Peptide Design

Peptide design focuses on creating novel peptide sequences with desired properties, primarily for therapeutic applications. Current research heavily utilizes machine learning, employing architectures like graph neural networks, transformers, and generative models (including those incorporating reinforcement learning) to predict peptide properties and design sequences with optimized characteristics such as cell penetration or binding affinity to specific targets. These advancements are significantly accelerating drug discovery by reducing reliance on extensive experimental trials and enabling the exploration of a much larger chemical space than previously possible, leading to more effective and targeted therapeutics.