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Covalent drugs based on small molecules and peptides for disease theranostics.

Ying-Jin ZhangJian-Xiao LiangYin-Sheng XuYi-Xuan LiuYingying CuiZeng-Ying QiaoHao Wang
Published in: Biomaterials science (2023)
Biomacromolecules, such as proteins, nucleic acids and polysaccharides, are widely distributed in the human body, and some of them have been recognized as the targets of drugs for disease theranostics. Drugs typically act on targets in two ways: non-covalent bond and covalent bond. Non-covalent bond-based drugs have some disadvantages, such as structural instability and environmental sensitivity. Covalent interactions between drugs and targets have a longer action time, higher affinity and controllability than non-covalent interactions of conventional drugs. With the development of artificial intelligence, covalent drugs have received more attention and have been developed rapidly in pharmaceutical research in recent years. From the perspective of covalent drugs, this review summarizes the design methods and the effects of covalent drugs. Finally, we discuss the application of covalent peptide drugs and expect to provide a new reference for cancer treatment.
Keyphrases
  • artificial intelligence
  • machine learning
  • drug induced
  • deep learning
  • risk assessment
  • climate change
  • working memory
  • water soluble