Illuminating the universe of enzyme catalysis in the era of artificial intelligence.

Cell Syst

Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA. Electronic address:

Published: August 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Scientific research has revealed only a minuscule fraction of the enzymes that evolution has generated to power life's essential chemical reactions-and an even tinier fraction of the vast universe of possible enzymes. Beyond the enzymes already annotated lie an astronomical number of biocatalysts that could enable sustainable chemical production, degrade toxic pollutants, and advance disease diagnosis and treatment. For the past few decades, directed evolution has been a powerful strategy for reshaping enzymes to access new chemical transformations: by harnessing nature's existing diversity as a starting point and taking inspiration from nature's most powerful design process, evolution, to modify enzymes incrementally. Recently, artificial intelligence (AI) methods have started revolutionizing how we understand and compose the language of life. In this perspective, we discuss a vision for AI-driven enzyme discovery to unveil a world of enzymes that transcends biological evolution and perhaps offers a route to genetically encoding almost any chemistry.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cels.2025.101372DOI Listing

Publication Analysis

Top Keywords

artificial intelligence
8
enzymes
6
illuminating universe
4
universe enzyme
4
enzyme catalysis
4
catalysis era
4
era artificial
4
intelligence scientific
4
scientific revealed
4
revealed minuscule
4

Similar Publications

Background: Subcellular localisation is a determining factor of protein function. Mass spectrometry-based correlation profiling experiments facilitate the classification of protein subcellular localisation on a proteome-wide scale. In turn, static localisations can be compared across conditions to identify differential protein localisation events.

View Article and Find Full Text PDF

Oral cancer is a major global health burden, ranking sixth in prevalence, with oral squamous cell carcinoma (OSCC) being the most common type. Importantly, OSCC is often diagnosed at late stages, underscoring the need for innovative methods for early detection. The oral microbiome, an active microbial community within the oral cavity, holds promise as a biomarker for the prediction and progression of cancer.

View Article and Find Full Text PDF

Postoperative aphasia (POA) is a common complication in patients undergoing surgery for language-eloquent lesions. This study aimed to enhance the prediction of POA by leveraging preoperative navigated transcranial magnetic stimulation (nTMS) language mapping and diffusion tensor imaging (DTI)-based tractography, incorporating deep learning (DL) algorithms. One hundred patients with left-hemispheric lesions were retrospectively enrolled (43 developed postoperative aphasia, as the POA group; 57 did not, as the non-aphasia (NA) group).

View Article and Find Full Text PDF

In recent AI-driven disease diagnosis, the success of models has depended mainly on extensive data sets and advanced algorithms. However, creating traditional data sets for rare or emerging diseases presents significant challenges. To address this issue, this study introduces a direct-self-attention Wasserstein generative adversarial network (DSAWGAN) designed to improve diagnostic capabilities in infectious diseases with limited data availability.

View Article and Find Full Text PDF

Applications driven by large language models (LLMs) are reshaping higher education by offering innovative tools that enhance learning, streamline administrative tasks, and support scholarly work. However, their integration into education institutions raises ethical concerns related to bias, misinformation, and academic integrity, necessitating thoughtful institutional responses. This article explores the evolving role of LLMs in midwifery higher education, providing historical context, key capabilities, and ethical considerations.

View Article and Find Full Text PDF