NS-2 Simulator Research Articles

Utilizing minimum spanning trees for effective mobile sink routing in wireless sensor networks

With many practical applications, wireless sensor networks (WSNs) represent an important field of study. Real-world applications of WSNs include smart home automation, healthcare, agriculture, industrial automation, and environmental monitoring. WSNs present countless chances for creative solutions across various industries as they develop and become more sophisticated. But because they are unattended, we must devise ways to make them work better without using the sensor nodes’ most important resource—battery power. A unique sink mobility model from a deployed WSN is proposed in this paper, based on constructing a minimal Spanning tree. The proposed approach derives a controlled movement model for the mobile sink based on minimal spanning tree (MST) features. Consequently, fixed nodes will be scheduled and visited to save routing overhead and improve network efficiency. Using the properties of the minimal spanning tree, the moving sink node can visit immobile sensor nodes, which is the most effective approach to gather data and send it to the base station. The effectiveness of WSNs was examined when implementing this mobility model, and we used the NS-2 simulator to run simulations to assess how efficiently the suggested strategy performed. Our findings demonstrate that WSN performance can be significantly enhanced by implementing the proposed method.

Improving the performance of IoT devices that use Wi-Fi

<p>Providing quality service to users of the internet of things (IoT) entails addressing two crucial aspects: one related to security and the other concerning the limited resources of IoT devices. We will face a challenge while using timesensitive applications within a network that utilizes a high-performance Wi-Fi technology with exceeding energy consumption. Due to this research challenge, we propose a new algorithm, IoT-quality of service (QoS), designed to achieve a true balance between enhancing the security aspects of IoT devices and improving network-hardware performance. Thus, the algorithm efficiently manages the limited energy resources by monitoring energy levels, communication quality, and queuing delay at access points. This is accomplished by utilizing a streamlined identity management system capable of achieving authentication and access authorization with reduced loading for IoT devices. The research hypothesis underwent validation through a comparative analysis of its performance against the conventional model of a Wi-Fi-based IoT device. This evaluation was conducted utilizing the NS3 simulator and was based on a predetermined set of parameters influencing the examined performance metrics, including power consumption, throughput, delay, and response time. The findings exposed the superiority of the proposed algorithm.</p>

SERAV Deep-MAD: Deep Learning-Based Security–Reliability–Availability Aware Multiple D2D Environment

The tremendous growth of internet-connected devices can lead to network congestion, making it essential to incorporate new technologies to optimize performance. Thus, Device to Device(D2D) communication has been deemed as an emerging technology that can be used to communicate efficiently. However, establishing a secure and reliable mechanism for Device-to-Device (D2D) communication that ensures security, reliability, and availability poses a significant challenge. To tackle these issues a novel deep learning-based security-reliability-availability aware multiple D2D environment (SERAV Deep-MAD) has been proposed for Secure D-2-D Communication in a Fog environment. The proposed method utilizes a Fully Homomorphic Quantum Diffie Hellman Encryption (FHQDHE) to secure the data while transmitting. The proposed method utilizes the novel secure Quantum Diffie Hellman key exchange (QDHKE) technique for sharing the key to transform the plain data into cipher data, then applies FH operations on the encrypted data before transferring it to the Fog environment. Whenever a client requests data from the Fog, the Fog provider verifies the client's access rights. Moreover, the Attention-based Bi-GRU model is utilized to categorize whether the device is non-attack or attack, if the data is attacked then the proposed model classifies multiple attacks. The NS2 Simulator is used to verify and validate the proposed SERAV Deep-MAD model, and resiliency analysis is done to assess performance. The proposed techniques attain a higher accuracy of 98.18% which is 1.58%, 2.02%, and 2.41% better than MECC, MIMO, andAAKA-D2D respectively.

Implementation of A Delay-Tolerant Routing Protocol in the Network Simulator NS-3

The paper explores the implementation of the Epidemic Routing Protocol using the NS-3 simulator, focusing on its application in intermittently connected networks like Mobile Adhoc Networks (MANETs). The Epidemic Protocol maximizes message delivery by flooding the network with multiple copies, ensuring reliability even in sparse or highly mobile environments. Through NS-3 simulations, the study examines the protocol’s performance, considering factors such as network size, node mobility, and message Time-To-Live (TTL). The simulation, which models an ad-hoc wireless network using IEEE 802.11b, demonstrates that the protocol achieves a 100-percentage packet delivery ratio with minimal latency. Tools like NetAnim provide detailed insights into node interactions and message dissemination, highlighting the protocol’s effectiveness in maintaining communication under challenging conditions. The paper concludes that while the Epidemic Protocol is resource- intensive, it is highly effective for scenarios where traditional routing methods fail, offering a reliable solution for dynamic and partitioned network.

Design of some phthalazine molecules as novel VEGFR-2 target inhibitors through 3D-QSAR modeling, molecular docking and dynamic simulation and pharmacokinetics profiling

AbstractBreast cancer is one of the dominant cause of cancer-related mortality in females, with an incidence of approximately 1.3 million cases annually, necessitating the development of effective therapeutic strategies. In this study, 3D-QSAR models were reported based on Phthalazine derivatives as VEGFR-2 inhibitors. The activities of these derivatives were correlated with the steric (S), electrostatic (E), hydrogen bond acceptor (A), and donor (D), and hydrophobic (H) fields, which served as critical parameters in model development. Statistical studies of these models showed that the best models are; CoMFA_S (Q2 = 0.623, R2 = 0.941), and CoMSIA_E + D (Q2 = 0.615, R2 = 0.977). Based on the insights from the model fields and docking simulation of the template (compound 17), twelve molecules were designed. These novel molecules exhibited stronger potency compared to the template and the standard, Sorafenib. Compound 17A emerged as the most potent, with pIC50 = 5.98, for CoMFA_S and 5.85, for CoMSIA_E + D, and a strong docking affinity of − 97.271 kcal/mol, therefore subjected to a 100-ns MD simulation. Results indicate better interaction and stabilizing potential over Sorafenib, due to the lower RMSD, RMSF, Rg, values and favorable hydrogen bond analyses. These conclusions were validated by Gibbs free energy analysis and MM-GBSA calculations, revealing a more favorable interaction free energy of − 18.48 kcal/mol related to Sorafenib. Furthermore, these designed compounds demonstrated promising pharmacokinetic profiles.

Advanced spatial query processing in IoT through mobile agent integration

In IoT environments, various applications and protocols rely on spatial query processing to obtain, analyze, and interpret information from sensor nodes based on their location within a specific area. It enables the efficient monitoring and management of spatial data, which is crucial for applications such as environmental monitoring, smart cities, and disaster response. By querying the location and status of sensor nodes, spatial query processing facilitates real-time decision-making, optimizes resource allocation, and enhances the overall performance of the IoT system.This paper focuses on Window queries, a key spatial query type that retrieves data from sensors within a defined two-dimensional zone. The research aims to improve spatial query processing in IoT environments by proposing a Window query processing method that balances various performance factors such as energy efficiency, latency, accuracy, and query success rate. We introduce a novel approach using mobile agents to enhance spatial query processing by addressing the constraints of sensor networks. Simulation results from the NS-2 simulator demonstrate the effectiveness of our method across different parameters and environments.

Comparative Analysis of Different Transport Layer Protocol Techniques Incognitive Network

Most of the networks employ TCP protocol for transmission control in transport mechanism. Although it offers numerous services such as reliability, end-to-end delivery, secure transmission of data, and so on to applications functioning across the World Wide Web, TCP needs to have effective congestion management techniques in order to handle traffic with a lot of data. Still, TCP have poor performance during data transmission in the network. The network community continues conducting research to develop a method that should provide a fair and effective transmission bandwidth distribution. Numerous congestion control strategies have been developed based on previous research in this area. This work discusses, identifies, compares, and analyses the behaviour of a few network congestion control strategies to determine their benefits and limitations. The widely known network simulator ns2 is employed for the simulation. The performance metrics for QTCP, TCP new Reno, TCP- Hybla, L-TCP and RL-TCP are throughput, average delay, PDR, packet loss, average jitter, latency and fairness are considered. The RL-TCP exhibits superior performance in multiple measures when it is compared to alternative TCP protocols, as indicated by simulation results. These metrics encompass throughput, average delay, packet delivery ratio (PDR), packet loss, jitter, latency, and fairness. Furthermore, several TCP protocols, such as L-TCP, TCP-Hybla, QTCP, and TCP-New Reno, have undergone evaluation, uncovering disparities in their individual performance attributes. Nevertheless, the RL-TCP regularly demonstrates superior performance in all aspects.

Exploration of phytoconstituents of Medhya Rasayana herbs to identify potential inhibitors for cerebroside sulfotransferase through high-throughput screening.

Cerebroside sulfotransferase (CST) is a key enzyme in sulfatide biosynthesis and regulation of the myelin sheath in the nervous system. To counter sulfatide accumulation with the deficiency of aryl sulfatase A, CST is considered a target protein in substrate reduction therapy in metachromatic leukodystrophy. In this study, 461 phytoconstituents from four herbs of Medhya Rasayana were screened using multi-pronged virtual screening methods including molecular docking, molecular dynamics (MD) simulation, and reverse pharmacophore analysis. The initial screening of the top 15 hits was based on the binding affinity of the compounds toward the CST substrate-binding site using the lowest free energy of a binding score cutoff of ≤ -7.5 kcal/mol, with the number of conformations in the largest cluster more than 75. The absorption, distribution, metabolism, and excretion (ADME) and toxicity-based pharmacokinetic analysis delivered the top four hits: 18alpha-glycyrrhetinic acid, lupeol, alpha carotene, and beta-carotene, with high blood-brain barrier permeability and negligible toxicity. Furthermore, a 100-ns simulation of protein-ligand complexes with a trajectory analysis of structural deviation, compactness, intramolecular interactions, principal component analysis, free energy landscape, and dynamic cross-correlation analysis showed the binding potential and positioning of the four hits in the binding pocket. Thus, an in-depth analysis of protein-ligand interactions from pre- and post-molecular dynamics simulation, along with reverse pharmacophore mapping, suggests that 18alpha-glycyrrhetinic acid is the most potent and specific CST inhibitor, while beta-carotene could be considered the second most potent compound for CST inhibition as it also exhibited overall stability throughout the simulation. Therefore, the computational drug screening approach applied in this study may contribute to the development of oral drugs as a therapeutic option for metachromatic leukodystrophy.

Performance Analysis for Producer Mobility in Named Data Networking

The influence of producer mobility on Named Data Networking (NDN) networks in dynamic networking environments is amplified, hence necessitating an escalation in the demand for performance analysis. When producers transition between different sites or nodes relocation, there is a significant increase in packet loss. Consequently, the present work centres on conducting experiments and evaluating producer mobility by utilizing the Hybrid Indirection Method (HIM) to mitigate the effects of signalling cost on the handoff procedure. This study aims to analyse the effects of producer mobility, specifically focusing on two critical factors: handoff signalling cost and packet data ratio. The data gathered from the study provide significant insights into the benefits and challenges related to producer mobility. This research paper comprehensively investigates producer mobility within the network simulator ns3 framework. The findings demonstrate a notable enhancement achieved by the HIM technique, resulting in substantial improvements in handoff signalling cost and packet data ratio.

Link-Quality Aware Routing for Software-Defined Vehicular Networks

The routing protocol for Vehicular Ad Hoc Networks (VANETs) uses hop-count as a routing metric to determine the shortest route from source to destination. The presence of unstable links in the selected route may cause packet failures, resulting in an increase in packet retransmissions, causing network congestion, increasing total end-to-end delay, and reducing throughput. Thus, route selection based on hop count may not always be optimal in terms of route link quality. In Software-Defined Vehicular Networks (SDVN), the global view of link-state information for the vehicular networks is created at the controller; thus, a better route can be computed. Our study proposes an SDVN routing technique that considers link quality while determining the route. Our proposed framework examines the link quality using two metrics: Expected Transmission Count (ETX) and Expected Transmission Time (ETT), and this information is used by the controller to compute the flow rule. The routing performance of the proposed scheme is compared to traditional VANETs and other existing works with the help of network simulations using the NS-3 simulator. The obtained simulation results for our proposed scheme outperform in terms of performance metrics such as packet delivery ratio, average throughput, and end-to-end delay.

From millets to medicine: ADMET insights into diabetes management with P. sumatrense compounds

Diabetes mellitus, a prevalent metabolic disorder characterised by impaired blood glucose regulation, has escalated into a global health crisis, exacerbated by high-glycaemic diets and unhealthy eating habits. While therapeutic agents such as acarbose mitigate diabetes by inhibiting alpha-amylase and alpha-glucosidase, their use is marred by adverse side effects, underscoring the need for safer, plant-based alternatives. This study explores the antidiabetic potential of Little Millet, an underutilised cereal grain with a low glycaemic index, rich in bioactive compounds. Unlike common staples such as wheat and rice, Little Millet contains unique compounds, including octodrine, 18,19-secoyohimban-19-oic acid, and phenylephrine, which were investigated for their novel application in diabetes management. Gas chromatography-mass spectrometry (GCMS) analysis identified 120 bioactive compounds, selected for their abundance and potential bioactivity. These compounds span fatty acids, phenols, flavonoids, organic acids, sugar alcohols, and amino acids, all of which were rigorously docked to alpha-amylase and human maltase-glucoamylase receptors. Notably, key ligands such as chlorogenic acid and 18,19-secoyohimban-19-oic acid exhibited superior binding affinities compared to acarbose, with promising drug-likeness and ADMET profiles, suggesting higher absorption and fewer side effects. A 100-ns dynamics simulation further validated the stability of these compounds, positioning them as viable candidates for diabetes treatment. These findings advance drug design and highlight the potential of incorporating Little Millet into diets for diabetes prevention. Further validation through In-vitro, In-vivo, and clinical studies is essential to fully realise their therapeutic potential. This research also opens avenues for exploring Little Millet in managing related conditions and enhancing its health benefits through breeding programmes.

Towards fine-grained load balancing with dynamical flowlet timeout in datacenter networks

In modern datacenter networks (DCNs), load balancing mechanisms are widely deployed to enhance link utilization and alleviate congestion. Recently, a large number of load balancing algorithms have been proposed to spread traffic among the multiple parallel paths. The existing solutions make rerouting decisions for all flows once they experience congestion on a path. They are unable to distinguish between the flows that really need to be rerouted and the flows that potentially have negative effects due to rerouting, resulting in frequently ineffective rerouting. Fine-grained rerouting will also cause severe packet reordering, especially in asymmetric topology scenarios. To address the above issues, we present a fine-grained traffic-differentiated load balancing (TDLB) mechanism, which aims to distinguish flows that are necessarily to be rerouted and reroute traffic in fine-grained without packet reodering. Specifically, TDLB distinguishes the traffic that must be rerouted through the host pair information in the packet header, and selects an optimal path for rerouting. To prevent severe packet reodering caused by excessive path delay differences, TDLB dynamically adjusts the flowlet timeout to segment the traffic and select the optimal path for rerouting. The NS-2 simulation results show that TDLB effectively reduces tail latency and average flow completion time (FCT) for short flows by up to 49% and 46%, respectively, compared to the state-of-the-art load balancing schemes.

Energy Efficient Secured PSO Optimized Clustering and Data Aggregation Routing Protocol for Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), sensor nodes are placed to sense and collect data. Due to the energy constraint nature of WSN, optimising the energy during the data dissemination is a major concern. To solve this problem, data aggregation may be used to bring down the redundant transmission of packets in WSN. In most of the previously available techniques, security is also a major concern during data aggregation and routing process with optimized energy. Many data aggregation-based routing systems are subject to security attacks during the data transfer from sensors to source to Clustered Heads (CHs) and then to sink with data aggregation process. Moreover, the existing data aggregation-based routing protocols suffer from data redundancy with less accuracy in aggregated data. For handling such issues order to overcome these issues, an Energy Efficient Secured Clustered Particle Swarm Optimization (PSO) oriented Data Aggregation Routing Protocol (EESCPSO-DARP) that can provide efficient authentication during data aggregation-based routing is introduced in this paper. Moreover, the proposed protocol enhances the rate of the data transmission by efficient prevention of false data injection and other attacks through node authentication and data encryption. This proposed protocol minimizes the energy usage by minimizing the retransmissions by eliminating the possible redundant transmissions of data during data aggregation-based routing. Moreover, the introduced protocol minimizes both communication and computational overhead through optimal clustering and routing with PSO and provides and efficient routing system. This proposed EESCPSO-DARP protocol has been developed by using the NS3 simulator. The results of this protocol showed improved security, higher packet delivery ratio and enhanced network throughput with reduced energy and delay.

A Framework for Mitigating Gray Hole Attack On Mobile Ad Hoc Networks

posing a significant challenge to network performance and reliability. In a gray hole attack, a malicious node selectively drops packets while forwarding others, leading to increased packet loss and latency. This paper presents a novel Gray Hole Prevention algorithm designed to detect and mitigate the effects of such attacks, thereby enhancing the security and efficiency of MANETs. The proposed algorithm integrates existing techniques, specifically the Secure Detection Prevention and Elimination Gray Hole (SDPEGH) approach, with proactive measures to improve detection accuracy and minimize the risk of blacklisting legitimate nodes. Extensive simulations were conducted using the NS-2 simulation tool, comparing the performance of the proposed algorithm against traditional methods. The results demonstrate a significant improvement in network performance, with the GRAY-HP algorithm achieving a PDR of 92%, compared to 78% for the SDPEGH algorithm, representing an increase of 18%. Additionally, the throughput improved by 25%, reaching 85 kbps, while the energy consumption was reduced by 15%, indicating a more efficient use of resources. The routing overhead was also minimized by 20%, showcasing the algorithm's effectiveness in maintaining network stability. This research contributes to the field of network security by providing a robust solution to gray hole attacks, thereby enhancing the reliability and performance of MANETs. The findings underscore the importance of proactive security measures in dynamic and decentralized environments, paving the way for future advancements in secure communication protocols for mobile networks.

Real-Time Co-Simulation Implementation for Voltage and Frequency Regulation in Standalone AC Microgrid with Communication Network Performance Analysis across Traffic Variations

Effective communication networks are crucial for ensuring reliable and stable operation and control in smart microgrids (MGs). This paper proposes a comprehensive analysis of the interdependence between power and communication networks in the real-time control of a standalone AC microgrid to address this vital need. Thus, the role of communication network design is emphasized in facilitating an effective centralized secondary control to regulate the voltage and frequency of an MG. Consequently, voltage and frequency deviations from the droop-based primary control should be eliminated. This study employs a real-time co-simulation testbed setup that integrates OPAL-RT and network simulator (ns-3), supporting a rigorous evaluation of the interplay between the communication networks and control within the MG. Experiments have been conducted to demonstrate the effectiveness of the designed communication infrastructure in seamlessly enabling real-time data exchange among the primary and secondary control layers. Testing scenarios have been implemented, encompassing low-traffic patterns with minimal load variations and high traffic characterized by more frequent and severe load changes. The experimental results highlight the significant impact of traffic variations on communication network performance. Despite the increase in traffic, the effectiveness and reliability of the designed communication network have been validated, underscoring the vital role of communication in ensuring the resilient and stable operation of cyber–physical standalone AC microgrids.

Escrow-free and efficient dynamic anonymous privacy-preserving batch verifiable authentication scheme for VANETs

To enhance road safety, Vehicular Ad-hoc Networks (VANETs) facilitate the exchange of safety-critical messages between smart vehicles and road traffic authorities. However, VANET’s wireless channels are prone to several attacks, such as replay or modification. Therefore, to protect the links, robust authentication and message integrity mechanisms are required. Previously, several robust authentication schemes have been devised. However, those designs often struggle with complex certificate management, the key escrow problem, and the necessity for secure channels to establish user keys. Additionally, prior methods rely on pseudonyms to ensure user privacy. To implement it, several pseudonyms are stored in the vehicle’s device, which burdens the device. To overcome these limitations, this study introduces an efficient and escrow-free dynamic anonymous authentication scheme tailored for VANETs. By utilizing the paradigm of certificate-based cryptography and fuzzy identity generation, the proposed design eliminates the limitations. Through rigorous security analysis, the proposed design’s effectiveness against various threats is demonstrated. Furthermore, a detailed performance analysis, including computational and communication cost comparisons, showcases the scheme’s feasibility for VANET deployment. An NS-3 simulation further confirms the suitability of the proposed scheme for real-world VANET communication scenarios.

Performance Analysis of Routing Protocols for Urban VANET Based on SUMO and NS2.35

To make the dream of intelligent transportation systems come true, the development of the autonomous cars is considered as a tremendous disruptive innovation in the coming years. Vehicular ad hoc networks (VANETs) are being used as a tool for improving road safety by alarming the drivers about accidents occurred ahead of them or for providing internet access via gateways along the road. Due to highly dynamic nature of nodes in VANETs, designing a routing protocol for VANET is quite challenging compared to other networks environment. Researchers have suggested several routing algorithms for VANETs. Few routing algorithms are based on topology based whereas others have considered position based etc. As no standard scheme is available for choosing a routing protocol in VANETs, this paper gives an insight on how to choose a routing protocol depends on varying condition of traffic such as number of nodes on the roads and maximum speed of nodes. The popular protocols of Topology Based Routings and Position Based Routing have been chosen for analysis on varying traffic environment. All the protocols have been critically tested for different metrics such as packet delivery ratio and average end-to-end delay during the simulation. Simulation is carried out with the help of SUMO traffic simulator and open-source simulation tools NS2.35 network simulator. Simulation result show that Position Based Routing is performing better at low average end-to-end delay than Topology Based Routings, but Position Based Routing has the lowest possible performance in packet delivery ratio than Topology Based Routings.

Antibiotic resistance challenge: evaluating anthraquinones as rifampicin monooxygenase inhibitors through integrated bioinformatics analysis

ObjectiveAntibiotic resistance poses a pressing and crucial global public health challenge, leading to significant clinical and health-related consequences. Substantial evidence highlights the pivotal involvement of rifampicin monooxygenase (RIFMO) in the context of antibiotic resistance. Hence, inhibiting RIFMO could offer potential in the treatment of various infections. Anthraquinones, a group of organic compounds, have shown promise in addressing tuberculosis. This study employed integrated bioinformatics approaches to evaluate the potential inhibitory effects of a selection of anthraquinones on RIFMO. The findings were subsequently compared with those of rifampicin (RIF), serving as a positive control inhibitor.MethodsThe AutoDock 4.0 tool assessed the binding free energy between 21 anthraquinones and the RIFMO catalytic cleft. The ligands were ranked based on the most favorable scores derived from ΔGbinding. The docking analyses for the highest-ranked anthraquinone and RIF underwent a cross-validation process. This validation procedure utilized the SwissDock server and the Schrödinger Maestro docking software. Molecular dynamics simulations were conducted to scrutinize the stability of the backbone atoms in free RIFMO, RIFMO-RIF, and RIFMO complexed with the top-ranked anthraquinone throughout a 100-ns computer simulation. The Discovery Studio Visualizer tool visualized interactions between RIFMO residues and ligands. An evaluation of the pharmacokinetics and toxicity profiles of the tested compounds was also conducted.ResultsFive anthraquinones were indicated with ΔGbinding scores less than − 10 kcal/mol. Hypericin emerged as the most potent RIFMO inhibitor, boasting a ΔGbinding score and inhibition constant value of − 12.11 kcal/mol and 798.99 pM, respectively. The agreement across AutoDock 4.0, SwissDock, and Schrödinger Maestro results highlighted hypericin’s notable binding affinity to the RIFMO catalytic cleft. The RIFMO-hypericin complex achieved stability after a 70-ns computer simulation, exhibiting a root-mean-square deviation of 0.55 nm. Oral bioavailability analysis revealed that all anthraquinones except hypericin, sennidin A, and sennidin B may be suitable for oral administration. Furthermore, the carcinogenicity prediction analysis indicated a favorable safety profile for all examined anthraquinones.ConclusionInhibiting RIFMO, particularly with anthraquinones such as hypericin, holds promise as a potential therapeutic strategy for infectious diseases.

Design and computational analysis of a novel Leptulipin-p28 fusion protein as a multitarget anticancer therapy in breast cancer.

The search for novel therapeutic agents to treat breast cancer has compelled the development of fusion proteins that synergize the functional benefits of different bioactive peptides. Leptulipin, derived from scorpion venom, exhibits antitumor properties. On the other hand, p28, a peptide from the bacterial protein azurin, enhances cell penetration. The current study investigated the design and computational evaluation of a Leptulipin-p28 fusion protein for breast cancer treatment. The amino acid sequences of Leptulipin and p28 were joined via a rigid linker to maintain structural and functional integrity. Secondary and tertiary structure predictions were performed using online servers of GOR-IV and I-TASSER. Physicochemical properties and solubility were analyzed using ProtParam and Protein-Sol. Validation and quality assessment of the fusion protein were confirmed through Rampage and ERRAT2. Finally, the fusion protein was docked with 2 receptors (VEGFR and Cadherin) and docked complexes were simulated on GROMACS. The Leptulipin-p28 fusion protein exhibited a stable structure exhibiting a high quality score of 92 on ERRAT and Ramachandran plot analysis highlighting 76.3% of residues in the favorable region. Docking studies with VEGFR and Cadherin receptors followed by 100ns simulations on GROMACS showed stable complex formation. Molecular dynamics simulations confirmed the stability and robust interaction of the fusion protein-receptor complexes over time. The computational analysis indicates that the Leptulipin-p28 fusion protein holds promise as a multitarget therapeutic agent in breast cancer. The current findings warrant further investigation through in vitro and in vivo studies to validate the current outcomes.

Complexation process and binding parameters of curcumin and short amylose with V7-type helix structure

Pre-formed V7-type short amylose (SA) could interact with curcumin to form inclusion complex (IC) thereby to improve the stability of curcumin. However, the complexation mechanism of V7-type SA and curcumin is not clear, which limit the improvement of inclusion efficiency. To obtain a starch nanocarrier with high loading capacity, the encapsulation process and interaction parameters of V7-type SA-curcumin IC was studied. The analysis results demonstrated that stoichiometric ratio value of the SA-curcumin complex was around 1. V7-type SA performed excellently in the delivery of curcumin attributing to their high loading capacity (over 20 %). It was found that curcumin could enter into the pre-formed helical cavity of SA to form an IC. The conformation change of SA caused the reduction in the interaction ratio in the last 20 ns of simulation. However, SA and curcumin always remained complexation status during the simulation. Hydrogen bonds (H-bonds) and hydrophobic interaction were the most critical acting forces involved in the formation and stability of V7-type SA-curcumin complex. Molecular docking presented that H-bonds interaction between curcumin ligand and V7-type SA chain (O3 at the 25th glucose unit, and O6 at the 17th and 20th glucose units) were found. Furthermore, the hydrophobic interactions were discovered between curcumin ligand and SA chain (18th, 19th, 21st, 22nd and 23rd glucose units). Short abstractTo obtain a nanocarrier with high loading capacity, the interacting mechanism of curcumin and V-type short amylose (SA) was studied. The results demonstrated that curcumin could enter into the pre-formed helical cavity of SA to form an inclusion complex. SA and curcumin always remained complexation status during the simulation. Hydrogen bonding and hydrophobic interaction were the most critical acting forces involved in the formation and stability of V7-type SA-curcumin complex.