scholarly journals Network-Assisted Prediction of Potential Drugs for Addiction

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jingchun Sun ◽  
Liang-Chin Huang ◽  
Hua Xu ◽  
Zhongming Zhao
Keyword(s):  
Drug Addiction ◽  
Drug Target ◽  
Addiction Treatment ◽  
Complex Disease ◽  
Drug Repurposing ◽  
Network Pharmacology ◽  
Network Analyses ◽  
Addictive Drugs ◽  
Target Network ◽  
Addictive Drug

Drug addiction is a chronic and complex brain disease, adding much burden on the community. Though numerous efforts have been made to identify the effective treatment, it is necessary to find more novel therapeutics for this complex disease. As network pharmacology has become a promising approach for drug repurposing, we proposed to apply the approach to drug addiction, which might provide new clues for the development of effective addiction treatment drugs. We first extracted 44 addictive drugs from the NIDA and their targets from DrugBank. Then, we constructed two networks: an addictive drug-target network and an expanded addictive drug-target network by adding other drugs that have at least one common target with these addictive drugs. By performing network analyses, we found that those addictive drugs with similar actions tended to cluster together. Additionally, we predicted 94 nonaddictive drugs with potential pharmacological functions to the addictive drugs. By examining the PubMed data, 51 drugs significantly cooccurred with addictive keywords than expected. Thus, the network analyses provide a list of candidate drugs for further investigation of their potential in addiction treatment or risk.

scholarly journals SmartGraph: A Network Pharmacology Investigation Platform

2019 ◽  
Author(s):  
Gergely Zahoránszky-Kőhalmi ◽  
Timothy Sheils ◽  
Tudor I. Oprea
Keyword(s):  
Drug Target ◽  
State Of The Art ◽  
Target Prediction ◽  
Drug Repurposing ◽  
Network Pharmacology ◽  
Biomedical Data ◽  
Graph Database ◽  
High Quality ◽  
Complex Landscape ◽  
Unique Compound

AbstractMotivationDrug discovery investigations need to incorporate network pharmacology concepts while navigating the complex landscape of drug-target and target-target interactions. This task requires solutions that integrate high-quality biomedical data, combined with analytic and predictive workflows as well as efficient visualization. SmartGraph is an innovative platform that utilizes state-of-the-art technologies such as a Neo4j graph-database, Angular web framework, RxJS asynchronous event library and D3 visualization to accomplish these goals.ResultsThe SmartGraph framework integrates high quality bioactivity data and biological pathway information resulting in a knowledgebase comprised of 420,526 unique compound-target interactions defined between 271,098 unique compounds and 2,018 targets. SmartGraph then performs bioactivity predictions based on the 63,783 Bemis-Murcko scaffolds extracted from these compounds. Through several use-cases, we illustrate the use of SmartGraph to generate hypotheses for elucidating mechanism-of-action, drug-repurposing and off-target prediction.Availabilityhttps://smartgraph.ncats.io/

scholarly journals The Role of Ghrelin/GHS-R1A Signaling in Nonalcohol Drug Addictions

2022 ◽  
Vol 23 (2) ◽  
pp. 761
Author(s):  
Magdalena Sustkova-Fiserova ◽  
Chrysostomos Charalambous ◽  
Anna Khryakova ◽  
Alina Certilina ◽  
Marek Lapka ◽  
...  
Keyword(s):  
Drug Addiction ◽  
Addiction Treatment ◽  
Early Stage ◽  
Human Society ◽  
Growth Hormone Secretagogue Receptor ◽  
Comprehensive Overview ◽  
Growth Hormone Secretagogue ◽  
Addictive Drugs ◽  
Abused Drugs

Drug addiction causes constant serious health, social, and economic burden within the human society. The current drug dependence pharmacotherapies, particularly relapse prevention, remain limited, unsatisfactory, unreliable for opioids and tobacco, and even symptomatic for stimulants and cannabinoids, thus, new more effective treatment strategies are researched. The antagonism of the growth hormone secretagogue receptor type A (GHS-R1A) has been recently proposed as a novel alcohol addiction treatment strategy, and it has been intensively studied in experimental models of other addictive drugs, such as nicotine, stimulants, opioids and cannabinoids. The role of ghrelin signaling in these drugs effects has also been investigated. The present review aims to provide a comprehensive overview of preclinical and clinical studies focused on ghrelin’s/GHS-R1A possible involvement in these nonalcohol addictive drugs reinforcing effects and addiction. Although the investigation is still in its early stage, majority of the existing reviewed experimental results from rodents with the addition of few human studies, that searched correlations between the genetic variations of the ghrelin signaling or the ghrelin blood content with the addictive drugs effects, have indicated the importance of the ghrelin’s/GHS-R1As involvement in the nonalcohol abused drugs pro-addictive effects. Further research is necessary to elucidate the exact involved mechanisms and to verify the future potential utilization and safety of the GHS-R1A antagonism use for these drug addiction therapies, particularly for reducing the risk of relapse.

Identification of Antineoplastic Targets with Systems Approaches, Using Resveratrol as an In-Depth Case Study

2017 ◽  
Vol 23 (32) ◽  
pp. 4773-4793 ◽  
Author(s):  
Nivedita Singh ◽  
Sherry Freiesleben ◽  
Olaf Wolkenhauer ◽  
Yogeshwer Shukla ◽  
Shailendra K. Gupta
Keyword(s):  
Drug Target ◽  
Complex Disease ◽  
Biological Targets ◽  
Systems Approaches ◽  
Anticancer Mechanism ◽  
Genetic And Environmental Factors ◽  
Key Steps ◽  
Network Approaches ◽  
Novel Drug

The identification and validation of novel drug–target combinations are key steps in the drug discovery processes. Cancer is a complex disease that involves several genetic and environmental factors. High-throughput omics technologies are now widely available, however the integration of multi-omics data to identify viable anticancer drug-target combinations, that allow for a better clinical outcome when considering the efficacy-toxicity spectrum, is challenging. This review article provides an overview of systems approaches which help to integrate a broad spectrum of technologies and data. We focus on network approaches and investigate anticancer mechanism and biological targets of resveratrol using reverse pharmacophore mapping as an in-depth case study. The results of this case study demonstrate the use of systems approaches for a better understanding of the behavior of small molecule inhibitors in receptor binding sites. The presented network analysis approach helps in formulating hypotheses and provides mechanistic insights of resveratrol in neoplastic transformations.

scholarly journals Mining Significant Substructure Pairs for Interpreting Polypharmacology in Drug-Target Network

PLoS ONE ◽  
2011 ◽  
Vol 6 (2) ◽  
pp. e16999 ◽  
Author(s):  
Ichigaku Takigawa ◽  
Koji Tsuda ◽  
Hiroshi Mamitsuka
Keyword(s):  
Drug Target ◽  
Target Network

scholarly journals The Role of Personal, Famililal and Social Awarenesss in Permanent Drug Abandonment in Kashan Drug Addiction Treatment Centers

2019 ◽  
Vol 21 (4) ◽  
pp. 330-343
Author(s):  
SS Hoseinizadeh ◽  
M Niazi ◽  
M Mehtari Arani ◽  
◽  
◽  
...  
Keyword(s):  
Drug Addiction ◽  
Addiction Treatment ◽  
Drug Addiction Treatment
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