Literature DB >> 25694073

Network based approach to drug discovery: a mini review.

Peng Li, Yingxue Fu, Yonghua Wang1.   

Abstract

With the rapid development of high-throughput genomic technologies and the accumulation of genome-wide datasets for human disease, it has been shown that using only reductionistic principles has been difficult to capture the complex biological networks and design rational medication. However, the emerging paradigm of "network based methodology" proposes to harness the power of networks to uncover relationships between various data types of interest for drug discovery. Recent advances include networks that encompass relationships between drugs, disease-related genes, therapeutic targets and diseases. It is shown how network techniques can help in the investigation of the mechanism of action of existing drugs, new molecules, or to identify novel disease genes and targets. We review how these different types of network analysis approaches facilitate drug discovery and their associated challenges. Some representative examples are reviewed to show that network analysis is a powerful, integrated, computational and experimental approach to improve the drug discovery process.

Entities:  

Mesh:

Year:  2015        PMID: 25694073     DOI: 10.2174/1389557515666150219143933

Source DB:  PubMed          Journal:  Mini Rev Med Chem        ISSN: 1389-5575            Impact factor:   3.862


  5 in total

1.  Topological network measures for drug repositioning.

Authors:  Apurva Badkas; Sébastien De Landtsheer; Thomas Sauter
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

Review 2.  Systems Pharmacology in Small Molecular Drug Discovery.

Authors:  Wei Zhou; Yonghua Wang; Aiping Lu; Ge Zhang
Journal:  Int J Mol Sci       Date:  2016-02-18       Impact factor: 5.923

Review 3.  Biomolecular Network-Based Synergistic Drug Combination Discovery.

Authors:  Xiangyi Li; Guangrong Qin; Qingmin Yang; Lanming Chen; Lu Xie
Journal:  Biomed Res Int       Date:  2016-11-07       Impact factor: 3.411

Review 4.  Thymus Regeneration and Future Challenges.

Authors:  Valentin P Shichkin; Mariastefania Antica
Journal:  Stem Cell Rev Rep       Date:  2020-04       Impact factor: 5.739

5.  A multiple network-based bioinformatics pipeline for the study of molecular mechanisms in oncological diseases for personalized medicine.

Authors:  Serena Dotolo; Anna Marabotti; Anna Maria Rachiglio; Riziero Esposito Abate; Marco Benedetto; Fortunato Ciardiello; Antonella De Luca; Nicola Normanno; Angelo Facchiano; Roberto Tagliaferri
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.