Nov 2025· Nucleic Acids Research· Vol 54, pp. D1469 - D1476· 6 citations· 25 references
Medicine
TL;DR
Macrocycle-DB is presented, the most extensive online database dedicated to macrocycles, featuring 45 525 compounds, including 76 approved drugs and 105 clinical candidates that target 2533 proteins.
Abstract
Abstract Macrocycles have gained significant attention in drug design owing to their distinctive structural and physicochemical features. Despite the abundance of available experimental data, there remains a need for a centralized resource to support macrocycle-based drug discovery. Here, we present Macrocycle-DB, the most extensive online database dedicated to macrocycles, featuring 45 525 compounds, including 76 approved drugs and 105 clinical candidates that target 2533 proteins. The database offers comprehensive structural information, experimental bioactivity data, and physicochemical properties for each macrocycle, along with co-crystal structures to visualize protein–ligand interactions. Additionally, Macrocycle-DB provides specialized descriptors, scaffold and linker details for synthetic macrocycles, and high-quality downloadable datasets to facilitate computational drug design. Macrocycle-DB is freely accessible at https://macro-db.dpbio.tech/ and https://macro-db.cn/.
Natural cyclic peptides have long served as a rich reservoir of bioactivity, occupying a unique region of the drug space that bridges the gap between small molecules and large biologics, and researchers are rationally engineering next-generation macrocycles, positioning them at the frontier of modern drug development.
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MIT News · Artificial Intelligence· news.mit.eduAug 27, 2026
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
