Discovery of anti-colon cancer agents targeting wild-type and mutant p53 using computer-aided drug design

Area of Science:

• Medicinal Chemistry
• Computational Drug Design
• Oncology

Background:

• p53 gene mutations are prevalent in over 50% of cancers, particularly 70% of colon cancers, necessitating urgent therapeutic strategies.
• The p53 protein's role in DNA repair, cell cycle regulation, and apoptosis makes it a critical target for cancer therapy.

Purpose of the Study:

• To apply in silico drug design approaches for developing novel quinoline derivatives with anticancer activity against colon cancer.
• To identify key molecular interactions and design compounds that can overcome p53 mutations in colon cancer.

Main Methods:

• 3D-Quantitative Structure-Activity Relationship (3D-QSAR) studies using CoMSIA/SEHA models to predict activity.
• Molecular docking and molecular dynamics simulations to analyze binding interactions with p53 protein (wild type and mutant).
• ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) property evaluation for designed compounds.

Main Results:

• Two robust CoMSIA/SEHA models demonstrated high predictive accuracy for colon cancer cell lines with differing p53 statuses (p53+/+ and p53-/-).
• Molecular docking identified critical interactions between designed quinoline derivatives and p53 active sites.
• Designed compounds showed potential for stable interactions with key residues, essential for overcoming p53 mutations, confirmed by MM-GBSA analysis.

Conclusions:

• In silico drug design effectively identified promising quinoline derivatives for colon cancer treatment.
• The designed compounds exhibit potential for stable binding to p53, offering a strategy to combat p53 mutations.
• This study provides a strong theoretical basis for the development of novel p53-targeted colon cancer therapeutics.