Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches

Curr Med Chem. 2019;26(21):3874-3889. doi: 10.2174/0929867324666170712115411.

Abstract

Background: Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation.

Results: Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery. Similarity, searches and virtual screening are used to identify molecules with an increased probability to interact with drug targets of interest, while the other computational approaches are applied for the design and evaluation of molecules with enhanced activity and improved safety profile.

Conclusion: In this review are described the main in silico techniques used in rational drug design of antineoplastic agents and presented optimal combinations of computational methods for design of more efficient antineoplastic drugs.

Keywords: Antineoplastic agents; QSAR; cheminformatics; pharmacophore; rational drug design; virtual docking; virtual screening..

Publication types

  • Review

MeSH terms

  • Antineoplastic Agents / chemical synthesis*
  • Antineoplastic Agents / chemistry
  • Computer-Aided Design*
  • Drug Design*
  • Drug Evaluation, Preclinical / methods*
  • Humans
  • Models, Molecular
  • Quantitative Structure-Activity Relationship*

Substances

  • Antineoplastic Agents