Literature DB >> 30547440

Implementation of a Pipeline Using Disease-Disease Associations for Computational Drug Repurposing.

Preethi Balasundaram1, Rohini Kanagavelu1, Nivya James1, Sayoni Maiti1, Shanthi Veerappapillai1, Ramanathan Karuppaswamy2.   

Abstract

Drug repurposing is a powerful technique which has been recently employed in both industry and academia to discover and validate previously approved drugs for new indications. It provides the quickest possible transition from bench to bedside. In essence, computational strategies are appealing because they putatively nominate the most encouraging candidate for a given indication. A wide range of computational methods exist for repositioning. In this chapter we present the guidelines for performing integrated drug repurposing strategy by combining disease-disease association and molecular simulation analysis.

Keywords:  ALOGPS; AutoDock tools; CMAP; ChemMine; DisGeNET; Jaccard index; PLIP; PharmaGist; VigiAccess

Mesh:

Substances:

Year:  2019        PMID: 30547440     DOI: 10.1007/978-1-4939-8955-3_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

Review 1.  Machine Learning Techniques for Personalised Medicine Approaches in Immune-Mediated Chronic Inflammatory Diseases: Applications and Challenges.

Authors:  Junjie Peng; Elizabeth C Jury; Pierre Dönnes; Coziana Ciurtin
Journal:  Front Pharmacol       Date:  2021-09-30       Impact factor: 5.810

Review 2.  Computational methods directed towards drug repurposing for COVID-19: advantages and limitations.

Authors:  Prem Prakash Sharma; Meenakshi Bansal; Aaftaab Sethi; Lindomar Pena; Vijay Kumar Goel; Maria Grishina; Shubhra Chaturvedi; Dhruv Kumar; Brijesh Rathi
Journal:  RSC Adv       Date:  2021-11-10       Impact factor: 4.036

  2 in total

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