Sistemas Computacionais para Auxílio na Cicatrização de Feridas: Revisão de Escopo / Computer Systems to Aid in Wound Healing: Scope Review / Sistemas Informáticos para Ayudar en la Cicatrización de Heridas: Revisión del Alcance

Objetivo:Investigar estudos que apresentem sistemas computacionais de auxílio à cicatrização de feridas e quais sistemas se referem ao uso de laser de baixa intensidade. Método: Revisão de escopo que visou responder à questão de pesquisa: Quais sistemas computacionais auxiliam na cicatrização de feridas? Uma subquestão foi: quais sistemas computacionais se referem ao uso do laser de baixa intensidade? Resultados: A partir da busca, aplicando os critérios de elegibilidade, 49 artigos compuseram a amostra final. Os sistemas apresentaram várias finalidades de apoio à cicatrização de feridas, em que a maioria apresentou como usuário do sistema o profissional de saúde, sendo a medicina a área profissional mais mencionada, embora a enfermagem esteja envolvida com o manejo do cuidado às pessoas com feridas. Foi relatada com frequência a inovação na assistência a partir do uso do sistema computacional, o que demonstra a importância desse tipo de ferramenta para a prática clínica. Verificou-se com frequência o uso de plataforma mobile, como tendência da atualidade. Conclusão: Os sistemas computacionais têm sido utilizados como ferramentas para apoiar pacientes e principalmente profissionais na cicatrização de feridas. Quanto ao laser de baixa intensidade, houve escassez de sistemas computacionais com essa finalidade, com apenas um estudo.

Objective:To investigate studies that present computational systems to aid healing and systems which refer to the use of low-level laser. Method: Scope review that aimed to answer the question: Which computer systems help in wound healing? A subquestion was: Which of the computer systems refer to the use of low-level laser? Results: From the search, applying the eligibility criteria, 49 articles made up the final sample. The systems served multiple purposes in support of wound healing; the majority presented the health professional as a user of the system; medicine was the most mentioned professional area despite nursing being involved in the management of care for people with wounds. Innovation in care using the computer system was frequently reported, demonstrating the importance of this type of tool for clinical practice. There was a high frequency of the mobile platform, showing that this is a current trend. Conclusion: Computer systems have been used as tools to support patients and especially professionals in wound healing. Regarding the systems aimed at the low intensity laser, there was a shortage of computer systems for this purpose, with a study.

Objetivo:Investigar estudios que presenten sistemas computacionales de ayuda a la cicatrización y sistemas que se refieran al uso de láser de bajo nivel. Método: Revisión de alcance que tuvo como objetivo responder a la pregunta: ¿Qué sistemas informáticos ayudan en la cicatrización de heridas? Una subpregunta fue: ¿Cuál de los sistemas informáticos se refieren al uso de láser de bajo nivel? Resultados: A partir de la búsqueda, aplicando los criterios de elegibilidad, 49 artículos conformaron la muestra final. Los sistemas sirvieron para múltiples propósitos en apoyo de la cicatrización de heridas; la mayoría presentó al profesional de la salud como usuario del sistema; la medicina fue el área profesional más mencionadas, a pesar de que la enfermería está involucrada en la gestión del cuidado de las personas con heridas. La innovación en la atención basada en el uso del sistema informático fue relatada con frecuencia, demostrando la importancia de este tipo de herramienta para la práctica clínica. Hubo una alta frecuencia de la plataforma móvil, lo que demuestra que esta es una tendencia actual. Conclusión: Los sistemas informáticos se han utilizado como herramientas de apoyo a los pacientes y especialmente a los profesionales en la cicatrización de heridas. En cuanto a los sistemas dirigidos al láser de baja intensidad, hubo escasez de sistemas informáticos para este fin, con un estudio.

Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence.

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

Systems pharmacogenomics identifies novel targets and clinically actionable therapeutics for medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is the most common malignant paediatric brain tumour and a leading cause of cancer-related mortality and morbidity. Existing treatment protocols are aggressive in nature resulting in significant neurological, intellectual and physical disabilities for the children undergoing treatment. Thus, there is an urgent need for improved, targeted therapies that minimize these harmful side effects. METHODS: We identified candidate drugs for MB using a network-based systems-pharmacogenomics approach: based on results from a functional genomics screen, we identified a network of interactions implicated in human MB growth regulation. We then integrated drugs and their known mechanisms of action, along with gene expression data from a large collection of medulloblastoma patients to identify drugs with potential to treat MB. RESULTS: Our analyses identified drugs targeting CDK4, CDK6 and AURKA as strong candidates for MB; all of these genes are well validated as drug targets in other tumour types. We also identified non-WNT MB as a novel indication for drugs targeting TUBB, CAD, SNRPA, SLC1A5, PTPRS, P4HB and CHEK2. Based upon these analyses, we subsequently demonstrated that one of these drugs, the new microtubule stabilizing agent, ixabepilone, blocked tumour growth in vivo in mice bearing patient-derived xenograft tumours of the Sonic Hedgehog and Group 3 subtype, providing the first demonstration of its efficacy in MB. CONCLUSIONS: Our findings confirm that this data-driven systems pharmacogenomics strategy is a powerful approach for the discovery and validation of novel therapeutic candidates relevant to MB treatment, and along with data validating ixabepilone in PDX models of the two most aggressive subtypes of medulloblastoma, we present the network analysis framework as a resource for the field.

Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology.

Highly prevalent respiratory diseases such as asthma and allergy remain a pressing health challenge. Currently, there is an unmet need for precise diagnostic tools capable of predicting the great heterogeneity of these illnesses. In a previous study of 94 asthma/respiratory allergy biomarker candidates, we defined a group of potential biomarkers to distinguish clinical phenotypes (i.e. nonallergic asthma, allergic asthma, respiratory allergy without asthma) and disease severity. Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. With this approach, we aim to prioritize the most relevant biomarkers according to their specificity and mechanistic implication with molecular motifs of the diseases. The Therapeutic Performance Mapping System (Anaxomics' TPMS technology) was used to generate one mathematical model per disease: allergic asthma (AA), non-allergic asthma (NA), and respiratory allergy (RA), defining specific molecular motifs for each. The relationship of our molecular biomarker candidates and each disease was analyzed by artificial neural networks (ANNs) scores. These analyses prioritized molecular biomarkers specific to the diseases and to particular molecular motifs. As a first step, molecular characterization of the pathophysiological processes of AA defined 16 molecular motifs: 2 specific for AA, 2 shared with RA, and 12 shared with NA. Mechanistic analysis showed 17 proteins that were strongly related to AA. Eleven proteins were associated with RA and 16 proteins with NA. Specificity analysis showed that 12 proteins were specific to AA, 7 were specific to RA, and 2 to NA. Finally, a triggering analysis revealed a relevant role for AKT1, STAT1, and MAPK13 in all three conditions and for TLR4 in asthmatic diseases (AA and NA). In conclusion, this study has enabled us to prioritize biomarkers depending on the functionality associated with each disease and with specific molecular motifs, which could improve the definition and usefulness of new molecular biomarkers.

Behavioral fingerprints predict insecticide and anthelmintic mode of action.

Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high-throughput imaging and quantitative phenotyping to measure Caenorhabditis elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode-of-action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode-of-action discovery in invertebrate-targeting compound development and help to refine mode-of-action categories.

A Systems Biology Approach Identifies B Cell Maturation Antigen (BCMA) as a Biomarker Reflecting Oral Vaccine Induced IgA Antibody Responses in Humans.

Vaccines against enteric diseases could improve global health. Despite this, only a few oral vaccines are currently available for human use. One way to facilitate such vaccine development could be to identify a practical and relatively low cost biomarker assay to assess oral vaccine induced primary and memory IgA immune responses in humans. Such an IgA biomarker assay could complement antigen-specific immune response measurements, enabling more oral vaccine candidates to be tested, whilst also reducing the work and costs associated with early oral vaccine development. With this in mind, we take a holistic systems biology approach to compare the transcriptional signatures of peripheral blood mononuclear cells isolated from volunteers, who following two oral priming doses with the oral cholera vaccine Dukoral®, had either strong or no vaccine specific IgA responses. Using this bioinformatical method, we identify TNFRSF17, a gene encoding the B cell maturation antigen (BCMA), as a candidate biomarker of oral vaccine induced IgA immune responses. We then assess the ability of BCMA to reflect oral vaccine induced primary and memory IgA responses using an ELISA BCMA assay on a larger number of samples collected in clinical trials with Dukoral® and the oral enterotoxigenic Escherichia coli vaccine candidate ETVAX. We find significant correlations between levels of BCMA and vaccine antigen-specific IgA in antibodies in lymphocyte secretion (ALS) specimens, as well as with proportions of circulating plasmablasts detected by flow cytometry. Importantly, our results suggest that levels of BCMA detected early after primary mucosal vaccination may be a biomarker for induction of long-lived vaccine specific memory B cell responses, which are otherwise difficult to measure in clinical vaccine trials. In addition, we find that ALS-BCMA responses in individuals vaccinated with ETVAX plus the adjuvant double mutant heat-labile toxin (dmLT) are significantly higher than in subjects given ETVAX only. We therefore propose that as ALS-BCMA responses may reflect the total vaccine induced IgA responses to oral vaccination, this BCMA ELISA assay could also be used to estimate the total adjuvant effect on vaccine induced-antibody responses, independently of antigen specificity, further supporting the usefulness of the assay.

Mapping drug-target interactions and synergy in multi-molecular therapeutics for pressure-overload cardiac hypertrophy.

Advancements in systems biology have resulted in the development of network pharmacology, leading to a paradigm shift from "one-target, one-drug" to "target-network, multi-component therapeutics". We employ a chimeric approach involving in-vivo assays, gene expression analysis, cheminformatics, and network biology to deduce the regulatory actions of a multi-constituent Ayurvedic concoction, Amalaki Rasayana (AR) in animal models for its effect in pressure-overload cardiac hypertrophy. The proteomics analysis of in-vivo assays for Aorta Constricted and Biologically Aged rat models identify proteins expressed under each condition. Network analysis mapping protein-protein interactions and synergistic actions of AR using multi-component networks reveal drug targets such as ACADM, COX4I1, COX6B1, HBB, MYH14, and SLC25A4, as potential pharmacological co-targets for cardiac hypertrophy. Further, five out of eighteen AR constituents potentially target these proteins. We propose a distinct prospective strategy for the discovery of network pharmacological therapies and repositioning of existing drug molecules for treating pressure-overload cardiac hypertrophy.

Systems Pharmacology-Based Identification of Mechanisms of Action of Bolbostemma paniculatum for the Treatment of Hepatocellular Carcinoma.

BACKGROUND Traditional Chinese medicine has widely used Bolbostemma paniculatum to treat diseases, including cancer, but its underlying mechanisms remain unclear. The present study aimed to elucidate the potential pharmacological mechanisms of "Tu Bei Mu" (TBM), the Chinese name for Bolbostemmatis Rhizoma, the dry tuber of B. paniculatum, for the treatment of hepatocellular carcinoma (HCC). MATERIAL AND METHODS The active components and putative therapeutic targets of TBM were explored using SwissTargetPrediction, Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and Search Tool for Interactions of Chemicals (STITCH). The HCC-related target database was built using DrugBank, DisGeNet, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). A protein-protein interaction network of the common targets was constructed, based on the matches between TBM potential targets and HCC-related targets, using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the cluster networks were used to elucidate the biological functions of TBM. RESULTS Pharmacological network diagrams of the TBM compound-target network and HCC-related target network were successfully constructed. A total of 22 active components, 191 predicted biological targets of TBM, and 3775 HCC-related targets were identified. Through construction of an HCC-related target database and a protein-protein interaction network of the common targets, TBM was predicted to be effective in treating HCC mainly through the PI3K-Akt, HIF-1, p53, and PPAR signaling pathways. CONCLUSIONS The PI3K/Akt, HIF1, p53, and PPAR pathways may play vital roles in TBM treatment of HCC. Also, the potential anti-cancer effect of TBM on HCC appears to stem from the synergetic effect of multiple targets and mechanisms.

Identification of potential bioactive compounds and mechanisms of GegenQinlian decoction on improving insulin resistance in adipose, liver, and muscle tissue by integrating system pharmacology and bioinformatics analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: GegenQinlian Decoction (GQD), a classical formula in traditional Chinese medicine, is widely used in the treatment of diabetes. While studies have demonstrated that GQD is an efficacious treatment for insulin resistance (IR) in type 2 diabetes mellitus (T2DM), the potential bioactive compounds and mechanisms remain unclear. AIM OF THE STUDY: To further investigate the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue using an integrated strategy of system pharmacology and bioinformatics analysis. MATERIALS AND METHODS: We screened the candidate compounds and targets of GQD and identified IR-associated differentially expressed genes (DEGs) of adipose, liver, and muscle tissue, respectively. Then the intersecting target genes between candidate targets and DEGs were used for "GQD-compounds-targets-tissue" network construction in each type of tissue. The top 10 bioactive compounds acting on each type of tissue were intersected and consequently identified as potential bioactive compounds of GQD. Furthermore, pathway enrichment, protein-protein interaction (PPI) network construction, and hub target identification were performed based on the targets of GQD and the targets of quercetin in each type of tissue, respectively. Finally, to further confirm the role of quercetin, we intersected the hub targets of quercetin and the hub targets of GQD, and the pathways were intersected as well. RESULTS: 132 compounds and 119 potential targets of these compounds were obtained. 1,765, 3,206, and 3594 DEGs were identified between IR and insulin sensitivity (IS) tissue in adipose, liver, and muscle, respectively. There were 21, 23, 45 targets and 103, 73, 123 compounds in the "GQD-compounds-targets-tissue" network of adipose, liver, and muscle tissue, respectively. Then compounds such as quercetin, kaempferol, baicalein, wogonin, isorhamnetin, beta-sitosterol and licochalcone A, were identified as the potential bioactive compounds of GQD, and quercetin had the highest degree among the compounds. Moreover, based on the targets of GQD, hub targets like PPARG, RELA, EGFR, CASP3, VEGFA, AR, ESR1 and CCND1, and signaling pathways such as insulin signaling pathway, endocrine resistance, TNF signaling pathway, PI3K-Akt signaling pathway, AMPK signaling pathway, MAPK signaling pathway, NF-κB signaling pathway, HIF-1 signaling pathway, apoptosis, and VEGF signaling pathway, were filtered out as the underlying mechanisms of GQD on improving diabetic IR. In addition, the hub targets and pathways of quercetin coincided with most of the hub targets and pathways of GQD in each type of tissue, respectively, suggesting that quercetin may be a potential representative compound of GQD. CONCLUSIONS: Our analysis identifies the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue, which shows the characteristics of multi-compounds, multi-targets, multi-pathways, and multi-mechanisms of GQD and lays a solid foundation for further experimental research and clinical application.

Systemic pharmacology understanding of the key mechanism of Sedum sarmentosum Bunge in treating hepatitis.

Sedum sarmentosum Bunge is a Traditional Chinese Medicine that is widely used in treating hepatitis, whereas the detailed mechanisms have not been fully interpreted. A systemic pharmacology method including absorption, distribution, metabolism and elimination screening, drug targeting, interaction network plotting, and enrichment analysis was applied for exploring the underlying mechanisms of Sedum sarmentosum Bunge in the treatment of hepatitis. A total of 47 ingredients were identified in Sedum sarmentosum Bunge, and 5 active ingredients (DFV, isorhamnetin, beta-sitosterol, luteolin and quercetin) were screened out with the criteria of oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. Those 5 ingredients interacted with 170 targets, 163 of which were hepatitis-related. By compound-target-disease network plotting, protein-protein interaction network plotting and enrichment analysis, the pathways that the 5 ingredients engaged in during hepatitis development and progression were investigated, such as threonine-protein kinase signaling. The integrated systemic pharmacology analysis facilitates the in-depth understanding of Sedum sarmentosum Bunge in the hepatitis treatment, which also paves the way for further knowledge of the molecular mechanism of Sedum sarmentosum Bunge in treating hepatitis.

Network pharmacology-based strategy for predicting therapy targets of Tripterygium wilfordii on acute myeloid leukemia.

This is a study on the potential therapeutic targets and pharmacological mechanism of Tripterygium wilfordii (TW) in acute myeloid leukemia (AML) based on network pharmacology.Active components of TW were obtained by network pharmacology through oral bioavailability, drug-likeness filtration. Comparative analysis was used to investigate the overlapping genes between active ingredient's targets and AML treatment-related targets. Using STRING database to analyze interactions among overlapping genes. Both KEGG pathway analysis and Gene Ontology enrichment analysis were conducted in DAVID. These genes were analyzed for survival in OncoLnc database.We screened 53 active ingredients; the results of comparative analysis showed that 8 active ingredients had an effect on AML treatment. On the basis of the active ingredients and overlapping genes, we constructed the Drug-Compounds-Genes-Disease Network. Survival analysis of overlapping genes indicated that some targets possessed a significant influence on patients' survival and prognosis. The enrichment analysis showed that the main pathways of targets were Toll-like receptor signaling pathway, NF-kappa B signaling pathway, and HIF-1 signaling pathway.This study, using a network pharmacologic approach, provides another strategy that can help us to understand the mechanisms by which TW treats AML comprehensively.

Systems biology drug screening identifies statins as enhancers of current therapies in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is a B lymphoid malignancy highly dependent on the microenvironment. Despite new targeted therapies such as ibrutinib and venetoclax, disease progression and relapse remain an issue. CLL cell interactions with the supportive tissue microenvironment play a critical role in disease pathogenesis. We used a platform for drug discovery based on systems biology and artificial intelligence, to identify drugs targeting key proteins described to have a role in the microenvironment. The selected compounds were screened in CLL cell lines in the presence of stromal cells to mimic the microenvironment and validated the best candidates in primary CLL cells. Our results showed that the commercial drug simvastatin was the most effective and selective out of the tested compounds. Simvastatin decreased CLL cell survival and proliferation as well as cell adhesion. Importantly, this drug enhanced the antitumor effect of venetoclax and ibrutinib. We proposed that systems biology approaches combined with pharmacological screening could help to find new drugs for CLL treatment and to predict new combinations with current therapies. Our results highlight the possibility of repurposing widely used drugs such as statins to target the microenvironment and to improve the efficacy of ibrutinib or venetoclax in CLL cells.

Uncovering the pharmacological mechanism of the effects of the Banxia-Xiakucao Chinese Herb Pair on sleep disorder by a systems pharmacology approach.

Sleep disorder (SD) has a high incidence and seriously affects quality of life, mental health and even the manifestation of physical diseases. The combination of Pinellia ternata (Chinese name: banxia) and Prunella vulgaris (Chinese name: xiakucao), known as the Banxia-Xiakucao Chinese herb pair (BXHP), is a proven Chinese herbal medicine that has been used to treat SD for thousands of years due to its significant clinical effects. However, its active pharmacological components and sedative-hypnotic mechanisms have not been fully elucidated. Thus, the present study used a systematic pharmacological approach to develop pharmacokinetic screens and target predictions via construction of a protein-protein interaction network and annotation database for SD-related and putative BXHP-related targets. Visualization, screening and integrated discovery enrichment analyses were conducted. The BXHP chemical database contains 166 compounds between the two herbal ingredients, and of these, 22 potential active molecules were screened by pharmacokinetic evaluation. The targets of 114 of the active molecules were predicted, and 34 were selected for further analysis. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses suggested that BXHP can reduce inflammatory responses. and mediate immune-related and central nervous system neurotransmitters via regulation of multiple targets and pathways. The use of a systematic pharmacology-based approach in the present study further elucidated the mechanisms of action underlying BXHP for the treatment of SD from a holistic perspective and sheds light on the systemic mechanisms of action of Chinese herbal medicines in general.

Integrating systematic biological and proteomics strategies to explore the pharmacological mechanism of danshen yin modified on atherosclerosis.

This research utilized the systematic biological and proteomics strategies to explore the regulatory mechanism of Danshen Yin Modified (DSYM) on atherosclerosis (AS) biological network. The traditional Chinese medicine database and HPLC was used to find the active compounds of DSYM, Pharmmapper database was used to predict potential targets, and OMIM database and GeneCards database were used to collect AS targets. String database was utilized to obtain the other protein of proteomics proteins and the protein-protein interaction (PPI) data of DSYM targets, AS genes, proteomics proteins and other proteins. The Cytoscape 3.7.1 software was utilized to construct and analyse the network. The DAVID database is used to discover the biological processes and signalling pathways that these proteins aggregate. Finally, animal experiments and proteomics analysis were used to further verify the prediction results. The results showed that 140 active compounds, 405 DSYM targets and 590 AS genes were obtained, and 51 differentially expressed proteins were identified in the DSYM-treated ApoE-/- mouse AS model. A total of 4 major networks and a number of their derivative networks were constructed and analysed. The prediction results showed that DSYM can regulate AS-related biological processes and signalling pathways. Animal experiments have also shown that DSYM has a therapeutic effect on ApoE-/-mouse AS model (P < .05). Therefore, this study proposed a new method based on systems biology, proteomics, and experimental pharmacology, and analysed the pharmacological mechanism of DSYM. DSYM may achieve therapeutic effects by regulating AS-related signalling pathways and biological processes found in this research.

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza.

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.

Assessing the Anti-cancer Therapeutic Mechanism of a Herbal Combination for Breast Cancer on System-level by a Network Pharmacological Approach.

BACKGROUND/AIM: Accumulating evidence has shown therapeutic effects of herbals on breast cancer, a commonly diagnosed malignancy in women worldwide. However, their underlying mechanisms remain unclear. We aimed to explore the mode of action of a recently developed herbal combination at system-level. MATERIALS AND METHODS: We employed network pharmacological approaches to study the mechanism of a combination of three herbals, Astragalus membranaceus, Angelica gigas and Trichosanthes kirilowii by investigating active compounds and performing functional enrichment analysis for the interacting targets. RESULTS: For in silico pharmacokinetic evaluation, ten active ingredients interacted with fifty-six breast cancer-associated therapeutic targets. Functional enrichment analysis revealed that TNF, estrogen, PI3K-Akt and MAPK signaling pathways were involved in tumorigenesis and development of breast cancer. The pharmacological mechanisms might be associated with cellular effects on proliferation, cell cycle process and apoptosis. CONCLUSION: The present study provides novel insights into the system-level pharmacological mechanisms underlying a herbal combination used for breast cancer therapies.

Systems Pharmacology Dissection of Mechanisms of Dengzhan Xixin Injection against Cardiovascular Diseases.

Dengzhan Xixin injection (DZXXI), a herbal product prepared from a Chinese herb called Erigeron breviscapus, is a classical and traditional therapeutic for cadiovascular diseases (CVDs), including coronary heart disease (CHD), angina, and stroke, etc. However, its potential pharmacology mechanism against CVDs remains unclear. In this paper, a systems pharmacology-based strategy is presented for predicting drug targets and understanding therapeutic mechanisms of DZXXI against CVDs. The main ingredients were identified by HPLC-diode array detector (DAD). The target fishing was performed on the PharmMapper Server (http://lilab-ecust.cn/pharmmapper/). Potential targets were confirmed by two molecular docking tools, Sybyl-X 1.3 and Ledock to ensure the accuracy. The resulting target proteins were applied as baits to fish their related diseases and pathways from the molecular annotation system (MAS 3.0, http://bioinfo.capitalbio.com/mas3/) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/). Network generation and topological analysis were performed in Cytoscape 3.6.0. 15 main ingredients from DZXXI were identified. Forty five putative drug targets and 50 KEGG pathways, which have highly relevance to the therapeutic effects of DZXXI against CVDs, were then obtained. The systems analysis suggested that DZXXI could attenuate cardiac fibrosis, regulate cardiac contractility, and preserve heart function in adverse cardiac remodeling; meanwhile DZXXI also could have the function of activating blood circulation and dilating blood vessels. DZXXI exerts its therapeutic effects on CVDs possibly through multi-targets including CMA1, epidermal growth factor receptor (EGFR), phenylalanine-4-hydroxylase (PAH), SRC, F7, etc., and multi-pathways including Focal adhesion, mitogen-activated protein kinase (MAPK) signaling pathway, complement and coagulation cascades, Wnt signaling pathway, vascular endothelial growth factor (VEGF) signaling pathway, Renin-angiotensin system, etc.

Systems Biology Approaches in Autophagy Research.

As a classical form of programmed cell death, autophagy is widely involved in cellular metabolism and vital for the maintenance of homeostasis in physiological and pathological states. With multiple levels of regulation and signaling integrated in, autography presents complicated relevance with various diseases, such as cancer and neurological diseases. The emerging subject, systems biology, along with multi-omics approaches, offers a new strategy to investigate these interactive processes from a holistic perspective. In this chapter, we focus on the systems biology method for autophagy research and introduce essential research skills and procedures. The critical step of systematic study is to explore interplay between biological molecules based on massive biological data, which requires construction of networks in different biological levels, modification, and identification of key pathways and targets via optimized algorithm and experimental verification. Guided by systems biology research, drug design can thus be strengthened by efficient screening and accurate evaluation. Overall, systems biology promises to act as a powerful tool which both helps to clarify the profound mechanism and to develop efficacious medicine.

A Systems Biological Approach to Understanding the Mechanisms Underlying the Therapeutic Potential of Red Ginseng Supplements against Metabolic Diseases.

Red ginseng has been widely used in health-promoting supplements in Asia and is becoming increasingly popular in Western countries. However, its therapeutic mechanisms against most diseases have not been clearly elucidated. The aim of the present study was to provide the biological mechanisms of red ginseng against various metabolic diseases. We used a systems biological approach to comprehensively identify the component-target and target-pathway networks in order to explore the mechanisms underlying the therapeutic potential of red ginseng against metabolic diseases. Of the 23 components of red ginseng with target, 5 components were linked with 37 target molecules. Systematic analysis of the constructed networks revealed that these 37 targets were mainly involved in 9 signaling pathways relating to immune cell differentiation and vascular health. These results successfully explained the mechanisms underlying the efficiency of red ginseng for metabolic diseases, such as menopausal symptoms in women, blood circulation, diabetes mellitus, and hyperlipidemia.

A network pharmacology-based strategy for predicting anti-inflammatory targets of ephedra in treating asthma.

Asthma, the most common chronic respiratory disease in the world, is involved in a sustained inflammatory response caused by a variety of immune cells. Ephedra with multi-target, multi-pathway functions is an effective treatment for asthma. However, the ingredients and anti-inflammatory targets of ephedra in treating asthma are unclear. Therefore, there is a need for further research. Ephedra-related and anti-inflammatory targets were found and then combined to get intersection, which represented potential anti-inflammatory targets of ephedra. Moreover, compound-anti-inflammatory target and asthma-target protein-protein interaction network were merged to get the protein-protein interaction network intersection and core genes in asthma-target protein-protein interaction network. For the anti-inflammatory targets of ephedra in treating asthma, Gene Ontology and pathway analysis were executed to confirm gene functions of ephedra in antagonizing inflammation of asthma. Finally, molecular docking, qRT-PCR, WB and ELISA were performed to assess the binding activities between the compounds and anti-inflammatory targets of ephedra in treating asthma. Critical compounds and anti-inflammatory targets of ephedra in treating asthma were identified, including quercetin, luteolin, kempferol, naringenin, beta-sitosterol, SELE, IL-2 and CXCL10. The biological processes of anti-inflammatory targets of ephedra in treating asthma were involved in immune response, inflammatory response, cell-cell signaling and response to lipopolysaccharide. Moreover, 22 pathways were obtained and we proved that critical compounds inhabited the expression of SELE, IL-2 and CXCL10 at mRNA and protein levels.