Cliff Function

Activity cliffs describe the phenomenon where structurally similar molecules exhibit drastically different biological activities, posing a significant challenge in drug discovery and other fields. Current research focuses on developing robust computational models, including image-based and language-based approaches (e.g., employing pre-trained models like ESM2), to accurately predict and understand these activity cliffs, particularly in areas like antimicrobial peptides. Overcoming the limitations of existing methods in identifying subtle structural changes driving these differences is crucial for improving the efficiency and accuracy of drug design and materials science. The development of improved predictive models has significant implications for accelerating the discovery of novel therapeutics and materials with desired properties.