Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

Current protein language models (PLMs) learn protein representations mainly based on
their sequences, thereby well capturing co-evolutionary information, but they are unable to …

For most proteins annotated as enzymes, it is unknown which primary and/or secondary
reactions they catalyze. Experimental characterizations of potential substrates are time …

Metabolic networks are interconnected and influence diverse cellular processes. The protein-
metabolite interactions that mediate these networks are frequently low affinity and …

Functional annotation of open reading frames in microbial genomes remains substantially
incomplete. Enzymes constitute the most prevalent functional gene class in microbial …

The turnover number k cat, a measure of enzyme efficiency, is central to understanding
cellular physiology and resource allocation. As experimental k cat estimates are unavailable …

The sustainable production of chemicals from renewable, nonedible biomass has emerged
as an essential alternative to address pressing environmental issues arising from our heavy …

Abstract The bacterial metadatabase Bac Dive (https://bacdive. dsmz. de) has developed
into a leading database for standardized prokaryotic data on strain level. With its current …

Genome-scale metabolic models (GEMs) are computational representations that enable
mathematical exploration of metabolic behaviors within cellular and environmental …