Protein-Protein Binding Affinity Prediction: Sequence vs. Structure

While structural information can enhance accuracy, it's not always mandatory for intermolecular binding affinity calculations. 'Sequence-based' or 'sequence-only' methods leverage algorithms and machine learning to predict binding affinities solely from amino acid sequences.

However, the accuracy of these methods can fluctuate depending on the specific protein-protein interaction and the quality of training data. Incorporating structural data, such as protein structures or binding site details, can often refine prediction accuracy.

Sequence-based methods offer valuable insights but might not always be adequately accurate independently, particularly for intricate protein-protein interactions. Combining them with structural information can significantly enhance the accuracy of binding affinity predictions.