Deep learning-guided discovery of IL23/IL23R macromolecular inhibitors: An integrative framework combining virtual screening and experimental validation

Key Points

• IL23/IL23R inhibitors exhibit promising bioactivity, offering potential therapeutic options.
• Deep learning tools achieved high accuracy, outperforming traditional methods in virtual screening.
• Integrative framework combined computational predictions with rigorous experimental validation for improved outcomes.
• Findings may accelerate discovery of macromolecular drugs for inflammatory diseases, highlighting the need for further exploration.