Pioneering QSAR Modeling Study of FAP-Targeting Radiopharmaceuticals Used in Oncology

Area of Science:

• Medicinal Chemistry
• Radiopharmacy
• Computational Chemistry

Background:

• Fibroblast Activation Protein (FAP) is a key target in the tumor microenvironment, driving cancer progression.
• Radiolabeled FAP inhibitors (FAPIs) are emerging as crucial tools for cancer diagnosis and therapy.
• Understanding structure-activity relationships is vital for developing potent FAPIs.

Purpose of the Study:

• To investigate the relationship between structural characteristics and inhibitory activity of FAPI radiopharmaceuticals.
• To develop predictive quantitative structure-activity relationship (QSAR) models for FAPI design.
• To identify potential FAPI candidates through virtual screening.

Main Methods:

• Employed 2D-QSAR (Multiple Linear Regression, Genetic Algorithm) and 3D-QSAR (Partial Least Squares, CoMFA, CoMSIA) analyses.
• Evaluated model performance using internal (Q² _LOO) and external (pred_R²) validation metrics.
• Conducted virtual screening of FDA-approved drugs against the FAP enzyme.

Main Results:

• Developed robust 2D-QSAR models with high predictive accuracy (e.g., R² _train=0.877, Q² _LOO=0.830).
• Achieved excellent parametric results with a 3D-QSAR CoMFA model (R²=0.988, pred_R²=0.642).
• Identified steric, hydrophobic, and hydrogen-bonding properties as critical for FAPI potency.
• Discovered 23 potential FAP inhibitors from FDA-approved drug screening.

Conclusions:

• This pioneering QSAR study provides valuable insights into FAPI radiopharmaceutical design.
• The identified structure-activity relationships and potential inhibitors can accelerate the development of novel FAP-targeted agents.
• Findings offer a foundation for designing more potent and effective radiopharmaceuticals for cancer management.