Finding the molecular scaffold of nuclear receptor inhibitors through high-throughput screening based on...

Area of Science:

• Biochemistry
• Medicinal Chemistry
• Computational Biology

Background:

• Nuclear receptors (NRs) are crucial protein targets involved in regulating gene expression and are implicated in various diseases.
• Developing effective NR inhibitors is essential for therapeutic interventions.
• Predictive models for NR-inhibitor activity can accelerate drug development.

Purpose of the Study:

• To introduce proteochemometric (PCM) modeling for analyzing the bioactivity between chemical compounds and NR targets.
• To develop and validate a PCM model for high-throughput screening of NR inhibitors.
• To identify and compare essential molecular scaffolds for major NR targets.

Main Methods:

• Proteochemometric modeling was employed to analyze compound-NR interactions.
• The developed PCM model was rigorously validated using internal and external datasets.
• In-silico predicted bioactive compounds were clustered by structural similarity to derive molecular scaffolds.

Main Results:

• The PCM model demonstrated high performance in predicting NR-inhibitor activity, with AUC values exceeding 0.870 (internal) and 0.746 (external).
• Analysis of predicted bioactive compounds revealed distinct molecular scaffolds for five major NR targets.
• The study successfully identified and compared essential bioactive scaffolds across different NR targets.

Conclusions:

• The developed PCM modeling approach is effective for high-throughput screening of NR inhibitors.
• The identified molecular scaffolds provide valuable guidance for future NR-related drug discovery efforts.
• This methodology can accelerate the identification of potential therapeutic NR-inhibitors.