AlphaFold-based peptide structure prediction: Opportunities, limitations, and future directions.

AlphaFold models achieve high accuracy in peptide structure and complex prediction but struggle to capture dynamic conformational changes critical for bioactivity.

• Why it matters: Understanding peptide flexibility and transient interactions is vital for effective peptide drug development, yet static predictions often miss low-probability, functional conformations.
• What they did: The review highlights advances in AlphaFold series, including geometric reasoning and confidence metrics, and discusses combining these predictions with molecular dynamics and ensemble sampling to improve dynamic representation.
• The result: Integrating AlphaFold with dynamic simulation methods enhances predictive accuracy and supports structure-guided peptide drug design, bridging the gap between static models and complex biophysical behaviors.

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