LDM-DTI: A multimodal framework integrating pretrained language models and geometric graph networks for interpretable drug-target interaction prediction

Key Points

• Improved prediction of drug-target interaction enhances understanding of therapeutic options, driving better patient outcomes.
• The LDM-DTI framework combines pretrained language models with geometric graph networks to facilitate connection insights.
• Utilizing machine learning algorithms, the model demonstrates increased interpretability in predicting drug-target interactions.
• The approach supports future drug discovery by providing a transparent method for evaluating drug interactions based on molecular structures.