Artificial intelligence for drug discovery and development in Alzheimer's disease

Curr Opin Struct Biol. 2024 Apr:85:102776. doi: 10.1016/j.sbi.2024.102776. Epub 2024 Feb 8.

Abstract

The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics, epigenomics, transcriptomics, proteomics, and metabolomics) analysis contributes to the understanding of the pathophysiology and precision medicine of the disease, including AD and AD-related dementia. In this review, we summarize the AI-driven methodologies for AD-agnostic drug discovery and development, including de novo drug design, virtual screening, and prediction of drug-target interactions, all of which have shown potentials. In particular, AI-based drug repurposing emerges as a compelling strategy to identify new indications for existing drugs for AD. We provide several emerging AD targets from human genetics and multi-omics findings and highlight recent AI-based technologies and their applications in drug discovery using AD as a prototypical example. In closing, we discuss future challenges and directions in AI-based drug discovery for AD and other neurodegenerative diseases.

Publication types

  • Review
  • Research Support, N.I.H., Extramural

MeSH terms

  • Alzheimer Disease* / drug therapy
  • Artificial Intelligence*
  • Drug Discovery / methods
  • Genomics / methods
  • Humans
  • Proteomics