Competition Between Phenothiazines and BH3 Peptide for the Binding Site of the Antiapoptotic BCL-2 Protein

Aline Lagoeiro do Carmo1, Fernanda Bettanin2, Michell Oliveira Almeida3

  • 1Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, Brazil.

Frontiers in Chemistry
|April 21, 2020
PubMed

Insights

Phenothiazine compounds like thioridazine and trifluoperazine show potential in cancer drug development by stabilizing the BCL-2 protein. These compounds may compete with natural ligands, offering a new strategy to induce apoptosis in tumor cells.

Area of Science:

  • Computational chemistry and molecular biology
  • Drug discovery and development
  • Cancer research

Background:

  • Cancer cells evade apoptosis, a programmed cell death process crucial for preventing tumor formation.
  • The BCL-2 protein family and cysteine-proteases are key regulators of apoptosis.
  • Phenothiazine compounds are known to influence cellular death pathways.

Purpose of the Study:

  • To investigate the interaction of phenothiazine compounds with the BCL-2 protein.
  • To evaluate the pharmacological potential of phenothiazines in cancer therapy.
  • To computationally simulate the effects of phenothiazines on apoptosis-related targets.

Main Methods:

  • Molecular docking to study compound-protein interactions at the active site.
  • Molecular dynamics simulations to assess complex stability and mobility.
  • Binding free energy calculations to quantify interaction strength.

Main Results:

  • Thioridazine and trifluoperazine were found to enhance the stability of the BCL-2 protein.
  • These phenothiazines can compete with the natural BH3 peptide for binding to the BCL-2 active site.
  • Computational simulations provided insights into the structural basis of phenothiazine activity.

Conclusions:

  • Phenothiazines demonstrate potential as modulators of apoptosis through BCL-2 interaction.
  • Thioridazine and trifluoperazine represent promising candidates for further investigation in cancer drug development.
  • Computational approaches are valuable for understanding drug-target interactions and guiding drug design.