CR4/5 domain is not refolded by overexpression of its hTERT binding partner. This result suggests a functional role for an RNA folding cofactor other than hTERT during telomerase biogenesis. Mutagenesis demonstrates that stabilization of the alternative CR4/5 conformation is detrimental to telomerase assembly and activity. Moreover, the alternative CR4/5 conformation is not found in telomerase RNP complexes purified from cells via an epitope tag on hTERT, supporting the hypothesis that only the major CR4/5 conformer is active. We propose that this misfolded portion of the cellular hTR pool is either slowly refolded or degraded. Thus, kinetic traps for RNA folding that have been so well-studied in vitro may also present barriers for assembly of ribonucleoprotein complexes in vivo.

Smart Urban Food Re-Distribution using Web Application

Smart Urban Food Re-Distribution using Web Application

FedRDR: Federated Reinforcement Distillation-Based Routing Algorithm in UAV-Assisted Networks for Communication Infrastructure Failures

Traditional Internet of Things (IoT) networks have limited coverage and may experience failures due to natural disasters affecting critical IoT devices, making it difficult for them to provide communication services. Therefore, how to establish network communication service more efficiently in the presence of fault points is the problem we solve in this paper. To address this issue, this study constructs a hierarchical multi-domain data transmission architecture for an emergency network with unmanned aerial vehicles (UAVs) employed as core communication devices. This architecture expands the functionality of UAVs as key network devices and provides a theoretical basis for their feasibility as intelligent network controllers and switches. Firstly, the UAV controllers perceive the network status and learn the spatio-temporal characteristics of air-to-ground network links. Secondly, a routing algorithm within the domain based on federated reinforcement distillation (FedRDR) is developed, which enhances the generalization capability of the routing decision model by increasing the training data samples. Simulation experiments are conducted, and the results show that the average communication data size between each domain controller and the server is approximately 45.3 KB when using the FedRDR algorithm. Compared to the transmission of parameters through federated reinforcement learning algorithms, FedRDR reduces the transmitted parameter size by approximately 29%. Therefore, the FedRDR routing algorithm helps to facilitate knowledge transfer, accelerate the training process of intelligent agents within the domain, and reduce communication costs in resource-constrained scenarios for UAV networks and has practical value.

Fluorescent human RPA to track assembly dynamics on DNA

DNA metabolic processes including replication, repair, recombination, and telomere maintenance occur on single-stranded DNA (ssDNA). In each of these complex processes, dozens of proteins function together on the ssDNA template. However, when double-stranded DNA is unwound, the transiently open ssDNA is protected and coated by the high affinity heterotrimeric ssDNA binding Replication Protein A (RPA). Almost all downstream DNA processes must first remodel/remove RPA or function alongside to access the ssDNA occluded under RPA. Formation of RPA-ssDNA complexes trigger the DNA damage checkpoint response and is a key step in activating most DNA repair and recombination pathways. Thus, in addition to protecting the exposed ssDNA, RPA functions as a gatekeeper to define functional specificity in DNA maintenance and genomic integrity. RPA achieves functional dexterity through a multi-domain architecture utilizing several DNA binding and protein-interaction domains connected by flexible linkers. This flexible and modular architecture enables RPA to adopt a myriad of configurations tailored for specific DNA metabolic roles. To experimentally capture the dynamics of the domains of RPA upon binding to ssDNA and interacting proteins we here describe the generation of active site-specific fluorescent versions of human RPA (RPA) using 4-azido-L-phenylalanine (4AZP) incorporation and click chemistry. This approach can also be applied to site-specific modifications of other multi-domain proteins. Fluorescence-enhancement through non-canonical amino acids (FEncAA) and Förster Resonance Energy Transfer (FRET) assays for measuring dynamics of RPA on DNA are also described. The fluorescent human RPA described here will enable high-resolution structure-function analysis of RPA-ssDNA interactions.

Bi-channel hybrid GAN attention based anomaly detection system for multi-domain SDN environment

Software-Defined Networking (SDN) is a strategy that leads the network via software by separating its control plane from the underlying forwarding plane. In support of a global digital network, multi-domain SDN architecture emerges as a viable solution. However, the complex and ever-evolving nature of network threats in a multi-domain environment presents a significant security challenge for controllers in detecting abnormalities. Moreover, multi-domain anomaly detection poses a daunting problem due to the need to process vast amounts of data from diverse domains. Deep learning models have gained popularity for extracting high-level feature representations from massive datasets. In this work, a novel deep neural network architecture, supervised learning based LD-BiHGA (Low Dimensional Bi-channel Hybrid GAN Attention) system is designed to learn class-specific features for accurate anomaly detection. Two asymmetric GANs are employed for learning the normal and abnormal network flows separately. Then, to extract more relevant features, a bi-channel attention mechanism is added. This is the first study to introduce an innovative hybrid architecture that merges bi-channel hybrid GANs with attention models for the purpose of anomaly detection in a multi-domain SDN environment that effectively handles real-time unbalanced data. The suggested architecture demonstrates its effectiveness on three benchmark datasets, achieving an average accuracy improvement of 7.225% on balanced datasets and 3.335% on imbalanced datasets compared to previous intrusion detection system (IDS) architectures in the literature.

An Updated View on the Cellular Uptake and Mode-of-Action of Clostridioides difficile Toxins.

Research on the human gut pathogen Clostridioides (C.) difficile and its toxins continues to attract much attention as a consequence of the threat to human health posed by hypervirulent strains. Toxin A (TcdA) and Toxin B (TcdB) are the two major virulence determinants of C. difficile. Both are single-chain proteins with a similar multidomain architecture. Certain hypervirulent C. difficile strains also produce a third toxin, namely binary toxin CDT (C. difficile transferase). C. difficile toxins are the causative agents of C. difficile-associated diseases (CDADs), such as antibiotics-associated diarrhea and pseudomembranous colitis. For that reason, considerable efforts have been expended to unravel their molecular mode-of-action and the cellular mechanisms responsible for their uptake. Many of these studies have been conducted in European laboratories. Here, we provide an update on our previous review (Papatheodorou et al. Adv Exp Med Biol, 2018) on important advances in C. difficile toxins research.

Protein-based bandpass filters for controlling cellular signaling with chemical inputs

Biological signal processing is vital for cellular function. Similar to electronic circuits, cells process signals via integrated mechanisms. In electronics, bandpass filters transmit frequencies with defined ranges, but protein-based counterparts for controlled responses are lacking in engineered biological systems. Here, we rationally design protein-based, chemically responsive bandpass filters (CBPs) showing OFF-ON-OFF patterns that respond to chemical concentrations within a specific range and reject concentrations outside that range. Employing structure-based strategies, we designed a heterodimeric construct that dimerizes in response to low concentrations of a small molecule (ON), and dissociates at high concentrations of the same molecule (OFF). The CBPs have a multidomain architecture in which we used known drug receptors, a computationally designed protein binder and small-molecule inhibitors. This modular system allows fine-tuning for optimal performance in terms of bandwidth, response, cutoff and fold changes. The CBPs were used to regulate cell surface receptor signaling pathways to control cellular activities in engineered cells.

A Systematic Compilation of Human SH3 Domains: A Versatile Superfamily in Cellular Signaling.

SRC homology 3 (SH3) domains are fundamental modules that enable the assembly of protein complexes through physical interactions with a pool of proline-rich/noncanonical motifs from partner proteins. They are widely studied modular building blocks across all five kingdoms of life and viruses, mediating various biological processes. The SH3 domains are also implicated in the development of human diseases, such as cancer, leukemia, osteoporosis, Alzheimer's disease, and various infections. A database search of the human proteome reveals the existence of 298 SH3 domains in 221 SH3 domain-containing proteins (SH3DCPs), ranging from 13 to 720 kilodaltons. A phylogenetic analysis of human SH3DCPs based on their multi-domain architecture seems to be the most practical way to classify them functionally, with regard to various physiological pathways. This review further summarizes the achievements made in the classification of SH3 domain functions, their binding specificity, and their significance for various diseases when exploiting SH3 protein modular interactions as drug targets.

The protease associated (PA) domain in ScpA from Streptococcus pyogenes plays a role in substrate recruitment

Annually, over 18 million disease cases and half a million deaths worldwide are estimated to be caused by Group A Streptococcus. ScpA (or C5a peptidase) is a well characterised member of the cell enveleope protease family, which possess a S8 subtilisin-like catalytic domain and a shared multi-domain architecture. ScpA cleaves complement factors C5a and C3a, impairing the function of these critical anaphylatoxins and disrupts complement-mediated innate immunity. Although the high resolution structure of ScpA is known, the details of how it recognises its substrate are only just emerging. Previous studies have identified a distant exosite on the 2nd fibronectin domain that plays an important role in recruitment via an interaction with the substrate core. Here, using a combination of solution NMR spectroscopy, mutagenesis with functional assays and computational approaches we identify a second exosite within the protease-associated (PA) domain. We propose a model in which the PA domain assists optimal delivery of the substrate's C terminus to the active site for cleavage.

An Alternative Multi-Physics-Based Methodology for Strongly Coupled Electro-Magneto-Mechanical Problems

The analysis of complex systems tends to be approached through a separation and a simplification of the main macro phenomena and, thus, addressed through dedicated techniques, tools, and algorithms. A smart and interesting possibility, instead, is represented by the so-called model-based design analysis, which allows one to interface phenomena coming from interactions of different physical natures. This paper aims to propose a multi-physics Matlab/Simulink®-based architecture that allows one to integrate general and strongly non-linear coupling phenomena, taking efforts from two novel implemented bi-directional co-simulation routines based on Spice® and ESRF Radia® engines. Emphasis is dedicated to the discussion and description of the co-simulation algorithms and processes characteristic of these routines, which allow the analog electronic and the magneto dynamic domain’s integration under a single simulation environment. To highlight the reliability of the multi-domain architecture and to validate the reported co-simulation results, a comparison with the experimental measures obtained on an innovative MEMS electromagnetic actuator are proposed.

Expression of blue pigment synthetase a from Streptomyces lavenduale reveals insights on the effects of refactoring biosynthetic megasynthases for heterologous expression in Escherichia coli.

High GC bacteria from the genus Streptomyces harbor expansive secondary metabolism. The expression of biosynthetic proteins and the characterization and identification of biological “parts” for synthetic biology purposes from such pathways are of interest. However, the high GC content of proteins from actinomycetes in addition to the large size and multi-domain architecture of many biosynthetic proteins (such as non-ribosomal peptide synthetases; NRPSs, and polyketide synthases; PKSs often called “megasynthases”) often presents issues with full-length translation and folding. Here we evaluate a non-ribosomal peptide synthetase (NRPS) from Streptomyces lavenduale, a multidomain “megasynthase” gene that comes from a high GC (72.5%) genome. While a preliminary step in revealing differences, to our knowledge this presents the first head-to-head comparison of codon-optimized sequences versus a native sequence of proteins of streptomycete origin heterologously expressed in E. coli. We found that any disruption in co-translational folding from codon mismatch that reduces the titer of indigoidine is explainable via the formation of more inclusion bodies as opposed to compromising folding or posttranslational modification in the soluble fraction. This result supports that one could apply any refactoring strategies that improve soluble expression in E. coli without concern that the protein that reaches the soluble fraction is differentially folded.

Abstract A025: Investigating the molecular mechanisms of regulation of the RAS guanine nucleotide exchange factor, SOS1 by Grb2 and 14-3-3

Abstract The MAPK/ERK signaling pathway is one of the most heavily mutated in human cancers. In normal cells, the stimulation of receptor tyrosine kinases (e.g. EGFR) on the plasma membrane signals the GTP-loading and activation of RAS through a mechanism catalyzed by the guanine nucleotide exchange factor (GEF) Son of Sevenless 1 (SOS1). RAS activation, in turn, initiates the RAF-MEK-ERK kinase cascade which triggers many downstream signals that can affect gene transcription, protein translation, cell proliferation, and feedback regulation. Several factors regulate SOS1 GEF activity, including two autoinhibitory domains within its own multi-domain architecture. First, the N-terminal domains of SOS1 occlude the allosteric RAS-GTP binding site in the RAS exchanger motif—thereby precluding SOS1 GEF activity—and this inhibition is relieved upon membrane recruitment and PIP2 phospholipid binding. Second, the C-terminal Proline-Rich Region (PRR) of SOS1 also occludes allosteric RAS-GTP binding by an unknown mechanism and is relieved when the growth factor receptor-bound protein 2 (Grb2) binds to motifs in the PRR. While the independent functions of these domains and interactions to inhibition and activation of GEF activity of SOS1 are known, the molecular mechanisms are poorly understood. An additional negative feedback loop involves the phosphorylation of the SOS1 PRR at two sites by the ribosomal protein S6 kinase 1 (RSK1), a substrate of downstream ERK. These modifications create 14-3-3 binding sites on SOS1, where 14-3-3 binding downregulates GEF activity, possibly by obstructing Grb2 association with the SOS1 PRR and membrane localization of SOS1. This work reconstitutes the SOS1:Grb2 and the SOS1:14-3-3 protein complexes in vitro to study the molecular mechanisms underlying SOS1 activity regulation. Citation Format: Orlando E. Martinez, Jawahar Sudhamsu. Investigating the molecular mechanisms of regulation of the RAS guanine nucleotide exchange factor, SOS1 by Grb2 and 14-3-3 [abstract]. In: Proceedings of the AACR Special Conference: Targeting RAS; 2023 Mar 5-8; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Res 2023;21(5_Suppl):Abstract nr A025.

The architecture of abnormal reward behaviour in dementia: multimodal hedonic phenotypes and brain substrate.

Abnormal reward processing is a hallmark of neurodegenerative diseases, most strikingly in frontotemporal dementia. However, the phenotypic repertoire and neuroanatomical substrates of abnormal reward behaviour in these diseases remain incompletely characterized and poorly understood. Here we addressed these issues in a large, intensively phenotyped patient cohort representing all major syndromes of sporadic frontotemporal dementia and Alzheimer's disease. We studied 27 patients with behavioural variant frontotemporal dementia, 58 with primary progressive aphasia (22 semantic variant, 24 non-fluent/agrammatic variant and 12 logopenic) and 34 with typical amnestic Alzheimer's disease, in relation to 42 healthy older individuals. Changes in behavioural responsiveness were assessed for canonical primary rewards (appetite, sweet tooth, sexual activity) and non-primary rewards (music, religion, art, colours), using a semi-structured survey completed by patients' primary caregivers. Changes in more general socio-emotional behaviours were also recorded. We applied multiple correspondence analysis and k-means clustering to map relationships between hedonic domains and extract core factors defining aberrant hedonic phenotypes. Neuroanatomical associations were assessed using voxel-based morphometry of brain MRI images across the combined patient cohort. Altered (increased and/or decreased) reward responsiveness was exhibited by most patients in the behavioural and semantic variants of frontotemporal dementia and around two-thirds of patients in other dementia groups, significantly (P < 0.05) more frequently than in healthy controls. While food-directed changes were most prevalent across the patient cohort, behavioural changes directed toward non-primary rewards occurred significantly more frequently (P < 0.05) in the behavioural and semantic variants of frontotemporal dementia than in other patient groups. Hedonic behavioural changes across the patient cohort were underpinned by two principal factors: a 'gating' factor determining the emergence of altered reward behaviour and a 'modulatory' factor determining how that behaviour is directed. These factors were expressed jointly in a set of four core, trans-diagnostic and multimodal hedonic phenotypes: 'reward-seeking', 'reward-restricted', 'eating-predominant' and 'control-like'-variably represented across the cohort and associated with more pervasive socio-emotional behavioural abnormalities. The principal gating factor was associated (P < 0.05 after correction for multiple voxel-wise comparisons over the whole brain) with a common profile of grey matter atrophy in anterior cingulate, bilateral temporal poles, right middle frontal and fusiform gyri: the cortical circuitry that mediates behavioural salience and semantic and affective appraisal of sensory stimuli. Our findings define a multi-domain phenotypic architecture for aberrant reward behaviours in major dementias, with novel implications for the neurobiological understanding and clinical management of these diseases.

Discovery of a Chemical Probe to Study Implications of BPTF Bromodomain Inhibition in Cellular and in vivo Experiments.

The bromodomain and PHD-finger containing transcription factor (BPTF) is part of the nucleosome remodeling factor (NURF) complex and has been implicated in multiple cancer types. Here, we report the discovery of a potent and selective chemical probe targeting the bromodomain of BPTF with an attractive pharmacokinetic profile enabling cellular and in vivo experiments in mice. Microarray-based transcriptomics in presence of the probe in two lung cancer cell lines revealed only minor effects on the transcriptome. Profiling against a panel of cancer cell lines revealed that the antiproliferative effect does not correlate with BPTF dependency score in depletion screens. Both observations and the multi-domain architecture of BPTF suggest that depleting the protein by proteolysis targeting chimeras (PROTACs) could be a promising strategy to target cancer cell proliferation. We envision that the presented chemical probe and the related negative control will enable the research community to further explore scientific hypotheses with respect to BPTF bromodomain inhibition.

Protein-plastic interactions: The driving forces behind the high affinity of a carbohydrate-binding module for polyethylene terephthalate

Polyethylene terephthalate (PET) waste is a common pollutant in the environment, mainly due to resistance of the plastic to bio-degradation. Nevertheless, hydrolytic enzymes have been identified with activity on this substrate, which are continually being engineered to increase activity. Some insoluble biological polymers are degraded by enzymes with a multi-domain architecture, comprising of a catalytic domain, and a substrate-binding domain, such as a carbohydrate-binding module (CBM). Enzymes that degrade PET have been shown to have a higher activity when fused with these CBMs, indicating a promising route for engineering better enzymes for plastic bioprocessing. However, no detailed study of the affinity and binding mechanism of these domains on PET has yet been made. Here, we perform an in depth analysis of a binding domain from CBM family 2 on PET, showing that the affinity of the protein for the plastic is highly dependent on temperature and crystallinity of the plastic. We also investigate the mechanism of the interaction, and show how affinity may be engineered in both directions. CBM affinity for other synthetic polymers is also demonstrated for the first time. Our results demonstrate that the substrate affinity of fusion enzymes with binding modules can be tuned to the desired level.

Tuning the phase separation properties of HP1α through ligand interactions.

Heterochromatin protein 1α (HP1α) is a crucial component for gene repression and the structural integrity of heterochromatin. It is proposed that HP1α functions through a liquid-liquid phase separation (LLPS) mechanism where HP1α compacts nucleosome arrays into a liquid compartment and prevents transcription factors from accessing chromatin. HP1α can undergo LLPS via phosphorylation of the N-terminus extension (NTE) or through interactions with DNA/nucleosomes. The multidomain architecture of HP1α allows for simultaneous multivalent interactions with other HP1α proteins and multiple binding partners. These multivalent interactions are believed to be important for forming and maintaining heterochromatin structure but their exact role in HP1α LLPS is not well understood. In our study, we used experimental and computational approaches to investigate how a series of peptides from HP1α binding partners can fine tune the ability of the protein to undergo phase separation. Our results showed that in phosphorylation-driven LLPS, positively charged peptides enhance phase separation, while negatively or near neutral charged peptides disrupt the process. DNA-driven LLPS can also be inhibited by negatively or near neutral charged ligands. However, in this case, positively charged peptides compete with HP1α for DNA interactions, which also disrupts LLPS. Our results suggest that phosphorylation-driven LLPS has a larger tunability range compared to phase separation with DNA, and that the electrostatic properties of HP1α ligands play an important role in modulating this process. Our study provides insights into the potential mechanisms of heterochromatin regulation where binding partners may modulate the biophysical properties of HP1α to control access to chromatin and the genetic information in the cell.

All-Atom Simulations Elucidate the Impact of U2AF2 Cancer-Associated Mutations on Pre-mRNA Recognition.

The U2AF2 splicing factor, made of two tandem RNA recognition motifs (RRMs) joined by a flexible linker, selects the intronic polypyrimidine sequence of premature mRNA, thus ensuring splicing fidelity. Increasing evidence links mutations of key splicing factors, including U2AF2, to a variety of cancers. Nevertheless, the impact of U2AF2 cancer-associated mutations on polypyrimidine recognition remains unclear. Here, we combined extensive (18 μs-long) all-atom molecular dynamics simulations and dynamical network theory analysis (NWA) of U2AF2, in its wild-type form and in the presence of the six most frequent cancer-associated mutations, bound to a poly-U strand. Our results reveal that the selected mutations affect the pre-mRNA binding at two hot spot regions, irrespectively of where these mutants are placed on the distinct U2AF2 domains. Complementarily, NWA traced the existence of cross-communication pathways, connecting each mutation site to these recognition hot spots, whose strength is altered by the mutations. Our outcomes suggest the existence of a structural/dynamical interplay of the two U2AF2's RRMs underlying the recognition of the polypyrimidine tract and reveal that the cancer-associated mutations affect the polypyrimidine selection by altering the RRMs' cooperativity. This mechanism may be shared by other RNA binding proteins hallmarked, like U2AF2, by multidomain architecture and high plasticity.

The role of binding modules in enzymatic poly(ethylene terephthalate) hydrolysis at high-solids loadings

In nature, enzymes that deconstruct biological polymers, such as cellulose and chitin, often exhibit multi-domain architectures, comprising a catalytic domain and a non-catalytic binding module; the latter serves to increase the enzyme concentration at the substrate surface. This multi-domain architecture has been shown to improve the hydrolysis of poly(ethylene terephthalate) (PET) using engineered cutinase enzymes. Here, we examine the role of accessory binding modules at industrially relevant PET solids loadings necessary for cost-effective enzymatic recycling. Using a thermostable variant of leaf compost cutinase (LCC), we produced synthetic fusion constructs of LCC with five type A carbohydrate-binding modules (CBMs). At solids loadings below 10 wt %, the CBMs improve aromatic monomer yield from PET, but above this threshold, conversion extents up to 97% are reached with no added benefits from the presence of CBM fusions. This suggests that fusion constructs with the herein studied CBMs are not necessary for industrial enzymatic PET recycling. • A new variant of LCC exhibits higher thermostability and greater PET turnover • Specific CBMs stimulate PET hydrolysis at low-solids loading • The advantage of these CBMs is lost at industrially relevant high-solids loading Closed-loop recycling and open-loop upcycling of waste plastics represent a suite of critical technologies to address the plastic-waste pollution crisis. Enzymatic deconstruction of the synthetic polyester poly(ethylene terephthalate) (PET) is among the several options available for chemical recycling of this common plastic. While early demonstrations of enzymatic PET recycling have shown feasibility, the technology is not yet cost competitive with production of virgin petroleum-derived PET. This study analyzes an enzyme engineering approach that takes a lesson from nature to improve the catalytic efficiency of PET-hydrolyzing enzymes and evaluates the impact of this strategy under reaction conditions that simulate a key industrial feature of enzymatic PET recycling. The implications of this study can help focus the resources available to the field on solutions that can enable rapid deployment of viable technologies to realistically address plastics pollution. Enzymatic recycling of PET offers a promising solution to the global plastic problem. Research into accessory domains to enhance PET turnover has so far not been tested at high PET solids loadings. Here, we show that carbohydrate-binding domains do not offer any benefit at high PET solids loadings that are relevant to industrial-scale biorecycling.

A GRU-based traffic situation prediction method in multi-domain software defined network.

With the continuous development and improvement of Software-Defined Networking (SDN), large-scale networks are divided into multiple domains. Each domain, which is managed by a controller, forms multi-domain SDN architecture. In multi-domain SDN, the dynamics and complexity are more significant, bringing great challenges to network management. Comprehensively and accurately predicting traffic situation in multi-domain SDN can better maintain network stability. In this article, we propose a traffic situation prediction method based on the gated recurrent unit (GRU) network in multi-domain SDN. We first analyzed the relevant factors that affect data traffic and control traffic and transformed them into a time series of actual situation values. Then, to enhance the prediction performance of GRU, we used the salp swarm algorithm to optimize the hyperparameters of GRU automatically. Finally, we adopted hyperparameter optimized GRU to achieve traffic situation prediction in multi-domain SDN. The experimental results indicate that the proposed method outperforms other traditional machine learning algorithms in terms of prediction accuracy.

A Blockchain-Based Multidomain Authentication Scheme for Conditional Privacy Preserving in Vehicular Ad-Hoc Network

Vehicular ad-hoc network enhances driving safety and enables various intelligent transportation applications by adopting the revolutionary vehicular wireless communication technology. This has attracted a lot of attentions from both academia and industry in recent years. Given the sophistication of vehicular manufacturing and the heterogeneity of intelligent transport terminals, performing vehicular authentication is of great importance. The existing schemes have largely considered vehicle security and authentication within a single administrative domain, which lacks supervision of the authority and entity in the intelligent transportation system. In this article, we propose a multidomain vehicular authentication architecture by introducing blockchain technique to build distributed trust and share cross-domain information among multiple administrative domains. To guarantee the anonymity and traceability, a pseudonym-based privacy-preserving authentication method is proposed. Specifically, considering the supervision of authority and the resilience to key escrow, we design a two-phase pseudonym distribution mechanism with the assistance of a roadside unit (RSU) proxy. We conduct in-depth security analysis by comparing with existing works and deploy experiments to show the efficiency and feasibility of the proposed scheme in the multidomain scenario.