Literature DB >> 22935104

In silico drug repositioning: what we need to know.

Zhichao Liu1, Hong Fang, Kelly Reagan, Xiaowei Xu, Donna L Mendrick, William Slikker, Weida Tong.   

Abstract

Drug repositioning, exemplified by sildenafil and thalidomide, is a promising way to explore alternative indications for existing drugs. Recent research has shown that bioinformatics-based approaches have the potential to offer systematic insights into the complex relationships among drugs, targets and diseases necessary for successful repositioning. In this article, we propose the key bioinformatics steps essential for discovering valuable repositioning methods. The proposed steps (repurposing with a purpose, repurposing with a strategy and repurposing with confidence) are aimed at providing a repurposing pipeline, with particular focus on the proposed Drugs of New Indications (DNI) database, which can be used alongside currently available resources to improve in silico drug repositioning. Published by Elsevier Ltd.

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Year:  2012        PMID: 22935104     DOI: 10.1016/j.drudis.2012.08.005

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  44 in total

1.  Drug search for leishmaniasis: a virtual screening approach by grid computing.

Authors:  Rodrigo Ochoa; Stanley J Watowich; Andrés Flórez; Carol V Mesa; Sara M Robledo; Carlos Muskus
Journal:  J Comput Aided Mol Des       Date:  2016-07-20       Impact factor: 3.686

Review 2.  Drug repurposing in oncology--patient and health systems opportunities.

Authors:  Francesco Bertolini; Vikas P Sukhatme; Gauthier Bouche
Journal:  Nat Rev Clin Oncol       Date:  2015-10-20       Impact factor: 66.675

3.  Auto-Generated Physiological Chain Data for an Ontological Framework for Pharmacology and Mechanism of Action to Determine Suspected Drugs in Cases of Dysuria.

Authors:  Masayo Hayakawa; Takeshi Imai; Yoshimasa Kawazoe; Kouji Kozaki; Kazuhiko Ohe
Journal:  Drug Saf       Date:  2019-09       Impact factor: 5.606

4.  Design of a tripartite network for the prediction of drug targets.

Authors:  Ryo Kunimoto; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2018-01-16       Impact factor: 3.686

5.  Uncovering New Drug Properties in Target-Based Drug-Drug Similarity Networks.

Authors:  Lucreţia Udrescu; Paul Bogdan; Aimée Chiş; Ioan Ovidiu Sîrbu; Alexandru Topîrceanu; Renata-Maria Văruţ; Mihai Udrescu
Journal:  Pharmaceutics       Date:  2020-09-16       Impact factor: 6.321

6.  Discovery of novel polyamine analogs with anti-protozoal activity by computer guided drug repositioning.

Authors:  Lucas N Alberca; María L Sbaraglini; Darío Balcazar; Laura Fraccaroli; Carolina Carrillo; Andrea Medeiros; Diego Benitez; Marcelo Comini; Alan Talevi
Journal:  J Comput Aided Mol Des       Date:  2016-02-18       Impact factor: 3.686

7.  Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform.

Authors:  Geetika Sethi; Gaurav Chopra; Ram Samudrala
Journal:  Mini Rev Med Chem       Date:  2015       Impact factor: 3.862

Review 8.  Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines.

Authors:  Guangxu Jin; Stephen T C Wong
Journal:  Drug Discov Today       Date:  2013-11-14       Impact factor: 7.851

9.  A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning.

Authors:  Bo-Wei Zhao; Zhu-Hong You; Lun Hu; Zhen-Hao Guo; Lei Wang; Zhan-Heng Chen; Leon Wong
Journal:  Cancers (Basel)       Date:  2021-04-27       Impact factor: 6.639

Review 10.  Drug rechanneling: A novel paradigm for cancer treatment.

Authors:  Itishree Kaushik; Sharavan Ramachandran; Sahdeo Prasad; Sanjay K Srivastava
Journal:  Semin Cancer Biol       Date:  2020-05-11       Impact factor: 15.707

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