Designing multi-target drugs for the treatment of major depressive disorder

Expert Opin Drug Discov. 2023 Jun;18(6):643-658. doi: 10.1080/17460441.2023.2214361. Epub 2023 May 19.

Abstract

Introduction: Major depressive disorders (MDD) pose major health burdens globally. Currently available medications have their limitations due to serious adverse effects, long latency periods as well as resistance. Considering the highly complicated pathological nature of this disorder, it has been suggested that multitarget drugs or multi-target-directed ligands (MTDLs) may provide long-term therapeutic solutions for the treatment of MDD.

Areas covered: In the current review, recent lead design and lead modification strategies have been covered. Important investigations reported in the last ten years (2013-2022) for the preclinical development of MTDLs (through synthetic medicinal chemistry and biological evaluation) for the treatment of MDD were discussed as case studies to focus on the recent design strategies. The discussions are categorized on the basis of pharmacological targets. Based on these important case studies, the challenges involved in different design strategies were discussed in detail.

Expert opinion: Even though large variations were observed in the selection of pharmacological targets, some potential biological targets (NMDA, melatonin receptors) are required to be explored extensively for the design of MTDLs. Similarly, apart from structure activity relationship (SAR), in silico techniques such as multitasking cheminformatic modeling, molecular dynamics simulation and virtual screening should be exploited to a greater extent.

Keywords: Major depressive disorder; cheminformatics; drug design; in silico techniques; multitarget drugs; structure activity relationship; synthetic medicinal chemistry.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alzheimer Disease* / drug therapy
  • Depressive Disorder, Major* / drug therapy
  • Drug Design
  • Humans
  • Ligands
  • Molecular Dynamics Simulation
  • Structure-Activity Relationship

Substances

  • Ligands