IIC-DTI: A Contrastive Learning Enhanced Inter–Intra Molecular Fusing Framework for Drug–Target Interaction Prediction

Key Points

• The proposed framework enhances drug-target interaction prediction accuracy by employing contrastive learning techniques.
• Key findings indicate a marked increase in prediction performance using this approach, surpassing existing methods.
• This analysis involved a comprehensive assessment of multiple molecular features for robust interaction prediction.
• Implications highlight the need for advanced predictive models in drug discovery, paving the way for better therapeutic strategies.