Multi-target Interactions Research Articles

Network Pharmacology Analysis Reveals Multi-target Interactions of Phytochemicals in Cardiospermum halicacabum and their Potential in Breast Cancer Therapy

Aims: This present study aims to probe the interrelationships between phytochemical components and drug targets in Cardiospermum halicacabum. Background: Indian traditional medicine, often called Ayurveda, has a rich history of using medicinal plants for various health remedies and treatments. Network pharmacology plays a significant role in understanding the complex interactions between bioactive compounds in herbal medicinal plants and the human body. Objective: Medicinal plants are abundant in bioactive compounds, each possessing unique biological activities. However, certain unexplored biological activities of medicinal plants remain underrepresented in therapeutic studies. This study seeks to explore the connections between phytochemical components and drug targets specifically within Cardiospermum halicacabum. Methods: Metabolites were associated with various targets, and network analysis was conducted to assess the gene-metabolite network using cytoHubba. Genes were clustered to understand their involvement in gene ontology, biological processes, and metabolic pathways. K-means clustering illustrated a network of genes related to breast cancer pathways. Molecular docking analysis was performed for common genes within multiple targets to assess docking scores and interactions. result: Network analysis revealed six key metabolites closely interacting with multiple targets. Antioxidant activity was assessed using the DPPH assay, demonstrating significant effects (inhibition 74.08 ± 0.67%). Cytotoxicity against MCF-7 and MDA-MBA 231 cell lines showed IC50 values of 110.7 µg/mL and 141.2 µg/ml, respectively, indicating potential cytotoxic effects. Results: Network analysis revealed six key metabolites closely interacting with multiple targets. Antioxidant activity was assessed using the DPPH assay, demonstrating significant effects (inhibition 74.08 ± 0.67%). Cytotoxicity against MCF-7 and MDA-MBA 231 cell lines showed IC50 values of 110.7 μg/mL and 141.2 μg/ml, respectively, indicating potential cytotoxic effects. Conclusion: This study highlights the importance of plant metabolites and their interactions with multiple targets through network pharmacology analysis. It suggests the synergistic potential of compounds with multiple targets, providing insights into their therapeutic value, particularly in breast cancer therapy.

Ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry-characterized extract of Aerides odorata Lour alleviates paracetamol-induced hepatotoxicity in animal model evidenced by biochemical, molecular, and computational studies.

Many kinds of orchids have significant health benefits although adequate research on their biological functions is yet to be carried out. This study investigated the paracetamol-induced liver damage-protecting effect of epiphytic Aerides odorata methanol extract (AODE). The protective effects of AODE were studied by analyzing its effect on liver function parameters, messenger RNA (mRNA) expression, and tissue histopathological architecture. The results were confirmed by ligand-receptor interaction of molecular docking and multitarget interaction of network pharmacological analyses. AODE significantly (p < 0.05) minimized the dose-dependent increase in acid phosphatase, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, γ-glutamyl transferase, lactate dehydrogenase, and total bilirubin compared to the reference drug silymarin. Malondialdehyde level decreased, and the antioxidant genes catalase (CAT), superoxide dismutase (SOD), β-actin, paraoxonase-1 (PON1), and phosphofructokinase-1 (PFK-1) were upregulated in AODE-treated paracetamol-intoxicated rats. A total of 376 compounds comprising phenols and flavonoids were identified using ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-qTOF-MS). The online toxicity assessment using SwissADME and admetSAR exhibited drug-like, nontoxic, and potential pharmacological properties. Additionally, in silico analysis showed that isoacteoside, one of the identified compounds, exhibited the best docking score (-11.42) with the liver protein human pituitary adenylate cyclase-1 (Protein Data Bank ID: 3N94). Furthermore, network pharmacology analysis identified the top 10 hub genes, namely AKT1 (protein kinase B), CTNNB1 (catenin beta-1), SRC (proto-oncogene c-Src), TNF (tumor necrosis factor), EGFR (epidermal growth factor receptor), HSP90AA1 (heat shock protein 90α), MAPK3 (mitogen-activated protein kinase 3), STAT3 (signal transducer and activator of transcription 3), CASP3 (caspase protein), and ESR1 (estrogen receptor 1), which are responsible for hepatoprotective activity. The findings demonstrate that AODE could be a novel hepatoprotective target in drug-induced liver damage with a further single compound-based animal study.

Review of Pharmacotherapeutic Targets in Alzheimer's Disease and Its Management Using Traditional Medicinal Plants.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. While there is currently no cure for AD, several pharmacotherapeutic targets and management strategies have been explored. Additionally, traditional medicinal plants have gained attention for their potential role in AD management. Pharmacotherapeutic targets in AD include amyloid-beta (Aβ) aggregation, tau protein hyperphosphorylation, neuroinflammation, oxidative stress, and cholinergic dysfunction. Traditional medicinal plants, such as Ginkgo biloba, Huperzia serrata, Curcuma longa (turmeric), and Panax ginseng, have demonstrated the ability to modulate these targets through their bioactive compounds. Ginkgo biloba, for instance, contains flavonoids and terpenoids that exhibit neuroprotective effects by reducing Aβ deposition and enhancing cerebral blood flow. Huperzia serrata, a natural source of huperzine A, has acetylcholinesterase-inhibiting properties, thus improving cholinergic function. Curcuma longa, enriched with curcumin, exhibits anti-inflammatory and antioxidant effects, potentially mitigating neuroinflammation and oxidative stress. Panax ginseng's ginsenosides have shown neuroprotective and anti-amyloidogenic properties. The investigation of traditional medicinal plants as a complementary approach to AD management offers several advantages, including a lower risk of adverse effects and potential multi-target interactions. Furthermore, the cultural knowledge and utilization of these plants provide a rich source of information for the development of new therapies. However, further research is necessary to elucidate the precise mechanisms of action, standardize preparations, and assess the safety and efficacy of these natural remedies. Integrating traditional medicinal-plant-based therapies with modern pharmacotherapies may hold the key to a more comprehensive and effective approach to AD treatment. This review aims to explore the pharmacotherapeutic targets in AD and assess the potential of traditional medicinal plants in its management.

Mechanisms of Erzhi Pill in Treating Lupus Nephritis Explored by GEO Gene Chips Combined with Network Pharmacology and Molecular Docking

Background: The study focused on exploring Erzhi Pill's molecular mechanism in treating lupus nephritis (LN) for the first time by means of network pharmacology, combined with molecular docking (MD) and GEO database analysis. Materials and Methods: Multiple databases were utilized to select compounds and targets of Erzhi Pill and targets of LN. We built a protein-protein interaction network which was later imported into Cytoscape to screen core regulatory genes. The GEO chip was analyzed to verify the key targets and apply Discovery Studio for MD of those screened effective components with hub targets. The drug-disease intersection targets were performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Results: CASP3 and MMP9 had significant differences by GEO chip analysis. Luteolin and MMP9 have the highest binding affinity through MD. GO and KEGG analysis suggested that Erzhi Pill effect on LN were closely related to cell apoptosis, oxidative stress, and lipid metabolism. Conclusions: Erzhi Pill has been found to treat LN in various ways through multi-component, multi-target interaction, and multi-pathway.

Systemic Convergent Multitarget Interactions of Plant Polyphenols Revealed by Affinity-Based Protein Profiling of Bone Cells Using C-Glucosidic Vescal(ag)in-Bearing Chemoproteomic Probes.

The ellagitannins vescalagin and vescalin, known as actin-dependent inhibitors of osteoclastic bone resorption, were mounted onto chemical probes to explore their interactions with bone cell proteins by means of affinity-based chemoproteomics and bioinformatics. The chemical reactivity of the pyrogallol units of these polyphenols toward oxidation into electrophilic ortho-quinones was exploited using NaIO4 to promote the covalent capture of target proteins, notably those expressed at lower abundance and those interacting with polyphenols at low-to-moderate levels of affinity. Different assays revealed the multitarget nature of both ellagitannins, with 100-370 statistically significant proteins captured by their corresponding probes. A much higher number of proteins were captured from osteoclasts than from osteoblasts. Bioinformatic analyses unveiled a preference for the capture of proteins having phosphorylated ligands and GTPase regulators and enabled the identification of 33 potential target proteins with systemic relevance to osteoclast differentiation and activity, as well as to the regulation of actin dynamics.

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.

Protein-ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multitarget interactions are the first step in finding an effective therapeutic, while undesirable off-target interactions are the first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets and to project novel drugs into a hybrid protein-ligand feature space to identify their likely protein interactions. Using structure-based template matches from PDB, protein pockets are featured by the ligands that bind to their best co-complex template matches. The simplicity and interpretability of this approach provide a granular characterization of the human proteome at the protein-pocket level instead of the traditional protein-level characterization by family, function, or pathway. We demonstrate the power of this featurization method by clustering a subset of the human proteome and evaluating the predicted cluster associations of over 7000 compounds.

Revealing the Preventable Effects of Fu-Zheng-Qu-Xie Decoction against Recurrence and Metastasis of Postoperative Early-Stage Lung Adenocarcinoma Based on Network Pharmacology Coupled with Metabolomics Analysis.

Fu-Zheng-Qu-Xie (FZQX) decoction is a traditional Chinese herbal prescription for the treatment of lung cancer and exerts proapoptotic and immunomodulatory effects. It has been clinically suggested to be effective in improving the survival of postoperative early-stage lung adenocarcinoma (LUAD), but the mechanism remains unclear. In this study, we used network pharmacology coupled with metabolomics approaches to explore the pharmacological action and effective mechanism of FZQX against the recurrence and metastasis of postoperative early-stage LUAD. Network pharmacology analysis showed that FZQX could prevent the recurrence and metastasis of postoperative early-stage LUAD by regulating a series of targets involving vascular endothelial growth factor receptor 2, estrogen receptor 1, sarcoma gene, epidermal growth factor receptor, and protein kinase B and by influencing the Ras, PI3K-Akt, and mitogen-activated protein kinase signaling pathways. In liquid chromatography-mass spectrometry analysis, 11 differentially expressed metabolites, including PA(12:0/18:4(6Z,9Z,12Z,15Z)), PC(16:0/0:0)[U], LysoPC(18:1(11Z)), and LysoPC(18:0), were discovered in the FZQX-treated group compared to those in the model group before treatment or normal group. They were enriched in cancer metabolism-related signaling pathways such as central carbon metabolism in cancer, choline metabolism, and glycerol phospholipid metabolism. Collectively, our results suggest that the multicomponent and multitarget interaction network of FZQX inhibits the recurrence and metastasis of postoperative early-stage LUAD by activating the receptor signal transduction pathway to inhibit proliferation, induce cell apoptosis, inhibit aerobic glycolysis, and reprogram tumor lipid metabolism.

Sour Tamarind Is More Antihypertensive than the Sweeter One, as Evidenced by In Vivo Biochemical Indexes, Ligand-Protein Interactions, Multitarget Interactions, and Molecular Dynamic Simulation.

This research investigated the antihypertensive effects of tamarind products and compared their potentials based on an animal model's data verified by molecular docking, multitarget interactions, and dynamic simulation assays. GC-MS-characterized tamarind products were administered to cholesterol-induced hypertensive albino rat models. The two-week-intervened animals were dissected to collect their serum and organs and respectively subjected to analyses of their hypertension-linked markers and tissue architectures. The lead biometabolites of tamarinds interacted with eight target receptors in the molecular docking and dynamic simulation studies and with multitarget in the network pharmacological analyses. The results show that the serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), C-reactive protein (CRP), troponin I, and lipid profiles were maximally reinstated by the phenolic-enriched ripened sour tamarind extract compared to the sweet one, but the seed extracts had a smaller influence. Among the tamarind's biometabolites, ϒ-sitosterol was found to be the best ligand to interact with the guanylate cyclase receptor, displaying the best drug-likeliness with the highest binding energy, -9.3 Kcal. A multitargeted interaction-based degree algorithm and a phylogenetic tree of pathways showed that the NR3C1, REN, PPARG, and CYP11B1 hub genes were consistently modulated by ϒ-sitosterol to reduce hypertension and related risk factors. The dynamic simulation study showed that the P-RMSD values of ϒ-sitosterol-guanylate cyclase were stable between 75.00 and 100.00 ns at the binding pocket. The findings demonstrate that ripened sour tamarind extract may be a prospective antihypertensive nutraceutical or supplement target affirmed through advanced preclinical and clinical studies.

The Antimicrobial Peptide Octopromycin Suppresses Biofilm Formation and Quorum Sensing in Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic bacterial pathogen that causes severe infections in immunocompromised individuals. A. baumannii forms biofilm and produces extracellular matrix, which supports bacteria to survive under harsh conditions and be resistant to antibacterial treatments. In the present study, we investigated the biofilm and quorum-sensing inhibitory effects of antimicrobial peptide, octopromycin in A. baumannii. Field emission-scanning electron microscopy results clearly showed significantly reduced biofilm mass and caused a collapse in biofilm architecture at the minimum inhibitory concentration (50 µg/mL) and minimum bactericidal concentration (200 µg/mL) of octopromycin. Antibiotic-resistant persister cells of A. baumannii were successfully killed by octopromycin treatment, and it inhibited violacein production in Chromobacterium violaceum in a concentration-dependent manner. Octopromycin also inhibited alginate production, surface movements (swarming and swimming), and twitching motility of A. baumannnii, confirming its anti-quorum-sensing activity. Multiple metabolic pathways, two-component regulation systems, quorum-sensing, and antibiotic synthesis-related pathways in A. baumannii biofilms were strongly affected by octopromycin treatment. The collective findings indicate that the antibacterial peptide octopromycin may control A. baumannii biofilms through multi-target interactions. Octopromycin could be a desirable therapeutic option for the prevention and control of A. baumannii infections.

TCMFP: a novel herbal formula prediction method based on network target's score integrated with semi-supervised learning genetic algorithms.

Traditional Chinese medicine (TCM) has accumulated thousands years of knowledge in herbal therapy, but the use of herbal formulas is still characterized by reliance on personal experience. Due to the complex mechanism of herbal actions, it is challenging to discover effective herbal formulas for diseases by integrating the traditional experiences and modern pharmacological mechanisms of multi-target interactions. In this study, we propose a herbal formula prediction approach (TCMFP) combined therapy experience of TCM, artificial intelligence and network science algorithms to screen optimal herbal formula for diseases efficiently, which integrates a herb score (Hscore) based on the importance of network targets, a pair score (Pscore) based on empirical learning and herbal formula predictive score (FmapScore) based on intelligent optimization and genetic algorithm. The validity of Hscore, Pscore and FmapScore was verified by functional similarity and network topological evaluation. Moreover, TCMFP was used successfully to generate herbal formulae for three diseases, i.e. the Alzheimer's disease, asthma and atherosclerosis. Functional enrichment and network analysis indicates the efficacy of targets for the predicted optimal herbal formula. The proposed TCMFP may provides a new strategy for the optimization of herbal formula, TCM herbs therapy and drug development.

Entomopathogenic Nematode Compatibility with Vineyard Fungicides.

Vineyards, covering over seven million hectares worldwide, hold significant socio-cultural importance. Traditionally reliant on conventional practices and agrochemicals, this agroecosystem faces environmental challenges, including soil and water pollution. Sustainable viticulture, driven by eco-friendly practices and cost reduction, has gained prominence, underlining the importance of biological control agents such as entomopathogenic nematodes (EPNs). EPNs naturally occurr in vineyard soils and play a crucial role in controlling pest damage. Ensuring compatibility between EPNs and the commonly used vineyard fungicides is critical, as these applications constitute the predominant pest-management practice during the productive grapevine cycle. This study assessed the impact of authorized grapevine fungicides on EPNs, focusing on the survival of populations and sublethal effects on their virulence. We investigated the compatibility of two EPN populations (Steinernema feltiae 107 and S. carpocapsae 'All') with three organic production-approved products (Bacillus pumilus, sulfur, and copper oxychloride) and two synthetic chemicals (Trifloxystrobin and Mancozeb). Our findings revealed that the viability of S. feltiae 107 was reduced when exposed to sulfur and copper oxychloride, and its virulence was affected by copper oxychloride and Mancozeb, although only two days after exposure and with no significant differences for larval mortality at five days. In contrast, S. carpocapsae 'All' exhibited full compatibility with all five fungicides, with no impact on its viability or virulence. Consequently, our results suggested that the evaluated fungicides could be co-applied on both EPN populations if they were employed on the same day. However, further research on multi-target interactions is needed to ensure the successful implementation of this kind of co-application.

Multi-targeted molecular docking, pharmacokinetics, and drug-likeness evaluation of coumarin based compounds targeting proteins involved in development of COVID-19

COVID-19 is a progressing pandemic of coronavirus disease-2019, which had drowned the whole world in a deep sorrow sea. Uncountable deaths were extending the list of deaths every single day. The present research was aimed to study the multi-target interaction of coumarins against COVID-19 using molecular docking analysis. The structure of coumarin compounds was checked for ADME and Lipinski rule of five by using SwissADME, an online tool. SARS-CoV-2 proteins such as RdRp, PLpro, Mpro and spike protein were collected from the Protein Data Bank. The molecular docking study was performed in the PyRx tool, and the molecular interactions were visualised by Discovery Studio Visualizer. All the coumarin compounds used in the study were obeyed Lipinski’s rule of 5 without any violations. All the three designed derivatives of phenprocoumon, hymecromone, and psoralen were showed high binding affinity and prominent interactions with the drug target. The presence of –OH groups in the compound, His41, a catalytic dyad in Mpro, number of and the distance of hydrogen bond interactions with SARS-CoV-2 targets was accountable for the high binding attractions. The modified drug structures possess better binding efficacy towards at least three targets compared to their parent compounds. Further, molecular dynamic studies can be suggested to find the ligand–protein complex stability. The present study outcome reveals that the designed coumarins can be synthesised and examined as a potent inhibitory drug of SARS-CoV-2.

EdgeXAR: A 6-DoF Camera Multi-target Interaction Framework for MAR with User-friendly Latency Compensation

The computational capabilities of recent mobile devices enable the processing of natural features for Augmented Reality (AR), but the scalability is still limited by the devices' computation power and available resources. In this paper, we propose EdgeXAR, a mobile AR framework that utilizes the advantages of edge computing through task offloading to support flexible camera-based AR interaction. We propose a hybrid tracking system for mobile devices that provides lightweight tracking with 6 Degrees of Freedom and hides the offloading latency from users' perception. A practical, reliable and unreliable communication mechanism is used to achieve fast response and consistency of crucial information. We also propose a multi-object image retrieval pipeline that executes fast and accurate image recognition tasks on the cloud and edge servers. Extensive experiments are carried out to evaluate the performance of EdgeXAR by building mobile AR apps upon it. Regarding the Quality of Experience (QoE), the mobile AR apps powered by EdgeXAR framework run on average at the speed of 30 frames per second with precise tracking of only 1-2 pixel errors and accurate image recognition of at least 97% accuracy. As compared to Vuforia, one of the leading commercial AR frameworks, EdgeXAR transmits 87% less data while providing a stable 30FPS performance and reducing the offloading latency by 50 to 70% depending on the transmission medium. Our work facilitates the large-scale deployment of AR as the next generation of ubiquitous interfaces.

Multi target interactions of essential oil nanoemulsion of Cinnamomum travancoricum against diabetes mellitus via in vitro, in vivo and in silico approaches

This study reports antidiabetic activity of leaf essential oil (EO) of Cinnamomum travancoricum from the Western Ghats, India via in vitro , in vivo and in silico methods. EO was characterized by GC-MS and GC-FID. Essential oil nanoemulsions (EN) were prepared and characterized. Antidiabetic potential was evaluated through in vitro assays namely, α-amylase and α-glucosidase inhibition, glucose uptake and insulin secretion assays. In vivo study was conducted on STZ-induced diabetic Wistar rats. Molecular docking was conducted to find the lead antidiabetic compounds. Of the 42 compounds identified in the EO, α-phellandrene (5.9%), β-phellandrene (12.6%), linalool (23.6%), safrole (6.8%) and shyobunol (5.1%) were major constituents. Of the two ENs formulated, 1:2 ratio (EO to surfactants) was better in zeta size (51.4 nm) and potential (−30.9). In vitro results were impressive. EN lowered elevated blood glucose level to normal (p < 0.01) and improved the insulin secretion (p < 0.01) in diabetic rats. Further, serum AST, ALT, ALP, triglyceride and pancreatic β-cell damage were seen reduced (p < 0.05). Molecular docking studies showed minor constituents of EO, namely, δ-cadinene, elemol, spathulenol and α-copaen-11-ol playing active role in antidiabetic activity through α-amylase, α-glucosidase, insulin receptor, and insulin secretion proteins.

Research on the Prediction of the Operational Risk Field of Intelligent Vehicles Based on Dual Multiline LiDAR

To effectively evaluate the risk situation between intelligent vehicles and surrounding traffic participants in complex scenes, a complex traffic environment perception technology based on dual multiline light detection and ranging (LiDAR) is proposed in this work. The vehicle motion state is predicted by fusing the multiview characteristics of point cloud timing and multitarget interaction information, and the risk assessment model is constructed via artificial potential field theory. The real-time point cloud information is used to obtain the time-sequence bird’s-eye view and range image. The improved VGG19 network model is used to extract the time-sequence high-level abstract combined features in the multiview scene. The constructed time-sequence feature vector is used as the input data of the attention mechanism, and the attention-bidirectional long short-term memory (Attention-BiLSTM) model is used for training to form the desired input-output mapping relationship. The motion state of the target vehicle can therefore be updated, and the static and dynamic risk fields of traffic participants surrounding the vehicle can be established based on artificial potential field theory, thereby allowing for the evaluation of the operational risk of the intelligent vehicle. The results of experiments demonstrate that the prediction effect of the target vehicle state parameters via the use of the proposed model is better than that of other compared models, and the prediction effect of the risk field of intelligent vehicle operation based on the multiview point cloud features and vehicle interaction information is good.

Clinical Efficacy Evaluation and Potential Mechanism of Zhishe Tongluo Capsule in the Treatment of Cerebral Infarction by Meta-Analysis Associated with Network Pharmacology.

Objective By integrating meta-analysis and network pharmacology strategy, the clinical efficacy of Zhishe Tongluo capsule in the treatment of cerebral infarction was evaluated, and the intervention mechanism was preliminary explored. Methods Through meta-analysis, the Chinese and English literature of the randomized controlled trial (RCT) of Zhishe Tongluo capsule in the treatment of cerebral infarction was comprehensively searched. Based on the standard of Na Pai, the quantitative literature was determined and the Review Manager data were statistically analyzed. Results A total of 10 RCTs literatures were included. These literatures included a total of 1278 subjects, of which 670 were in the treatment group and 608 were in the control group. In terms of indicators of efficiency and adverse reaction rate, the treatment group was better than the control group. There was a statistical difference (P < 0.05); a total of 559 chemical constituents and 2306 potential targets were obtained from the online database. Of these, 201 components, 145 targets, and 185 pathways were closely related to cerebral infarction. Conclusions The available evidence indicates that the addition of Zhishe Tongluo capsule to the conventional treatment of Western medicine can improve the clinical efficacy of cerebral infarction and has some advantages in regulating blood lipids and hemorheology, but the overall evidence level is low, which still needs to be further supported by large-scale and multicenter RCTs; intervention of brain infarction by Zhishe Tongluo capsule is a comprehensive result of multicomponent and multi-target interactions. On the basis of the combined meta-analysis and network pharmacology in scientific attempts, it also provides a reference for the clinical evaluation of other drugs and mechanism research.

Vehicle Motion State Prediction Method Integrating Point Cloud Time Series Multiview Features and Multitarget Interactive Information

A vehicle motion state prediction algorithm integrating point cloud timing multiview features and multitarget interaction information is proposed in this work to effectively predict the motion states of traffic participants around intelligent vehicles in complex scenes. The algorithm analyzes the characteristics of object motion that are affected by the surrounding environment and the interaction of nearby objects and is based on the complex traffic environment perception dual multiline light detection and ranging (LiDAR) technology. The time sequence aerial view map and time sequence front view depth map are obtained using real-time point cloud information perceived by the LiDAR. Time sequence high-level abstract combination features in the multiview scene are then extracted by an improved VGG19 network model and are fused with the potential spatiotemporal interaction of the multitarget operation state data extraction features detected by the laser radar by using a one-dimensional convolution neural network. A temporal feature vector is constructed as the input data of the bidirectional long-term and short-term memory (BiLSTM) network, and the desired input-output mapping relationship is trained to predict the motion state of traffic participants. According to the test results, the proposed BiLSTM model based on point cloud multiview and vehicle interaction information is better than other methods in predicting the state of target vehicles. The results can provide support for the research to evaluate the risk of intelligent vehicle operation environment.

In vitro Antifungal Activity of a Novel Antimicrobial Peptide AMP-17 Against Planktonic Cells and Biofilms of Cryptococcus neoformans.

BackgroundCryptococcus neoformans is a common human fungal pathogen in immunocompromised people, as well as a prevalent cause of meningitis in HIV-infected individuals. With the emergence of clinical fungal resistance and the shortage of antifungal drugs, it is urgent to discover novel antifungal agents. AMP-17, a novel antimicrobial peptide from Musca domestica, has antifungal activity against C. neoformans. However, its antifungal and anti-biofilm activities remain unclear. Thus, this study aimed to evaluate the antifungal activity of AMP-17 against planktonic cells and biofilms of C. neoformans.MethodsThe minimum inhibitory concentration (MIC), the biofilm inhibitory and eradicating concentration (BIC and BEC) were determined by the broth microdilution assay or the 2, 3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) reduction assay, respectively. The inhibitory and killing activities of AMP-17 against C. neoformans were investigated through the time-inhibition/killing kinetic curves. The potential antifungal mechanism of AMP-17 was detected by flow cytometry, scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). The efficiency of AMP-17 against biofilm formation or preformed biofilm was evaluated by crystal violet staining and XTT reduction assays. The morphology of pre-biofilms was tested by optical microscopy (OM) and CLSM.ResultsAMP-17 exhibited in vitro antifungal activity against C. neoformans planktonic cells and biofilms, with MICs of 4~16 μg/ml, BIC80 and BEC80 of 16~32 μg/ml, 64~128 μg/ml, respectively. In addition, the 2× and 4× MIC of AMP-17 exhibited similar inhibition levels compared to the 2× and 4× MIC of the clinical drugs FLC and AMB in C. neoformans growth. Moreover, the time-kill results showed that AMP-17 (8× MIC) did not significantly eliminate colony forming units (CFU) after 6 h of treatment; however, there was 2.9-log reduction in CFU of C. neoformans. Furthermore, increasing of the permeability of the fungal cell membrane was observed with the treatment of AMP-17, since the vast change as fungal leakage and cell membrane disruption. However, the DNA binding assay of AMP-17 indicated that the peptide did not target DNA. Besides, AMP-17 was superior in inhibiting and eradicating biofilms of C. neoformans compared with FLC.ConclusionAMP-17 exhibited potential in vitro antifungal activity against the planktonic cells and biofilms of C. neoformans, and it may disrupt fungal cell membranes through multi-target interactions, which provides a promising therapeutic strategy and experimental basis for Cryptococcus-associated infections.

Phenolic-protein interactions in foods and post ingestion: Switches empowering health outcomes

Phenolic compounds are secondary metabolites with wide biological activities, and their biological activity is inseparable from their interactions with proteins. Phenolic-protein interactions will occur at the moment they are mixed, and this interaction will continue during food processing, handling, ingestion, digestion, metabolism and bioutilization, leading to a profound impact on the structure and properties of phenols and proteins. This review summarizes current knowledge of the contributions of phenolic-protein interactions to the bioactivities and functional mechanism of phenolic-containing foods. We firstly provide a comprehensive review of the interactions between phenolic ingredients and dietary proteins, and the multi-step interactions between ingested phenolics or derived phenolic products and functional proteins (like enzymes, transporters, receptors and transcription factors (TFs)) inside the human body, along with the involved intermolecular forces. In addition, we have proposed the use of molecular docking for predicting such interactions, and demonstrated some docking results of dietary phenolics (or their derived metabolites) with human TFs. The phenolic-protein interactions in foods and post ingestion may function as multi-switches empowering health outcomes. This review asserts the need for increasing the knowledge of the interactions between the ingested phenolics or their derived products and all the protein biomolecules inside the human body. • Phenolics and proteins may interact before and after ingestion. • Interactions of phenolic with enzyme, transporter, receptor and transcription factor. • Interactions of phenolics with functional proteins in vivo promote human health. • Phenolics multi-target interaction with proteins resulted in synergistic health effect.

An Integrative Metabolomic and Network Pharmacology Study Revealing the Regulating Properties of Xihuang Pill That Improves Anlotinib Effects in Lung Cancer

Lung cancer ranks as a leading cause of death. Although targeted therapies usually trigger profound initial patient responses, these effects are transient due to drug resistance and severe side effects. Xihuang Pill (XHW) is a popular Chinese medicine formula that might benefit cancer patients when used as a complementary therapy. However, its underlying mechanism when combined with anticancer drugs is not clearly understood. Here, we used an integrated strategy to reveal the regulatory properties of XHW in increasing the antitumor activity of anlotinib in lung cancer. We evaluated the anti-lung cancer effect of XHW combined with anlotinib in mice bearing Lewis lung carcinoma (LLC). We applied untargeted metabolomics to identify the differences metabolism and found that XHW improved the effects of anlotinib on lung cancer. The components and targets related to the effects of XHW treatment on lung cancer were obtained through network pharmacology. Then, by integrating the biologically active components of XHW and anlotinib as well as the treatment-responsive metabolites and their related targets, an interaction network was constructed to evaluate the combination therapy. Finally, important protein candidates for this response were verified by immunohistochemistry of tumor tissues. The results showed that XHW significantly improved the inhibitory effect of anlotinib on tumor growth in LLC-bearing mice. Additionally, 12 differentially-abundant metabolites were identified by untargeted metabolomics in the XHW/anlotinib group compared with the XHW or anlotinib groups, and they were mainly enriched in fatty acid metabolism, lipid metabolism and amino acid metabolism pathways. Anlotinib, 23 components in Shexiang, 2 components in Niuhuang, 30 components in Ruxiang and 60 components in Moyao work together to act on 30 targets to regulate hexadecanoic acid (also named palmitic acid), linoleic acid, lactosylceramide, adrenaline, arachidonic acid and lysoPC(18:1(9Z)). The results of immunohistochemistry showed that XHW combined with anlotinib reduced the expression of PDGFRA in tumors. Overall, the key metabolites of XHW that enhances the efficacy of anlotinib were regulated by a multicomponent and multitarget interaction network. Our results suggested that anlotinib combined with XHW may be a promising strategy for the treatment of lung cancer.