About This Project

Topoisomerase II is a key enzyme in cancer therapy, but existing inhibitors suffer from toxicity and resistance issues. This project focuses on the computational design of a novel Topoisomerase II inhibitor, using molecular docking and simulations to enhance binding affinity and selectivity. By identifying more effective inhibitors, this research provides a foundation for future synthesis, in vitro validation, and potential advancements in targeted cancer treatment.

Ask the Scientists

What is the context of this research?

Topoisomerase II is a key enzyme that regulates DNA topology during replication and transcription. Its dysregulation contributes to genomic instability, uncontrolled cell growth, and drug resistance, making it a key target in cancer therapy (1,2). Overexpression of Topoisomerase II is prevalent in breast, lung, and leukemia cancers, while mutations in the TOP2A gene can alter drug sensitivity, reducing treatment efficacy (3). Current inhibitors, such as etoposide, often lead to off-target toxicity and resistance, underscoring the urgent need for more selective and effective drugs (4).

This project employs computational drug design, using molecular docking and MD simulations to model inhibitor interactions before synthesis, predicting binding affinity, stability, and selectivity (5,6). By designing novel Topoisomerase II inhibitors with enhanced efficacy and reduced toxicity, this study lays a strong foundation for future experimental validation and therapeutic development.

What is the significance of this project?

Current Topoisomerase II inhibitors, such as etoposide and doxorubicin, target the enzyme’s DNA cleavage complex, stabilizing DNA breaks that lead to cell death. However, their non-specific binding often results in severe side effects and resistance, limiting their long-term effectiveness (7).

This project utilizes computational drug design to identify alternative binding sites and optimize inhibitor interactions, offering a more selective and targeted approach. Molecular docking and MD simulations provide a cost-effective and time-efficient method to predict binding affinity, stability, and selectivity before synthesis, reducing the trial-and-error process in drug discovery (8,9).

By synthesizing more selective inhibitors, this research has the potential to accelerate the development of safer, more effective cancer treatments, minimizing toxicity and resistance while paving the way for next-generation chemotherapy drugs.

What are the goals of the project?

This project aims to design, synthesize, and evaluate novel Topoisomerase II inhibitors using computational and experimental approaches. Molecular docking and MD simulations will identify high-affinity compounds, predicting binding interactions, stability, and selectivity before synthesis.

Selected inhibitors will be synthesized, purified, and confirmed via NMR and mass spectrometry, ensuring integrity. Organic chemists will optimize synthesis for efficiency and yield.

Selection criteria include Docking Score ≤ -10 kcal/mol, binding mode validation with key active site residues (hydrogen bonds, π-π stacking), and MD stability for at least 500 ns (10). Compounds must also satisfy Lipinski’s Rule of Five (11), a widely used guideline predicting oral drug bioavailability, and exhibit a favorable Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profile (12). Optimization ensures the best inhibitors advance toward cancer therapy development.