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Author Spotlight: Purifying High-Quality Tubulin to Study Protein Dynamics and Therapeutic Applications
Published on: October 11, 2024
Phenanthrenes as anti-liver cancer agents: A computational pipeline to tubulin inhibition
Saida Meliani1, Rafik Menacer2, Emilio Benfenati3
1Pharmaceutical Sciences Research Center CRSP, Zone of Activity ZAM, Nouvelle Ville Ali Mendjeli, Constantine, Algeria.
Abstract:
The rising incidence of liver cancer highlights the urgent need for novel therapies targeting crucial molecular mediators such as tubulin, a key protein involved in cancer cell proliferation. This study aims to address this need through a robust pipeline combining QSAR, molecular docking, dynamics, and ADME to identify new promising anti-liver-cancer agents, with a focus on virtual screening of purchasable Aldrich® Market Select phenanthrene analogs. A QSAR model with 92.7 % predictive accuracy highlighted HeavyAtomCount and Chi1n as pivotal structural descriptors correlating with anti-proliferative activity in HepG2 cells. Subsequently, QSAR-based virtual screening enabled the identification of top candidates based on their anti-proliferative potential. Virtual screening via molecular docking prioritized compound 31, which exhibited exceptional binding affinity (-8.684 kcal/mol) at tubulin's colchicine site. ADME profiling confirmed favorable pharmacokinetics and low BBB permeability for lead candidates. Molecular dynamics (MD) simulations (200 ns) further validated compound 31's stability, indicative of a tightly bound conformation. By integrating QSAR, docking, ADME, and MD, this work establishes a computationally rigorous pipeline for anticancer drug discovery, offering phenanthrene-based scaffolds as candidates for in vitro testing. These results not only elucidate structure-activity principles for tubulin inhibition but also provide a pipeline for accelerating drug discovery, especially novel anticancer agents.
Insights
Researchers identified novel phenanthrene compounds as potential liver cancer treatments by targeting tubulin. Computational methods like QSAR and molecular docking pinpointed promising drug candidates for further laboratory testing.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Oncology
Background:
- Liver cancer incidence is rising, necessitating new therapeutic strategies.
- Tubulin is a key protein target for anticancer drug development due to its role in cell proliferation.
Purpose of the Study:
- To identify novel anti-liver-cancer agents using a computational drug discovery pipeline.
- To screen phenanthrene analogs for potential tubulin inhibition and anti-proliferative activity.
Main Methods:
- Quantitative Structure-Activity Relationship (QSAR) modeling to identify key structural descriptors.
- Virtual screening including molecular docking and ADME profiling.
- Molecular dynamics (MD) simulations to assess drug candidate stability and binding.
Main Results:
- A QSAR model with 92.7% accuracy identified HeavyAtomCount and Chi1n as significant descriptors.
- Compound 31 showed high binding affinity (-8.684 kcal/mol) to tubulin's colchicine site.
- MD simulations confirmed the stable binding conformation of compound 31.
Conclusions:
- A robust computational pipeline integrating QSAR, docking, ADME, and MD was established for anticancer drug discovery.
- Phenanthrene scaffolds show promise as novel anticancer agents targeting tubulin.
- The findings provide a foundation for in vitro testing of identified lead compounds.
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