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AI approaches for the discovery and validation of drug targets.
Wenteler, Aaron; Cabrera, Claudia P; Wei, Wei; Neduva, Victor; Barnes, Michael R.
Afiliação
  • Wenteler A; Digital Environment Research Institute, Queen Mary University of London, London, United Kingdom.
  • Cabrera CP; Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom.
  • Wei W; MSD Discovery Centre, London, United Kingdom.
  • Neduva V; Digital Environment Research Institute, Queen Mary University of London, London, United Kingdom.
  • Barnes MR; Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom.
Article em En | MEDLINE | ID: mdl-39258224
ABSTRACT
Artificial intelligence (AI) holds immense promise for accelerating and improving all aspects of drug discovery, not least target discovery and validation. By integrating a diverse range of biological data modalities, AI enables the accurate prediction of drug target properties, ultimately illuminating biological mechanisms of disease and guiding drug discovery strategies. Despite the indisputable potential of AI in drug target discovery, there are many challenges and obstacles yet to be overcome, including dealing with data biases, model interpretability and generalisability, and the validation of predicted drug targets, to name a few. By exploring recent advancements in AI, this review showcases current applications of AI for drug target discovery and offers perspectives on the future of AI for the discovery and validation of drug targets, paving the way for the generation of novel and safer pharmaceuticals.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article