scholarly journals Updates on drug–target network; facilitating polypharmacology and data integration by growth of DrugBank database

2015 ◽  
pp. bbv094 ◽  
Author(s):  
Farnaz Barneh ◽  
Mohieddin Jafari ◽  
Mehdi Mirzaie
PLoS ONE ◽  
2011 ◽  
Vol 6 (2) ◽  
pp. e16999 ◽  
Author(s):  
Ichigaku Takigawa ◽  
Koji Tsuda ◽  
Hiroshi Mamitsuka
Keyword(s):  

Author(s):  
Milan Sencanski ◽  
Vladimir Perovic ◽  
Snezana Pajovic ◽  
Miroslav Adzic ◽  
Slobodan Paessler ◽  
...  

<p>The SARS-CoV-2 outbreak caused an unprecedented global public health threat, having a high transmission rate with currently no drugs or vaccines approved. An alternative powerful additional approach to counteract COVID-19 is <em>in silico</em> drug repurposing. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. In this study, we used the virtual screening (VS) protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. First, the ISM applied for Small Molecules was used for searching the Drugbank database and further followed by molecular docking. After <em>in silico</em> screening of drug space, we identified 57 drugs as potential SARS-CoV-2 main protease inhibitors that we propose for further experimental testing.</p>


2010 ◽  
Author(s):  
Deepak Ranjan Sethi ◽  
Sanjay Kundu ◽  
Ibnul Hassan ◽  
Biplab Bhattacharjee ◽  
Jayadeepa R.M ◽  
...  

2011 ◽  
Vol 46 (4) ◽  
pp. 1074-1094 ◽  
Author(s):  
Francisco Prado-Prado ◽  
Xerardo García-Mera ◽  
Paula Abeijón ◽  
Nerea Alonso ◽  
Olga Caamaño ◽  
...  

2007 ◽  
Vol 25 (10) ◽  
pp. 1119-1126 ◽  
Author(s):  
Muhammed A Yıldırım ◽  
Kwang-Il Goh ◽  
Michael E Cusick ◽  
Albert-László Barabási ◽  
Marc Vidal
Keyword(s):  

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247018
Author(s):  
Edgardo Galan-Vasquez ◽  
Ernesto Perez-Rueda

In this work, we performed an analysis of the networks of interactions between drugs and their targets to assess how connected the compounds are. For our purpose, the interactions were downloaded from the DrugBank database, and we considered all drugs approved by the FDA. Based on topological analysis of this interaction network, we obtained information on degree, clustering coefficient, connected components, and centrality of these interactions. We identified that this drug-target interaction network cannot be divided into two disjoint and independent sets, i.e., it is not bipartite. In addition, the connectivity or associations between every pair of nodes identified that the drug-target network is constituted of 165 connected components, where one giant component contains 4376 interactions that represent 89.99% of all the elements. In this regard, the histamine H1 receptor, which belongs to the family of rhodopsin-like G-protein-coupled receptors and is activated by the biogenic amine histamine, was found to be the most important node in the centrality of input-degrees. In the case of centrality of output-degrees, fostamatinib was found to be the most important node, as this drug interacts with 300 different targets, including arachidonate 5-lipoxygenase or ALOX5, expressed on cells primarily involved in regulation of immune responses. The top 10 hubs interacted with 33% of the target genes. Fostamatinib stands out because it is used for the treatment of chronic immune thrombocytopenia in adults. Finally, 187 highly connected sets of nodes, structured in communities, were also identified. Indeed, the largest communities have more than 400 elements and are related to metabolic diseases, psychiatric disorders and cancer. Our results demonstrate the possibilities to explore these compounds and their targets to improve drug repositioning and contend against emergent diseases.


2011 ◽  
Vol 1 (1) ◽  
Author(s):  
Francisco J. Azuaje ◽  
Lu Zhang ◽  
Yvan Devaux ◽  
Daniel R. Wagner

2011 ◽  
Vol 46 (12) ◽  
pp. 5838-5851 ◽  
Author(s):  
Francisco Prado-Prado ◽  
Xerardo García-Mera ◽  
Manuel Escobar ◽  
Eduardo Sobarzo-Sánchez ◽  
Matilde Yañez ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Qihui Wu ◽  
Yunbo Chen ◽  
Yong Gu ◽  
Shuhuan Fang ◽  
Weirong Li ◽  
...  

Abstract Background Alzheimer’s disease (AD) is the most common cause of dementia in the elderly, characterized by a progressive and irreversible loss of memory and cognitive abilities. Currently, the prevention and treatment of AD still remains a huge challenge. As a traditional Chinese medicine (TCM) prescription, Danggui-Shaoyao-san decoction (DSS) has been demonstrated to be effective for alleviating AD symptoms in animal experiments and clinical applications. However, due to the complex components and biological actions, its underlying molecular mechanism and effective substances are not yet fully elucidated. Methods In this study, we firstly systematically reviewed and summarized the molecular effects of DSS against AD based on current literatures of in vivo studies. Furthermore, an integrated systems pharmacology framework was proposed to explore the novel anti-AD mechanisms of DSS and identify the main active components. We further developed a network-based predictive model for identifying the active anti-AD components of DSS by mapping the high-quality AD disease genes into the global drug-target network. Results We constructed a global drug-target network of DSS consisting 937 unique compounds and 490 targets by incorporating experimental and computationally predicted drug–target interactions (DTIs). Multi-level systems pharmacology analyses revealed that DSS may regulate multiple biological pathways related to AD pathogenesis, such as the oxidative stress and inflammatory reaction processes. We further conducted a network-based statistical model, drug-likeness analysis, human intestinal absorption (HIA) and blood-brain barrier (BBB) penetration prediction to uncover the key ani-AD ingredients in DSS. Finally, we highlighted 9 key ingredients and validated their synergistic role against AD through a subnetwork. Conclusion Overall, this study proposed an integrative systems pharmacology approach to disclose the therapeutic mechanisms of DSS against AD, which also provides novel in silico paradigm for investigating the effective substances of complex TCM prescription.


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