Drug repurposing is an unconventional drug discovery approach to explore new therapeutic benefits of existing, shelved and the drugs in clinical trials. This approach is currently emerging to overcome the bottleneck constraints faced during traditional drug discovery in grounds of financial support, timeline and resources. In this direction, several efforts were made for the construction of stratagems based on bioinformatics and computational tools to intensify the repurposing process off-late. Further, advanced research has succeeded in widening its boundaries in identification of gene targets and subsequent molecular interactions of the drugs depending on available omics data. Currently, the advent of data repositories like Connectivity Map (CMap), Library Integrated Network based Cellular Signatures (LINCS), Genome Wide Association Studies (GWAS), Side Effect Resource (SIDER), and Directionality Map (DMAP) has bestowed great oppurtunity to the researchers in improving their drug repurposing research exponentially. On the otherhand, in silico approaches like pharmacophore modelling and docking techniques circumvent the routine tedious in vitro and in vivo techniques involved in former screening phases of the drugs and disease specific targets. This review elaborates on currently designed contemporary tools, databases and strategies with relevant case studies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.biopha.2018.11.127 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Metformin use and pancreatic ductal adenocarcinoma outcomes: a narrative review.
ANZ J Surg
January 2025
Department of Surgery, Western Health, St. Albans, Victoria, Australia.
Background: Metformin is a diabetes medication with anti-mitotic properties. A narrative review was performed to investigate people using metformin and the risk of developing pancreatic ductal adenocarcinoma (PDAC) as well as survival outcomes in established PDAC.
Methods: Relevant studies on metformin use and PDAC were retrieved from PubMed including observational studies on metformin and the risk of developing PDAC and survival outcomes in PDAC, and randomized controlled trials of metformin as a treatment in PDAC.
On the importance of data curation for knowledge mining in antiviral research.
Sci Prog
January 2025
UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
The recent severe acute respiratory syndrome coronavirus 2 pandemic has clearly exemplified the need for broad-spectrum antiviral (BSA) medications. However, previous outbreaks show that about one year after an outbreak, interest in antiviral research diminishes and the work toward an effective medication is left unfinished. Martin et al.
View Article and Find Full Text PDFRole of Artificial Intelligence in Drug Discovery to Revolutionize the Pharmaceutical Industry: Resources, Methods and Applications.
Recent Pat Biotechnol
January 2025
SRM Modinagar College of Pharmacy, SRM Institute of Science and Technology, Delhi NCR Campus, Modinagar, Ghaziabad, Uttar Pradesh, India.
Traditional drug discovery methods such as wet-lab testing, validations, and synthetic techniques are time-consuming and expensive. Artificial Intelligence (AI) approaches have progressed to the point where they can have a significant impact on the drug discovery process. Using massive volumes of open data, artificial intelligence methods are revolutionizing the pharmaceutical industry.
View Article and Find Full Text PDFData-driven discovery of associations between prescribed drugs and dementia risk: A systematic review.
Alzheimers Dement (N Y)
January 2025
Department of Health and Community Sciences, Medical School University of Exeter Exeter UK.
Abstract: Recent clinical trials on slowing dementia progression have led to renewed focus on finding safer, more effective treatments. One approach to identify plausible candidates is to assess whether existing medications for other conditions may affect dementia risk. We conducted a systematic review to identify studies adopting a data-driven approach to investigate the association between a wide range of prescribed medications and dementia risk.
View Article and Find Full Text PDFNatural Compounds from Alhagi maurorum as Potential HCC and HepG2 Inhibitors: An Integrated Study using Pharmacophore Development, Molecular Docking, MD Simulation, and DFT Approaches.
Med Chem
January 2025
Department of Pharmacy, Pisa University, Pisa, Italy.
Background: The rise in the frequency of liver cancer all over the world makes it a prominent area of research in the discovery of new drugs or repurposing of existing drugs.
Methods: This article describes the pharmacophore-based structure-activity relationship (3DQSAR) on the secondary metabolites of Alhagi maurorum to inhibit human liver cancer cell lines Hepatocellular carcinoma (HCC) and hepatoma G2 (HepG2) which represents the molecular level understanding for isolated phytochemicals of Alhagi maurorum. The definite features, such as hydrophobic regions, average shape, and active compounds' electrostatic patterns, were mapped to screen phytochemicals.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!