Under ONIOM Layers: Analysis of BCR-ABL Enzyme Inhibitors Through Bond-Critical Points and Natural Orbitals

Kelvyn M L Rocha1, Érica C M Nascimento2, João B L Martins1,2

  • 1Department of Pharmacy, Faculty of Health Sciences, University of Brasilia, Brasilia 70910-900, DF, Brazil.

PubMed

Insights

Ponatinib demonstrates stronger interactions and higher chemical stability than rebastinib in BCR-ABL tyrosine kinase inhibition. This suggests ponatinib may be more effective at hindering enzyme activity due to its electronic structure.

Area of Science:

  • Biochemistry
  • Computational Chemistry
  • Structural Biology

Background:

  • Tyrosine kinases, like BCR-ABL, are crucial drug targets.
  • Intermolecular interactions, including hydrogen bonds, regulate enzyme activity.
  • Understanding these interactions is key for drug design.

Purpose of the Study:

  • To investigate the electronic structure of intermolecular interactions between BCR-ABL and inhibitors.
  • To compare the binding of rebastinib and ponatinib at a molecular level.
  • To elucidate the role of electronic properties in kinase inhibition.

Main Methods:

  • Molecular docking using AutoDock Vina.
  • Quantum chemical calculations using the ONIOM method for full geometry optimization.
  • Analysis of Frontier Molecular Orbitals (FMOs) and Bond-Critical Points (BCPs).

Main Results:

  • Ponatinib formed stronger and more stable interactions with BCR-ABL residues (Glu286, Met318, Asp381) compared to rebastinib.
  • Ponatinib exhibited a significant increase in the Highest Occupied Molecular Orbital (HOMO)-Lowest Unoccupied Molecular Orbital (LUMO) gap.
  • This increased HOMO-LUMO gap suggests enhanced chemical stability for ponatinib.

Conclusions:

  • Ponatinib's superior binding interactions and increased electronic stability contribute to its potential for effective BCR-ABL inhibition.
  • The study provides insights into the molecular mechanisms underlying differential drug efficacy.
  • Computational methods like ONIOM are valuable for predicting drug performance based on electronic structure.

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