Year: 2026
Type: article
Abstract: Enzyme function annotation is critical for decoding biological systems and enabling rational enzyme design. However, experimentally characterized enzyme functions remain available for only a small fraction of known protein sequences, resulting in a widening gap between rapidly expanding sequence space and reliable functional assignments. Recent advances in artificial intelligence (AI) have accelerated enzyme function annotation by facilitating accurate and high-throughput prediction from protein sequences. Here, we present CLEAN Database (CLEAN DB), a comprehensive resource encompassing >55 million enzyme function annotations across 1 098 305 strains, predicted by the CLEAN AI model. The database features an intuitive web interface that enables users to efficiently search, explore, and download enzyme function data through flexible query options. Additionally, powered by a protein language model, CLEAN DB supports mutation effect prediction through interactive heatmaps, structural overlays, and tabular data visualizations. We anticipate that CLEAN DB will serve as a valuable platform for advancing enzyme discovery and applications in synthetic biology, metabolic engineering, enzyme engineering, retrosynthesis, and drug discovery. The database is freely available at https://cleandb.platform.moleculemaker.org/.
Source: Nucleic Acids Research
DOI: 10.1093/nar/gkag1003
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,992
Awards: Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, BioFoundry: NSF iBioFoundry for Basic and Applied Biology, Global Centers: Reliable and Scalable Biofoundries for Biomanufacturing and Global Bioeconomy, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing: Molecule Maker Lab Institute (MMLI)
OpenAlex ID: W7222013322
