Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Sandra Brasil, Mariateresa Allocca, Salvador C.M. Magrinho, Inês Santos, Madalena Raposo, Rita Francisco, Carlota Pascoal, Tiago Martins, Paula A. Videira, Florbela Pereira, Giuseppina Andreotti, Jaak Jaeken, Kristin A. Kantautas, Ethan O. Perlstein, Vanessa Dos Reis Ferreira

Research output: Contribution to journalReview articlepeer-review

10 Citations (Scopus)
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Abstract

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

Original languageEnglish
Article number8725
Number of pages19
JournalInternational Journal of Molecular Sciences
Volume23
Issue number15
DOIs
Publication statusPublished - 5 Aug 2022

Keywords

  • AI in drug discovery
  • biomarkers
  • congenital disorders of glycosylation
  • disease models
  • drug repositioning
  • orphan drugs

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