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Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action.
Azad, A K M; Fatima, Shadma; Capraro, Alexander; Waters, Shafagh A; Vafaee, Fatemeh.
Afiliação
  • Azad AKM; School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia.
  • Fatima S; School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia.
  • Capraro A; Department of Medical Oncology, Ingham Institute of Applied Research, Sydney, Australia.
  • Waters SA; School of Women's and Children's Health, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia.
  • Vafaee F; Molecular and Integrative Cystic Fibrosis Research Centre, UNSW Sydney and Sydney Children's Hospital, Sydney, Australia.
Patterns (N Y) ; 2(9): 100325, 2021 Sep 10.
Article em En | MEDLINE | ID: mdl-34278363
ABSTRACT
An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http//vafaeelab.com/COVID19repositioning.html), that enables a visual and quantitative investigation of the interplay between the primary drug targets and the SARS-CoV-2-host interactome in the human protein-protein interaction network. COVID-CDR prioritizes drug combinations with potential to act synergistically through different, yet potentially complementary, pathways. It provides the options for understanding multi-evidence drug-pair similarity scores along with several other relevant information on individual drugs or drug pairs. Overall, COVID-CDR is a first-of-its-kind online platform that provides a systematic approach for pre-clinical in silico investigation of combination therapies for treating COVID-19 at the fingertips of the clinicians and researchers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Patterns (N Y) Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Patterns (N Y) Ano de publicação: 2021 Tipo de documento: Article