Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/146460
Título: Systematic Review
Autor: Brasil, Sandra
Allocca, Mariateresa
Magrinho, Salvador C.M.
Santos, Inês
Raposo, Madalena
Francisco, Rita
Pascoal, Carlota
Martins, Tiago
Videira, Paula A.
Pereira, Florbela
Andreotti, Giuseppina
Jaeken, Jaak
Kantautas, Kristin A.
Perlstein, Ethan O.
Ferreira, Vanessa Dos Reis
Palavras-chave: AI in drug discovery
biomarkers
congenital disorders of glycosylation
disease models
drug repositioning
orphan drugs
Catalysis
Molecular Biology
Spectroscopy
Computer Science Applications
Physical and Theoretical Chemistry
Organic Chemistry
Inorganic Chemistry
Data: 5-Ago-2022
Resumo: 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.
Descrição: R.F. and acknowledge the funding from the Fundação para a Ciência e Tecnologia (FCT), Portugal. S.B. was supported by CDG & Allies—PAIN funding. M.A. acknowledges PhD program at the DISTABIF, Università degli Studi della Campania “Luigi Vanvitelli”, PhD fellowship POR Campania FSE 2014/2020 “Dottorati di Ricerca Con Caratterizzazione Industriale”.
Peer review: yes
URI: http://hdl.handle.net/10362/146460
DOI: https://doi.org/10.3390/ijms23158725
ISSN: 1422-0067
Aparece nas colecções:Home collection (FCT)

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