ENTRAF

ENTRAF organizes experimentally validated transcription factors from bacterial and archaeal genomes into a relational database that integrates structural, functional, and regulatory information for these proteins.

Key Features:

• Experimentally Validated TF Collection: Contains 1784 transcription factors across 25 bacterial and seven archaeal phyla, including Gammaproteobacteria, Bacillota, Actinomycetota, Thermoproteota, and Thermococci.
• Experimental Evidence Annotation: Documents protein structure information from X-ray or NMR structural data, binding of purified proteins, footprinting assays, site mutation, in vitro transcription assay, and PRiMer extension analysis.
• Regulatory Role Classification: Annotates global regulatory roles including carbon source assimilation, virulence, antibiotic resistance, stress, and DNA damage.
• Mechanistic and Structural Categorization: Describes regulatory mechanisms (activation, repression, dual activities), evolutionary families, structural classifications, functional categories, and protein families.
• Benchmark Dataset for Genome Prediction: Provides a well-annotated collection for enhancing transcription factor predictions in complete genomes.

Scientific Applications:

• Transcription Factor Identification: Serves as a reference for predicting transcription factors in newly sequenced bacterial and archaeal genomes.
• Comparative Regulatory Genomics: Enables analysis of transcription factor diversity, evolutionary relationships, and regulatory mechanisms across prokaryotic phyla.
• Structural Biology of Gene Regulation: Supports studies of protein structure-function relationships in transcriptional regulation through integrated X-ray and NMR structural data.
• Functional Annotation of Regulatory Networks: Facilitates characterization of global regulatory systems controlling carbon metabolism, virulence, antibiotic resistance, stress responses, and DNA damage repair.

Methodology:

ENTRAF was constructed by collecting experimentally validated transcription factors from the literature, organizing them into a relational database, and annotating each entry with experimental evidence types, regulatory mechanisms, structural classifications, and functional categories.