Learning to Model G-Quadruplexes: Current Methods and Perspectives

Iker Ortiz de Luzuriaga1,2, Xabier Lopez2,3, Adrià Gil1,4

  • 1CIC nanoGUNE BRTA, 20018 Donostia, Euskadi, Spain;

Insights

G-quadruplexes are DNA structures crucial for cancer therapy development. Computational methods, including classical and quantum approaches, are essential for understanding how small molecules stabilize these structures, aiding in drug design.

Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Chemistry
  • Medicinal Chemistry

Background:

  • G-quadruplexes, noncanonical DNA structures, are implicated in cancer via telomeres and oncogene promoters.
  • Stabilization of G-quadruplexes can disrupt tumor cell growth, making them therapeutic targets.
  • Mechanisms of G-quadruplex folding and stabilization by various molecules (cations, organic compounds, metal complexes) are not fully understood.

Purpose of the Study:

  • To review and compile computational studies on G-quadruplex formation, stabilization, and interactions with small molecules.
  • To highlight the synergy between experimental and computational approaches in understanding G-quadruplexes.
  • To categorize and discuss different in silico methods used in G-quadruplex research.

Main Methods:

  • Focus on in silico approaches, categorizing them into classical and quantum methods.
  • Classical methods: Long-timescale molecular dynamics simulations for analyzing dynamical information.
  • Quantum methods: Semiempirical, QM/MM, and DFT for explicit electronic structure simulation (providing static insights).

Main Results:

  • Computational methods are vital for rationalizing the interaction of small molecules with G-quadruplexes.
  • Classical simulations offer insights into dynamics, while quantum methods provide detailed electronic structure information.
  • A comprehensive overview of leading computational studies in the field is presented.

Conclusions:

  • Synergistic use of experimental and computational methods is crucial for advancing G-quadruplex research.
  • In silico approaches provide essential tools for understanding G-quadruplex stabilization and interactions.
  • This review consolidates current computational strategies for G-quadruplex-targeted drug development.