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Ligify 2.0: a web server for predicted small molecule biosensors
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DOI：10.1093/nar/gkag458.png)
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Abstract
En 中文
Prokaryotic transcription factors (TFs) serve as small molecule biosensors with broad applications in biotechnology, yet only a fraction have been characterized. To address this gap, we recently described the bioinformatic method Ligify, which leverages information from genome context and enzyme reaction databases to predict a TF’s cognate effector molecule. Here, we report Ligify 2.0, a modern web server for Ligify predictions. We systematically evaluate 10 965 small molecules within the Rhea enzyme reaction database for associations to TFs, ultimately generating 13 435 hypothetical interactions between 1 362 small molecules and 3 164 TFs. We then develop an interactive web server (https://ligify.groov.bio) to search and visualize prediction data. Each TF sensor page includes visualizations for chemical ligand structures, interactive TF protein structures, and genome context. Pages also include metadata links, predicted promoter sequences, prediction confidence metrics, and references to relevant literature. A plasmid builder tool enables users to generate custom biosensor circuit designs. Finally, we provide case studies using Ligify 2.0 to identify two TFs from the pathogens Escherichia coli O157:H7 and Mycobacterium abscessus responsive to 4-hydroxybenzoate and Pseudomonas Quinolone Signal, respectively. The Ligify web server aims to facilitate the systematic characterization of biosensors for chemical-control of biological systems.
Keywords:
TF prediction
small molecule biosensors
genome context
enzyme reaction database
web server
Journal
IF:
13.1
Papers:
3.6W
Citations:
29.0W
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