Drug-induced conformational population shifts in topoisomerase-DNA ternary complexes

Area of Science:

• Biochemistry and Molecular Biology
• Computational Chemistry
• Pharmacology

Background:

• Type II topoisomerases (TOP2) are crucial enzymes involved in DNA replication and transcription.
• Many anti-cancer drugs function by inhibiting TOP2 activity, leading to DNA damage.
• Understanding precise drug-binding modes in TOP2 isoforms (TOP2-α and TOP2-β) is essential for drug development.

Purpose of the Study:

• To differentiate the binding mechanisms of VP-16, m-AMSA, and mitoxantrone in TOP2-α and TOP2-β cleavage complexes.
• To validate a novel scoring function, AutoDock4RAP, for assessing drug-DNA-enzyme interactions.
• To guide the design of more effective and specific TOP2-targeting anti-cancer agents.

Main Methods:

• Application of the AutoDock4RAP scoring function for molecular docking simulations.
• Utilizing molecular dynamics simulations to analyze conformational changes and binding stability.
• Comparison of computational predictions with existing crystallographic data.

Main Results:

• Docking accurately reproduced the known binding mode of VP-16 in TOP2-β, with a low root-mean-square deviation.
• Molecular dynamics confirmed VP-16's binding and residue R503 conformation in TOP2-β.
• Simulations indicated conformational flexibility in R503 for m-AMSA and mitoxantrone complexes, suggesting relaxation dynamics.
• The binding site for VP-16 in TOP2-α was identified and found to be similar to that in TOP2-β.

Conclusions:

• The AutoDock4RAP function effectively models drug interactions with TOP2 cleavage complexes.
• Distinct conformational dynamics exist between different drugs bound to TOP2 isoforms.
• These findings provide a foundation for designing novel TOP2-α specific anti-cancer drugs.