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1.
Cell Mol Life Sci ; 77(3): 379-380, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31932855

RESUMO

We put together a special issue on current approaches in systems biology with a focus on mathematical modeling of metabolic networks. Mathematical models have increasingly been used to unravel molecular mechanisms of complex dynamic biological processes. We here provide a short introduction into the topics covered in this special issue, highlighting current developments and challenges.


Assuntos
Redes e Vias Metabólicas/fisiologia , Biologia de Sistemas/métodos , Humanos , Modelos Teóricos
2.
BMC Bioinformatics ; 20(1): 494, 2019 Oct 11.
Artigo em Inglês | MEDLINE | ID: mdl-31604427

RESUMO

BACKGROUND: Literature derived knowledge assemblies have been used as an effective way of representing biological phenomenon and understanding disease etiology in systems biology. These include canonical pathway databases such as KEGG, Reactome and WikiPathways and disease specific network inventories such as causal biological networks database, PD map and NeuroMMSig. The represented knowledge in these resources delineates qualitative information focusing mainly on the causal relationships between biological entities. Genes, the major constituents of knowledge representations, tend to express differentially in different conditions such as cell types, brain regions and disease stages. A classical approach of interpreting a knowledge assembly is to explore gene expression patterns of the individual genes. However, an approach that enables quantification of the overall impact of differentially expressed genes in the corresponding network is still lacking. RESULTS: Using the concept of heat diffusion, we have devised an algorithm that is able to calculate the magnitude of regulation of a biological network using expression datasets. We have demonstrated that molecular mechanisms specific to Alzheimer (AD) and Parkinson Disease (PD) regulate with different intensities across spatial and temporal resolutions. Our approach depicts that the mitochondrial dysfunction in PD is severe in cortex and advanced stages of PD patients. Similarly, we have shown that the intensity of aggregation of neurofibrillary tangles (NFTs) in AD increases as the disease progresses. This finding is in concordance with previous studies that explain the burden of NFTs in stages of AD. CONCLUSIONS: This study is one of the first attempts that enable quantification of mechanisms represented as biological networks. We have been able to quantify the magnitude of regulation of a biological network and illustrate that the magnitudes are different across spatial and temporal resolution.


Assuntos
Algoritmos , Encéfalo/metabolismo , Doenças Neurodegenerativas/metabolismo , Biologia de Sistemas/métodos , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Regulação da Expressão Gênica , Humanos , Redes e Vias Metabólicas , Mitocôndrias/metabolismo , Mitocôndrias/fisiologia , Doenças Neurodegenerativas/genética , Doenças Neurodegenerativas/fisiopatologia , Doença de Parkinson/genética , Doença de Parkinson/metabolismo , Doença de Parkinson/fisiopatologia , Mapas de Interação de Proteínas , Transdução de Sinais
3.
BMC Bioinformatics ; 20(1): 508, 2019 Oct 21.
Artigo em Inglês | MEDLINE | ID: mdl-31638901

RESUMO

BACKGROUND: At the molecular level, nonlinear networks of heterogeneous molecules control many biological processes, so that systems biology provides a valuable approach in this field, building on the integration of experimental biology with mathematical modeling. One of the biggest challenges to making this integration a reality is that many life scientists do not possess the mathematical expertise needed to build and manipulate mathematical models well enough to use them as tools for hypothesis generation. Available modeling software packages often assume some modeling expertise. There is a need for software tools that are easy to use and intuitive for experimentalists. RESULTS: This paper introduces PlantSimLab, a web-based application developed to allow plant biologists to construct dynamic mathematical models of molecular networks, interrogate them in a manner similar to what is done in the laboratory, and use them as a tool for biological hypothesis generation. It is designed to be used by experimentalists, without direct assistance from mathematical modelers. CONCLUSIONS: Mathematical modeling techniques are a useful tool for analyzing complex biological systems, and there is a need for accessible, efficient analysis tools within the biological community. PlantSimLab enables users to build, validate, and use intuitive qualitative dynamic computer models, with a graphical user interface that does not require mathematical modeling expertise. It makes analysis of complex models accessible to a larger community, as it is platform-independent and does not require extensive mathematical expertise.


Assuntos
Simulação por Computador , Modelos Biológicos , Plantas , Software , Internet , Biologia de Sistemas/métodos , Interface Usuário-Computador
4.
Nat Commun ; 10(1): 4162, 2019 09 13.
Artigo em Inglês | MEDLINE | ID: mdl-31519910

RESUMO

Insoluble protein aggregates are the hallmarks of many neurodegenerative diseases. For example, aggregates of TDP-43 occur in nearly all cases of amyotrophic lateral sclerosis (ALS). However, whether aggregates cause cellular toxicity is still not clear, even in simpler cellular systems. We reasoned that deep mutagenesis might be a powerful approach to disentangle the relationship between aggregation and toxicity. We generated >50,000 mutations in the prion-like domain (PRD) of TDP-43 and quantified their toxicity in yeast cells. Surprisingly, mutations that increase hydrophobicity and aggregation strongly decrease toxicity. In contrast, toxic variants promote the formation of dynamic liquid-like condensates. Mutations have their strongest effects in a hotspot that genetic interactions reveal to be structured in vivo, illustrating how mutagenesis can probe the in vivo structures of unstructured proteins. Our results show that aggregation of TDP-43 is not harmful but protects cells, most likely by titrating the protein away from a toxic liquid-like phase.


Assuntos
Biologia Computacional/métodos , Genômica/métodos , Biologia de Sistemas/métodos , Esclerose Amiotrófica Lateral/genética , Esclerose Amiotrófica Lateral/metabolismo , Humanos , Interações Hidrofóbicas e Hidrofílicas , Mutação/genética , Príons/genética , Príons/metabolismo
5.
An Acad Bras Cienc ; 91(3): e20180424, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31553364

RESUMO

Abstract: Cardiovascular diseases (CVDs) are leading causes of death in the world, owing to noticeable incidence and mortality. Traditional Chinese Medicine (TCM) SINI Decoction (SND) is used to prevent and treat CVDs, which has attracted extensive attention for its moderate and little side effects. However, the involved molecular mechanisms are exceedingly complicated and remain unclear. Systems pharmacology, as a novel approach that integrates systems biology and pharmacology plays a significant role in investigating the molecular mechanism of TCM. In systems pharmacology approach, we use to systematically uncover the mechanisms of action in Chinese medicinal formula SND as an effective treatment for CVDs, which mainly includes:1) molecular database building; 2) ADME evaluation; 3) target-fishing 4) network construction and analysis. The results show that 78 underlying valid ingredients and their corresponding 71 direct targets of SND were obtained. And SND take part in cardiomyocyte protection, blood pressure regulation, and lipid regulation module in treatment of CVDs by cooperative way. Systems pharmacology as an emerging field that investigates the molecular mechanisms of TCM through pharmacokinetic evaluation target prediction, and pathway analysis, which will facilitate the development of traditional Chinese herbs in modern medicine.


Assuntos
Doenças Cardiovasculares/tratamento farmacológico , Medicamentos de Ervas Chinesas/química , Medicina Tradicional Chinesa , Biologia de Sistemas/métodos , Humanos , Modelos Biológicos
6.
Life Sci ; 235: 116820, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31476308

RESUMO

AIMS: Osteoporosis (OP) is a systemic metabolic bone disease characterized by bone mass decrease and microstructural degradation, which may increase the risk of bone fracture and leading to high morbidity. Dipsaci Radix (DR), one typical traditional Chinese medicine (TCM), which has been applied in the treatment of OP with good therapeutic effects and few side effects. However, the underlying molecular mechanisms of DR to treat OP have not been fully elucidated. In this study, we aim to dissect the molecular mechanism of DR in the treatment of OP. MATERIALS AND METHODS: A systems pharmacology approach was employed to comprehensively dissect the action mechanisms of DR for the treatment of OP. KEY FINDINGS: 10 compounds were screened out as the potential active ingredients with excellent biological activity based on in silico ADME (absorption, distribution, metabolism and excretion) prediction model. Then, 36 key protein targets of 6 compounds were identified by systems drug targeting model (SysDT) and they were involved in several biological processes, such as osteoclast differentiation, osteoblast differentiation and anti-inflammation. The target-pathway network indicated that targets are mainly mapped in multiple signaling pathways, i.e., MAPK, Tumor necrosis factor α (TNF-α), NF-κb and Toll-like receptor pathways. The in vitro results indicated that the compounds ursolic acid and beta-sitosterol effectively inhibited the osteoclast differentiation. SIGNIFICANCE: These results systematically dissected that DR exhibits the therapeutic effects of OP by the regulation of immune system-related pathways, which provide novel perspective to drug development of OP.


Assuntos
Bases de Dados de Produtos Farmacêuticos , Dipsacaceae/química , Medicamentos de Ervas Chinesas/farmacologia , Redes Reguladoras de Genes , Redes e Vias Metabólicas , Osteoporose/tratamento farmacológico , Biologia de Sistemas/métodos , Células CACO-2 , Humanos , Osteoporose/genética , Osteoporose/metabolismo , Transdução de Sinais
7.
Int J Mol Sci ; 20(16)2019 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-31430856

RESUMO

Asthma is a common chronic airway disease worldwide. Due to its clinical and genetic heterogeneity, the cellular and molecular processes in asthma are highly complex and relatively unknown. To discover novel biomarkers and the molecular mechanisms underlying asthma, several studies have been conducted by focusing on gene expression patterns in epithelium through microarray analysis. However, few robust specific biomarkers were identified and some inconsistent results were observed. Therefore, it is imperative to conduct a robust analysis to solve these problems. Herein, an integrated gene expression analysis of ten independent, publicly available microarray data of bronchial epithelial cells from 348 asthmatic patients and 208 healthy controls was performed. As a result, 78 up- and 75 down-regulated genes were identified in bronchial epithelium of asthmatics. Comprehensive functional enrichment and pathway analysis revealed that response to chemical stimulus, extracellular region, pathways in cancer, and arachidonic acid metabolism were the four most significantly enriched terms. In the protein-protein interaction network, three main communities associated with cytoskeleton, response to lipid, and regulation of response to stimulus were established, and the most highly ranked 6 hub genes (up-regulated CD44, KRT6A, CEACAM5, SERPINB2, and down-regulated LTF and MUC5B) were identified and should be considered as new biomarkers. Pathway cross-talk analysis highlights that signaling pathways mediated by IL-4/13 and transcription factor HIF-1α and FOXA1 play crucial roles in the pathogenesis of asthma. Interestingly, three chemicals, polyphenol catechin, antibiotic lomefloxacin, and natural alkaloid boldine, were predicted and may be potential drugs for asthma treatment. Taken together, our findings shed new light on the common molecular pathogenesis mechanisms of asthma and provide theoretical support for further clinical therapeutic studies.


Assuntos
Asma/diagnóstico , Biologia de Sistemas/métodos , Asma/genética , Asma/metabolismo , Asma/patologia , Biomarcadores/análise , Biomarcadores/metabolismo , Regulação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Mapas de Interação de Proteínas , Transcriptoma
8.
Stud Hist Philos Biol Biomed Sci ; 78: 101201, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31422008

RESUMO

In this paper we aim to give an analysis and cognitive rationalization of a common practice or strategy of modeling in systems biology known as a middle-out modeling strategy. The strategy in the cases we look at is facilitated through the construction of what can be called mesoscopic models. Many models built in computational systems biology are mesoscopic (midsize) in scale. Such models lack the sufficient fidelity to serve as robust predictors of the behaviors of complex biological systems, one of the signature goals of the field. This puts some pressure on the field to provide reasons for why and how these practices are warranted despite not meeting the stated goals of the field. Using the results of ethnographic study of problem-solving practices in systems biology, we aim to examine the middle-out strategy and mesoscopic modeling in detail and to show that these practices are rational responses to complex problem solving tasks on cognitive grounds in particular. However making this claim requires us to update the standard notion of bounded rationality to take account of how human cognition is coupled to computation in these contexts. Our account fleshes out the idea that has been raised by some philosophers on the "hybrid" nature of computational modeling and simulation. What we call "coupling" both extends modelers' capacities to handle complex systems, but also produces various cognitive and computational constraints which need to be taken into account in any computational problem solving strategy seeking to maintain insight and control over the models produced.


Assuntos
Cognição , Modelos Biológicos , Biologia de Sistemas/métodos , Humanos
9.
Int J Mol Sci ; 20(15)2019 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-31366017

RESUMO

Epilepsy refers to a common chronic neurological disorder that affects all age groups. Unfortunately, antiepileptic drugs are ineffective in about one-third of patients. The complex interindividual variability influences the response to drug treatment rendering the therapeutic failure one of the most relevant problems in clinical practice also for increased hospitalizations and healthcare costs. Recent advances in the genetics and neurobiology of epilepsies are laying the groundwork for a new personalized medicine, focused on the reversal or avoidance of the pathophysiological effects of specific gene mutations. This could lead to a significant improvement in the efficacy and safety of treatments for epilepsy, targeting the biological mechanisms responsible for epilepsy in each individual. In this review article, we focus on the mechanism of the epilepsy pharmacoresistance and highlight the use of a systems biology approach for personalized medicine in refractory epilepsy.


Assuntos
Epilepsia Resistente a Medicamentos/tratamento farmacológico , Genômica/métodos , Medicina de Precisão/métodos , Biologia de Sistemas/métodos , Anticonvulsivantes/uso terapêutico , Epilepsia Resistente a Medicamentos/genética , Humanos , Variantes Farmacogenômicos
10.
PLoS Negl Trop Dis ; 13(8): e0007678, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31469838

RESUMO

Wolbachia are alpha-proteobacteria known to infect arthropods, which are of interest for disease control since they have been associated with improved resistance to viral infection. Although several genomes for different strains have been sequenced, there is little knowledge regarding the relationship between this bacterium and their hosts, particularly on their dependency for survival. Motivated by the potential applications on disease control, we developed genome-scale models of four Wolbachia strains known to infect arthropods: wAlbB (Aedes albopictus), wVitA (Nasonia vitripennis), wMel and wMelPop (Drosophila melanogaster). The obtained metabolic reconstructions exhibit a metabolism relying mainly on amino acids for energy production and biomass synthesis. A gap analysis was performed to detect metabolic candidates which could explain the endosymbiotic nature of this bacterium, finding that amino acids, requirements for ubiquinone precursors and provisioning of metabolites such as riboflavin could play a crucial role in this relationship. This work provides a systems biology perspective for studying the relationship of Wolbachia with its host and the development of new approaches for control of the spread of arboviral diseases. This approach, where metabolic gaps are key objects of study instead of just additions to complete a model, could be applied to other endosymbiotic bacteria of interest.


Assuntos
Interações entre Hospedeiro e Microrganismos , Simbiose , Wolbachia/crescimento & desenvolvimento , Wolbachia/metabolismo , Aedes/microbiologia , Animais , Drosophila melanogaster/microbiologia , Himenópteros/microbiologia , Biologia de Sistemas/métodos
11.
Nat Commun ; 10(1): 3476, 2019 08 02.
Artigo em Inglês | MEDLINE | ID: mdl-31375661

RESUMO

Recent advances in DNA/RNA sequencing have made it possible to identify new targets rapidly and to repurpose approved drugs for treating heterogeneous diseases by the 'precise' targeting of individualized disease modules. In this study, we develop a Genome-wide Positioning Systems network (GPSnet) algorithm for drug repurposing by specifically targeting disease modules derived from individual patient's DNA and RNA sequencing profiles mapped to the human protein-protein interactome network. We investigate whole-exome sequencing and transcriptome profiles from ~5,000 patients across 15 cancer types from The Cancer Genome Atlas. We show that GPSnet-predicted disease modules can predict drug responses and prioritize new indications for 140 approved drugs. Importantly, we experimentally validate that an approved cardiac arrhythmia and heart failure drug, ouabain, shows potential antitumor activities in lung adenocarcinoma by uniquely targeting a HIF1α/LEO1-mediated cell metabolism pathway. In summary, GPSnet offers a network-based, in silico drug repurposing framework for more efficacious therapeutic selections.


Assuntos
Algoritmos , Reposicionamento de Medicamentos/métodos , Biologia de Sistemas/métodos , Adenocarcinoma de Pulmão/tratamento farmacológico , Adenocarcinoma de Pulmão/genética , Arritmias Cardíacas/tratamento farmacológico , Arritmias Cardíacas/genética , Simulação por Computador , Conjuntos de Dados como Assunto , Estudos de Viabilidade , Redes Reguladoras de Genes/efeitos dos fármacos , Insuficiência Cardíaca/tratamento farmacológico , Insuficiência Cardíaca/genética , Saúde Holística , Humanos , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Redes e Vias Metabólicas/efeitos dos fármacos , Redes e Vias Metabólicas/genética , Terapia de Alvo Molecular/métodos , Ouabaína/farmacologia , Ouabaína/uso terapêutico , Mapas de Interação de Proteínas/efeitos dos fármacos , Mapas de Interação de Proteínas/genética , Fatores de Transcrição/metabolismo , Transcriptoma
13.
Nucleic Acids Res ; 47(15): 7753-7766, 2019 09 05.
Artigo em Inglês | MEDLINE | ID: mdl-31340025

RESUMO

MicroRNAs (miRNAs) are short, noncoding RNAs that regulate gene expression by suppressing mRNA translation and reducing mRNA stability. A miRNA can potentially bind many mRNAs, thereby affecting the expression of oncogenes and tumor suppressor genes as well as the activity of whole pathways. The promise of miRNA therapeutics in cancer is to harness this evolutionarily conserved mechanism for the coordinated regulation of gene expression, and thus restoring a normal cell phenotype. However, the promiscuous binding of miRNAs can provoke unwanted off-target effects, which are usually caused by high-dose single-miRNA treatments. Thus, it is desirable to develop miRNA therapeutics with increased specificity and efficacy. To achieve that, we propose the concept of miRNA cooperativity in order to exert synergistic repression on target genes, thus lowering the required total amount of miRNAs. We first review miRNA therapies in clinical application. Next, we summarize the knowledge on the molecular mechanism and biological function of miRNA cooperativity and discuss its application in cancer therapies. We then propose and discuss a systems biology approach to investigate miRNA cooperativity for the clinical setting. Altogether, we point out the potential of miRNA cooperativity to reduce off-target effects and to complement conventional, targeted, or immune-based therapies for cancer.


Assuntos
Antineoplásicos/uso terapêutico , Regulação Neoplásica da Expressão Gênica , MicroRNAs/genética , Neoplasias/terapia , RNA Neoplásico/genética , Biologia de Sistemas/métodos , Antagomirs/genética , Antagomirs/metabolismo , Antineoplásicos/química , Antineoplásicos/metabolismo , Apoptose/efeitos dos fármacos , Apoptose/genética , Quimioterapia Adjuvante/métodos , Redes Reguladoras de Genes , Humanos , MicroRNAs/agonistas , MicroRNAs/antagonistas & inibidores , MicroRNAs/metabolismo , Neoplasias/genética , Neoplasias/metabolismo , Neoplasias/patologia , Oligorribonucleotídeos/genética , Oligorribonucleotídeos/metabolismo , Estabilidade de RNA , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , RNA Neoplásico/agonistas , RNA Neoplásico/antagonistas & inibidores , RNA Neoplásico/metabolismo , Bibliotecas de Moléculas Pequenas/uso terapêutico , Proteínas Supressoras de Tumor/agonistas , Proteínas Supressoras de Tumor/genética , Proteínas Supressoras de Tumor/metabolismo
14.
BMC Bioinformatics ; 20(1): 395, 2019 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-31311516

RESUMO

BACKGROUND: Ordinary differential equation systems are frequently utilized to model biological systems and to infer knowledge about underlying properties. For instance, the development of drugs requires the knowledge to which extent malign cells differ from healthy ones to provide a specific treatment with least side effects. As these cell-type specific properties may stem from any part of biochemical cell processes, systematic quantitative approaches are necessary to identify the relevant potential drug targets. An ℓ1 regularization for the maximum likelihood parameter estimation proved to be successful, but falsely predicted cell-type dependent behaviour had to be corrected manually by using a Profile Likelihood approach. RESULTS: The choice of extended ℓ1 penalty functions significantly decreased the number of falsely detected cell-type specific parameters. Thus, the total accuracy of the prediction could be increased. This was tested on a realistic dynamical benchmark model used for the DREAM6 challenge. Among Elastic Net, Adaptive Lasso and a non-convex ℓq penalty, the latter one showed the best predictions whilst also requiring least computation time. All extended methods include a hyper-parameter in the regularization function. For an Erythropoietin (EPO) induced signalling pathway, the extended methods ℓq and Adaptive Lasso revealed an unpublished alternative parsimonious model when varying the respective hyper-parameters. CONCLUSIONS: Using ℓq or Adaptive Lasso with an a-priori choice for the hyper-parameter can lead to a more specific and accurate result than ℓ1. Scanning different hyper-parameters can yield additional pieces of information about the system.


Assuntos
Modelos Biológicos , Eritropoetina/metabolismo , Humanos , Janus Quinase 2/metabolismo , Funções Verossimilhança , Fator de Transcrição STAT5/metabolismo , Transdução de Sinais , Biologia de Sistemas/métodos
15.
Nat Biotechnol ; 37(7): 810-818, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31267104

RESUMO

A major challenge for stem cell engineering is achieving a holistic understanding of the molecular networks and biological processes governing cell differentiation. To address this challenge, we describe a computational approach that combines gene expression analysis, previous knowledge from proteomic pathway informatics and cell signaling models to delineate key transitional states of differentiating cells at high resolution. Our network models connect sparse gene signatures with corresponding, yet disparate, biological processes to uncover molecular mechanisms governing cell fate transitions. This approach builds on our earlier CellNet and recent trajectory-defining algorithms, as illustrated by our analysis of hematopoietic specification along the erythroid lineage, which reveals a role for the EGF receptor family member, ErbB4, as an important mediator of blood development. We experimentally validate this prediction and perturb the pathway to improve erythroid maturation from human pluripotent stem cells. These results exploit an integrative systems perspective to identify new regulatory processes and nodes useful in cell engineering.


Assuntos
Engenharia Celular , Células-Tronco Hematopoéticas/metabolismo , Células-Tronco Pluripotentes Induzidas/fisiologia , Biologia de Sistemas/métodos , Algoritmos , Animais , Antígenos CD34/genética , Antígenos CD34/metabolismo , Diferenciação Celular , Linhagem da Célula , Proliferação de Células , Biologia Computacional/métodos , Eritrócitos , Eritropoese , Citometria de Fluxo , Regulação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Camundongos , Receptor ErbB-4/metabolismo , Transdução de Sinais , Peixe-Zebra
17.
BMC Bioinformatics ; 20(1): 385, 2019 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-31288758

RESUMO

BACKGROUND: In cancer research, robustness of a complex biochemical network is one of the most relevant properties to investigate for the development of novel targeted therapies. In cancer systems biology, biological networks are typically modeled through Ordinary Differential Equation (ODE) models. Hence, robustness analysis consists in quantifying how much the temporal behavior of a specific node is influenced by the perturbation of model parameters. The Conditional Robustness Algorithm (CRA) is a valuable methodology to perform robustness analysis on a selected output variable, representative of the proliferation activity of cancer disease. RESULTS: Here we introduce our new freely downloadable software, the CRA Toolbox. The CRA Toolbox is an Object-Oriented MATLAB package which implements the features of CRA for ODE models. It offers the users the ability to import a mathematical model in Systems Biology Markup Language (SBML), to perturb the model parameter space and to choose the reference node for the robustness analysis. The CRA Toolbox allows the users to visualize and save all the generated results through a user-friendly Graphical User Interface (GUI). The CRA Toolbox has a modular and flexible architecture since it is designed according to some engineering design patterns. This tool has been successfully applied in three nonlinear ODE models: the Prostate-specific Pten-/- mouse model, the Pulse Generator Network and the EGFR-IGF1R pathway. CONCLUSIONS: The CRA Toolbox for MATLAB is an open-source tool implementing the CRA to perform conditional robustness analysis. With its unique set of functions, the CRA Toolbox is a remarkable software for the topological study of biological networks. The source and example code and the corresponding documentation are freely available at the web site: http://gitlab.ict4life.com/SysBiOThe/CRA-Matlab .


Assuntos
Algoritmos , Modelos Biológicos , Neoplasias/metabolismo , Software , Biologia de Sistemas/métodos , Animais , Simulação por Computador , Modelos Animais de Doenças , Receptores ErbB/metabolismo , Humanos , Cinética , Masculino , Camundongos , Especificidade de Órgãos , PTEN Fosfo-Hidrolase/deficiência , PTEN Fosfo-Hidrolase/metabolismo , Próstata/metabolismo , Receptor IGF Tipo 1/metabolismo , Transdução de Sinais
18.
Int J Mol Sci ; 20(15)2019 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-31357410

RESUMO

Kidney-yang deficiency syndrome (KYDS) is a metabolic disease caused by a neuro-endocrine disorder. The You-gui pill (YGP) is a classic traditional Chinese medicine (TCM) formula for the treatment of KYDS and has been widely used to warm and recuperate KYDS clinically for hundreds of years in China. However, it is unknown whetherthe corresponding targets and metabolic pathways can also be found via using metabonomics based on one platform (e.g., 1H NMR) to study different biological samples of KYDS. At the same time, relevant reports on further molecular verification (e.g., RT-qPCR analysis) of these targets associated with biomarkers and metabolic pathways have not yet, to our knowledge, been seen in KYDS's research. In the present study, a comprehensive strategy integrating systems pharmacology and 1H NMR-based urinary metabonomics analysis was proposed to identify the target proteins and metabolic pathways that YGP acts on KYDS. Thereafter, further validation of target proteins in kidney tissue was performed through quantitative real-time PCR analysis (RT-qPCR). Furthermore, biochemical parameters and histopathological analysis were studied. As a result, seven target proteins (L-serine dehydratase; phosphoenolpyruvate carboxykinase; spermidine synthase; tyrosyl-tRNA synthetase, glutamine synthetase; 3-hydroxyacyl-CoA dehydrogenase; glycine amidinotransferase) in YGP were discovered to play a therapeutic role in KYDS via affecting eight metabolic pathways (glycine, serine and threonine metabolism; butanoate metabolism; TCA cycle, etc.). Importantly, three target proteins (i.e., 3-hydroxyacyl-CoA dehydrogenase; glutamine synthetase; and glycine amidinotransferase) and two metabolic pathways (butanoate metabolism and dicarboxylate metabolism) related to KYDS, to our knowledge, had been newly discovered in our study. The mechanism of action mainly involved energy metabolism, oxidative stress, ammonia metabolism, amino acid metabolism, and fatty acid metabolism. In short, our study demonstrated that targets and metabolic pathways for the treatment of KYDS by YGP can be effectively found via combining with systems pharmacology and urinary metabonomics. In addition to this, common and specific targets and metabolic pathways of KYDS treated by YGP can be found effectively by integration with the analysis of different biological samples (e.g., serum, urine, feces, and tissue). It is; therefore, important that this laid the foundation for deeper mechanism research and drug-targeted therapy of KYDS in future.


Assuntos
Medicamentos de Ervas Chinesas/farmacologia , Regulação da Expressão Gênica/efeitos dos fármacos , Nefropatias/etiologia , Nefropatias/metabolismo , Redes e Vias Metabólicas/efeitos dos fármacos , Deficiência da Energia Yang/etiologia , Deficiência da Energia Yang/metabolismo , Animais , Biomarcadores , Biópsia , Medicamentos de Ervas Chinesas/uso terapêutico , Humanos , Nefropatias/diagnóstico , Nefropatias/tratamento farmacológico , Espectroscopia de Ressonância Magnética , Masculino , Metaboloma , Metabolômica/métodos , Ratos , Reação em Cadeia da Polimerase em Tempo Real , Biologia de Sistemas/métodos , Deficiência da Energia Yang/diagnóstico , Deficiência da Energia Yang/tratamento farmacológico
19.
IET Syst Biol ; 13(3): 109-119, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31170690

RESUMO

Sensitivity analysis has been widely applied to study the biological systems, including metabolic networks, signalling pathways, and genetic circuits. The Morris method is a kind of screening sensitivity analysis approach, which can fast identify a few key factors from numerous biological parameters and inputs. The parameter or input space is randomly sampled to produce a very limited number of trajectories for the calculation of elementary effects. It is clear that the sampled trajectories are not enough to cover the whole uncertain space, which eventually causes unstable sensitivity measures. This paper presents a novel trajectory optimisation algorithm for the Morris-based sensitivity calculation to ensure a good scan throughout the whole uncertain space. The paper demonstrates that this presented method gets more consistent sensitivity results through a benchmark example. The application to a previously published ordinary differential equation model of a cellular signalling network is presented. In detail, the parameter sensitivity analysis verifies the good agreement with data of the literatures.


Assuntos
Biologia de Sistemas/métodos , Algoritmos , Modelos Biológicos , Transdução de Sinais
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