Network Medicine: Methods and Applications

2020 ◽  
pp. 3-18
Author(s):  
Italo F. do Valle ◽  
Helder I. Nakaya
Keyword(s):  
Network Medicine

scholarly journals Biomolecular Network-Based Synergistic Drug Combination Discovery

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Xiangyi Li ◽  
Guangrong Qin ◽  
Qingmin Yang ◽  
Lanming Chen ◽  
Lu Xie
Keyword(s):  
Drug Combination ◽  
Complex Disease ◽  
Recent Decade ◽  
Drug Combinations ◽  
Network Medicine ◽  
Disease Therapy ◽  
Biomolecular Network ◽  
Disease Related Genes ◽  
Disease Specific ◽  
Synergistic Drug Combinations

Drug combination is a powerful and promising approach for complex disease therapy such as cancer and cardiovascular disease. However, the number of synergistic drug combinations approved by the Food and Drug Administration is very small. To bridge the gap between urgent need and low yield, researchers have constructed various models to identify synergistic drug combinations. Among these models, biomolecular network-based model is outstanding because of its ability to reflect and illustrate the relationships among drugs, disease-related genes, therapeutic targets, and disease-specific signaling pathways as a system. In this review, we analyzed and classified models for synergistic drug combination prediction in recent decade according to their respective algorithms. Besides, we collected useful resources including databases and analysis tools for synergistic drug combination prediction. It should provide a quick resource for computational biologists who work with network medicine or synergistic drug combination designing.

Precision Medicine in Patients with Differential Diabetic Phenotypes: Novel Opportunities from Network Medicine

2021 ◽  
Vol 18 ◽  
Author(s):  
Claudio Napoli ◽  
Giuditta Benincasa ◽  
Samer Ellahham
Keyword(s):  
Precision Medicine ◽  
Protein Interactions ◽  
Randomized Clinical Trials ◽  
Growth Factor Receptor ◽  
Cardiovascular Complications ◽  
Personalized Therapy ◽  
Network Medicine ◽  
Prediabetic State ◽  
Relevant Role ◽  
Approved Drugs

Introduction: Diabetes mellitus (DM) comprises differential clinical phenotypes ranging from rare monogenic to common polygenic forms, such as type 1 (T1DM), type 2 (T2DM), and gestational diabetes, which are associated with cardiovascular complications. Also, the high-risk prediabetic state is rising worldwide, suggesting the urgent need for early personalized strategies to prevent and treat a hyperglycemic state. Objective: We aim to discuss the advantages and challenges of Network Medicine approaches in clarifying disease-specific molecular pathways, which may open novel ways for repurposing approved drugs to reach diabetes precision medicine and personalized therapy. Conclusion: The interactome [or protein-protein interactions (PPIs)] is a useful tool to identify subtle molecular differences between precise diabetic phenotypes and predict putative novel drugs. Despite being previously unappreciated as T2DM determinants, the growth factor receptor-bound protein 14 (GRB14), calmodulin 2 (CALM2), and protein kinase C-alpha (PRKCA) might have a relevant role in disease pathogenesis. Besides, in silico platforms have suggested that diflunisal, nabumetone, niflumic acid, and valdecoxib may be suitable for the treatment of T1DM; phenoxybenzamine and idazoxan for the treatment of T2DM by improving insulin secretion; and hydroxychloroquine reduce the risk of coronary heart disease (CHD) by counteracting inflammation. Network medicine has the potential to improve precision medicine in diabetes care and enhance personalized therapy. However, only randomized clinical trials will confirm the clinical utility of network-oriented biomarkers and drugs in the management of DM.

scholarly journals Microbiota and Network Medicine

2019 ◽  
Vol 2019 (2) ◽  
pp. 5-11
Author(s):  
Z.D. Semidotskaya ◽  
◽  
I.A. Chernyakova ◽  
M.Yu. Neffa ◽  
A.E. Chernyakova ◽  
...  
Keyword(s):  
Network Medicine

scholarly journals 2020 Jeffrey M. Hoeg Award Lecture

2020 ◽  
Author(s):  
Elena Aikawa ◽  
Mark C. Blaser
Keyword(s):  
Heart Valves ◽  
Molecular Level ◽  
Clinical Problem ◽  
Network Medicine ◽  
The Past ◽  
Ectopic Tissue ◽  
Level Data ◽  
Approaches To Study ◽  
Vascular Beds ◽  
Mechanistic Basis

Cardiovascular calcification is an insidious form of ectopic tissue mineralization that presents as a frequent comorbidity of atherosclerosis, aortic valve stenosis, diabetes, renal failure, and chronic inflammation. Calcification of the vasculature and heart valves contributes to mortality in these diseases. An inability to clinically image or detect early microcalcification coupled with an utter lack of pharmaceutical therapies capable of inhibiting or regressing entrenched and detectable macrocalcification has led to a prominent and deadly gap in care for a growing portion of our rapidly aging population. Recognition of this mounting concern has arisen over the past decade and led to a series of revolutionary works that has begun to pull back the curtain on the pathogenesis, mechanistic basis, and causative drivers of cardiovascular calcification. Central to this progress is the discovery that calcifying extracellular vesicles act as active precursors of cardiovascular microcalcification in diverse vascular beds. More recently, the omics revolution has resulted in the collection and quantification of vast amounts of molecular-level data. As the field has become poised to leverage these resources for drug discovery, new means of deriving relevant biological insights from these rich and complex datasets have come into focus through the careful application of systems biology and network medicine approaches. As we look onward toward the next decade, we envision a growing need to standardize approaches to study this complex and multifaceted clinical problem and expect that a push to translate mechanistic findings into therapeutics will begin to finally provide relief for those impacted by this disease.

Recent advances in network medicine: From disease mechanisms to new treatment strategies

2020 ◽  
Vol 26 (5) ◽  
pp. 609-615
Author(s):  
Ítalo Faria do Valle
Keyword(s):  
Molecular Mechanisms ◽  
Biological Significance ◽  
Treatment Strategies ◽  
Molecular Networks ◽  
Network Medicine ◽  
Disease Mechanisms ◽  
Protein Interactome ◽  
Cellular Context ◽  
Human Proteins ◽  
New Treatment

Conventional reductionist approaches have guided most of our understanding in disease diagnostic and treatment. However, most diseases are not consequence of perturbations in a single protein or metabolite, but rather of the effect that these perturbations have in their cellular context. The emerging field of network medicine offers a set of tools to explore molecular networks and to retrieve insights about mechanisms of different diseases. The study of the protein interactome, the map of physical interactions among human proteins, revealed that disease proteins tend to interact with each other, linking diseases to well-defined interactome neighborhoods. These disease-associated neighborhoods have been defined as disease modules, and they can uncover the biological significance of genes identified by genetic studies, reveal molecular mechanisms that connect different phenotypes, and help identify new pharmacological strategies for disease treatment. Therefore, network medicine offers a framework in which the complexity of different aspects of multiple sclerosis can be explored in an integrative fashion, which can ultimately provide insights about disease mechanisms and treatment.

Network Medicine — From Obesity to the “Diseasome”

2007 ◽  
Vol 357 (4) ◽  
pp. 404-407 ◽  
Author(s):  
Albert-László Barabási
Keyword(s):  
Network Medicine
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